JP7764880B2 - Biological information measurement system - Google Patents

Description

The disclosed embodiment relates to a biometric information measurement system.

Technology for sensing various types of information in toilets has been provided. For example, a toilet device that senses the properties of stool is known (see, for example, Patent Document 1). It is believed that information related to intestinal peristalsis can be inferred from such stool properties. Also, for example, a toilet device that senses fecal gas is known (see, for example, Patent Document 2). It is believed that information related to the intestinal environment can be inferred from such fecal gas.

Patent No. 7107338 Patent No. 4385402

However, there is room for improvement in the above-mentioned conventional technologies. For example, while it is possible to estimate information about intestinal peristalsis from the characteristics of stool, it is difficult to estimate health-related information that takes into account the intestinal environment. Also, while it is possible to estimate information about the intestinal environment from fecal gas, it is difficult to estimate health-related information that takes into account intestinal peristalsis. As such, estimation using only one element, as in the above-mentioned conventional technologies, makes it difficult to estimate information based on multiple elements, and it may be difficult to properly estimate information about the user's health. Therefore, there is a demand for a way to properly estimate information about the user's health.

The disclosed embodiments aim to provide a biometric information measurement system that can appropriately estimate information related to a user's health.

A biometric information measurement system according to one embodiment measures the biometric information of a user of a toilet room based on information about excrement discharged into the bowl of a toilet installed in the toilet room, and is characterized by comprising: a first detection unit that detects feces; a second detection unit that detects fecal gas; and a control unit that executes an estimation process to estimate at least one of the provided information or score related to the user's health based on the detection results of the first detection unit and the second detection unit, and controls the output of the results of the estimation process to an external device.

The health of the intestine is determined by the peristaltic movement of the outer wall of the intestine, which is primarily affected by stress, sleep, infections, etc., and the intestinal environment inside the intestine, which is primarily affected by diet. Furthermore, stool information (stool characteristics) is one indicator of peristaltic movement, and bowel gas information (amount or concentration of bowel gas) is one indicator of the intestinal environment. Therefore, according to one aspect of the embodiment, a bioinformation measurement system outputs information and scores related to the user's health based on stool information related to the user's peristaltic movement and bowel gas information related to the user's intestinal environment. This allows the output of information and scores related to the user's health that take into account the state of the outer wall and the state of the inner intestine, thereby enabling more accurate health support for the user.

The inventors' research has revealed that the overall health of the intestine is determined by the peristaltic movement of the outer wall of the intestine, which is primarily influenced by stress, sleep, infections, etc., and the intestinal environment inside the intestine, which is primarily influenced by diet. Conventional toilet devices that estimate only peristaltic movement or toilet devices that estimate the intestinal environment can only obtain information related to either peristaltic movement or the intestinal environment, making it impossible to accurately assess the health of the intestine as a whole. Furthermore, from only one type of information, it is not possible to determine which lifestyle factors, such as stress, sleep, or diet, are most problematic and what improvements are required. Furthermore, even behaviors such as visually observing the shape of excrement (stool observation) to estimate the health of the intestine (stool observation) are difficult to solve. Therefore, a bioinformation measurement system according to one aspect of the embodiment can appropriately estimate information related to the user's health by estimating the user's health based on the detection results of both stool and defecation gas.

In one aspect of the embodiment, the control unit of the biological information measuring system is characterized in that it estimates first biological information based on the properties of the stool from the detection results of the first detection unit, estimates second biological information based on the amount or concentration of the fecal gas from the detection results of the second detection unit, and executes control to output the first biological information and the second biological information to an external device.

The bioinformation measurement system according to one aspect of the embodiment displays the characteristics of stool, which is an indicator of peristalsis, and the amount or concentration of fecal gas, which is an indicator of the intestinal environment. This allows the user to better understand the cause of their condition and how to improve their lifestyle, thereby enabling more accurate health support for the user.

In one aspect of the embodiment, in the biological information measurement system, the control unit performs the estimation process using a larger number of samples of the detection results from the second detection unit than the number of samples of the detection results from the first detection unit.

While peristalsis is influenced by daily lifestyle habits and is prone to sudden changes, the intestinal environment changes slowly and is not significantly affected by recent lifestyle habits. Therefore, according to one aspect of the embodiment, a bioinformation measurement system estimates information about the user's health using a larger number of samples of data on the amount or concentration of fecal gas related to the intestinal environment than data on the properties of stool related to peristalsis, allowing for more accurate estimation of both peristalsis and the intestinal environment. Therefore, the bioinformation measurement system can appropriately estimate information about the user's health.

In one aspect of the embodiment, the biometric information measurement system is characterized in that the estimation process uses the detection result of the first detection unit obtained from a single toilet use and multiple detection results of the second detection unit obtained from multiple toilet use.

Stool properties can change significantly due to sudden stress, and properties can change if multiple bowel movements occur in one day. On the other hand, the intestinal environment changes slowly over a period of a week or more, with changes of around 2-3 days being due to data variability caused by diet, etc. Therefore, with a bioinformation measurement system according to one aspect of the embodiment, data on stool properties related to peristalsis is obtained from a single excretion, and data on the amount or concentration of bowel gas related to the intestinal environment is obtained from multiple excretion data, making it possible to appropriately convey comprehensive health-related information and scores to the user. Therefore, the bioinformation measurement system can appropriately estimate information related to the user's health.

In one aspect of the embodiment, the control unit executes the estimation process to estimate a higher score the higher the first evaluation corresponding to each classification of stool properties based on the detection results of the first detection unit, and to estimate a higher score the higher the second evaluation of the fecal gas based on the detection results of the second detection unit.

Stool properties are evaluated differently depending on their classification. For example, on the Bristol scale, a common indicator of stool properties, a banana-like shape in the middle indicates a good condition, with the condition worsening toward the ends. On the other hand, for fecal gas, which indicates the intestinal environment, a higher score indicates a more desirable condition. Therefore, according to a bioinformation measurement system according to one embodiment, when assessing intestinal condition, the better the classification of stool properties, the better the intestinal condition is estimated to be, and the higher the score of fecal gas, which indicates the intestinal environment, the better the intestinal condition is estimated to be. This allows for an appropriate estimation of intestinal condition as an overall score, and allows the user to be accurately informed of their intestinal condition. Therefore, the bioinformation measurement system can appropriately estimate information related to the user's health.

A biometric information measurement system according to one embodiment measures biometric information of a user of a toilet room based on information about excrement discharged into the bowl of a toilet installed in the toilet room, and is characterized by comprising: a first detection unit that detects information about intestinal peristalsis; a second detection unit that detects information about the intestinal environment; and a control unit that executes an estimation process to estimate at least one of the provided information or score related to the user's health based on the detection results of the first detection unit and the second detection unit, and controls the output of the results of the estimation process to an external device.

The health status of the intestine is determined by the peristaltic movement of the outer wall of the intestine, which is primarily affected by stress, sleep, infections, etc., and the intestinal environment inside the intestine, which is primarily affected by diet. Therefore, a bioinformation measurement system according to one aspect of the embodiment outputs information and scores related to the user's health based on information about the user's peristaltic movement and information about the user's intestinal environment. This allows the output of information and scores related to the user's health that takes into account the state of the outer wall and the state of the intestine, thereby enabling more accurate health support for the user. In this way, a bioinformation measurement system according to one aspect of the embodiment estimates information related to the user's health based on the detection of both peristaltic movement and the intestinal environment, thereby enabling appropriate estimation of information related to the user's health.

A biometric information measurement system according to one embodiment measures biometric information of a user of a toilet room based on information about excrement discharged into the bowl of a toilet installed in the toilet room, and is characterized by comprising a control unit that executes an estimation process to estimate at least one of the provided information or score related to the user's health based on the detection results from a first detection unit that detects feces and the detection results from a second detection unit that detects defecation gas, and that controls the output of the results of the estimation process to an external device.

The health status of the intestine is determined by the peristaltic movement of the outer wall of the intestine, which is primarily influenced by stress, sleep, infections, etc., and the intestinal environment inside the intestine, which is primarily influenced by diet. Furthermore, peristaltic movement depends on stool information, and the intestinal environment inside the intestine depends on bowel gas information. Therefore, according to one aspect of the embodiment, the bioinformation measurement system outputs information and scores related to the user's health based on stool information related to the user's peristaltic movement and bowel gas information related to the user's intestinal environment. This allows the output of information and scores related to the user's health that takes into account the condition of the outer wall and the condition of the intestine, thereby enabling more accurate health support for the user. In this way, the bioinformation measurement system according to one aspect of the embodiment estimates information related to the user's health based on the detection of both stool and bowel gas, thereby enabling appropriate estimation of information related to the user's health.

A biometric information measurement system according to one embodiment measures the biometric information of a user of a toilet room based on information about excrement discharged into the bowl of a toilet installed in the toilet room, and is characterized by comprising: a control unit that executes an estimation process to estimate at least one of the provided information or score related to the user's health based on the detection results of a first detection unit that detects information about intestinal peristalsis and the detection results of a second detection unit that detects information about the intestinal environment, and that controls the output of the results of the estimation process to an external device.

The health status of the intestine is determined by the peristaltic movement of the outer wall of the intestine, which is primarily influenced by stress, sleep, infections, etc., and the intestinal environment inside the intestine, which is primarily influenced by diet. Furthermore, peristaltic movement depends on stool information, and the intestinal environment inside the intestine depends on bowel gas information. Therefore, according to one aspect of the embodiment, the bioinformation measurement system outputs information and scores related to the user's health based on stool information related to the user's peristaltic movement and bowel gas information related to the user's intestinal environment. This allows the output of information and scores related to the user's health that takes into account the condition of the outer wall and the condition of the intestine, thereby enabling more accurate health support for the user. In this way, the bioinformation measurement system according to one aspect of the embodiment estimates information related to the user's health based on the detection of both stool and bowel gas, thereby enabling appropriate estimation of information related to the user's health.

According to one aspect of the embodiment, information about the user's health can be appropriately estimated.

FIG. 1 is a perspective view showing an example of the configuration of a toilet room according to an embodiment. FIG. 2 is a plan view illustrating an example of the configuration of the measurement device according to the embodiment. FIG. 3 is a diagram illustrating an example of an overall outline of a biological information measuring system according to an embodiment. FIG. 4 is a diagram illustrating an example of the configuration of a biological information measuring system according to the embodiment. FIG. 5 is a block diagram showing an example of the configuration of a toilet seat device according to an embodiment. FIG. 6 is a block diagram illustrating an example of the configuration of the control device according to the embodiment. FIG. 7 is a diagram illustrating an example of processing executed by the biological information measuring system according to the embodiment. FIG. 8 is a diagram showing an example of the configuration of a gas sensor. FIG. 9 is a diagram illustrating an example of the second evaluation based on a plurality of data. FIG. 10 is a diagram illustrating an example of estimation of the first evaluation according to the embodiment. FIG. 11 is a diagram illustrating an example of estimation of the second evaluation according to the embodiment. FIG. 12 is a diagram illustrating an example of estimation of provided information according to the embodiment. FIG. 13 is a diagram illustrating an example of information used to estimate a score according to the embodiment. FIG. 14 is a diagram illustrating an example of information used to estimate provided information according to the embodiment. FIG. 15 is a diagram illustrating an example of information used to estimate provided information according to the embodiment. FIG. 16 is a diagram illustrating an example of information provided by the biological information measuring system. FIG. 17 is a diagram illustrating an example of information provided by the biological information measuring system. FIG. 18 is a diagram illustrating an example of information provided by the biological information measuring system. FIG. 19 is a diagram illustrating an example of information according to the estimation result. FIG. 20 is a diagram illustrating an example of information according to the estimation result. FIG. 21 is a diagram showing an example of information relating to the user's intestinal activity. FIG. 22 is a diagram showing an example of recommendation information for a user. FIG. 23 is a diagram showing an example of recommendation information for a user. FIG. 24 is a diagram showing an example of information about other users provided to a user. FIG. 25 is a diagram showing an example of a display mode of information provided to a user. FIG. 26 is a diagram showing an example of recommendation information for a user. FIG. 27 is a diagram showing an example of information about other users provided to a user. FIG. 28 is a diagram showing an example of information about users who have a relationship with the user. FIG. 29 is a diagram showing an example of rank information related to users. FIG. 30 is a diagram showing an example of information notification to a user. FIG. 31 is a diagram showing an example of information notification according to the user's usage status. FIG. 32 is a diagram showing an example of information notification according to the user's usage status.

Embodiments of the biometric information measurement system disclosed herein will be described in detail below with reference to the accompanying drawings. Note that the present invention is not limited to the embodiments described below.

1. Embodiment
The biological information measurement system according to each embodiment described below manages information about the user's health estimated based on the detection results of a first detector 21, which is a detector that detects stool, and a second detector 22, which is a detector that detects defecation gas. In the following example, an imaging device having a line sensor and generating an image is described as an example of the first detector 21, and a gas detection device having a semiconductor gas sensor is described as an example of the second detector 22. Note that the first detector 21 and the second detector 22 can have any configuration as long as they can acquire (detect) the desired information, and this will be discussed later. Note that defecation gas here refers to gas released from the intestines, and includes, for example, gas released simultaneously with defecation and gas not released simultaneously with defecation.

Below, we will provide an overview of the toilet room R, where images and gas information are collected, and the vital signs measurement system 1, followed by a description of the various processes performed by the vital signs measurement system 1 and the configuration for performing those processes.

<1-1. Example of toilet room configuration>
First, the configuration of a biological information measurement system according to an embodiment will be described with reference to Fig. 1. Fig. 1 is a perspective view showing an example of the configuration of a biological information measurement system according to an embodiment. Note that Fig. 1 shows a toilet seat 5 and a toilet lid 9 in a see-through state in order to illustrate the configuration of a measurement device 4 and a first detection unit 21.

As shown in FIG. 1, a toilet 7 is installed on a floor surface F in a toilet room R. Note that hereinafter, the direction facing the interior of the toilet room R from the floor surface F may be referred to as "up." In the toilet room R, components of the vital information measurement system 1, such as a suction device 10, a measuring device 4 that detects gas including a second detection unit 22 that is a gas detection device, and a first detection unit 21, are arranged.

The toilet bowl 7 is a toilet bowl, and has a bowl portion 8 formed therein. The bowl portion 8 has a downwardly concave shape and is the portion that receives the user's excrement. The toilet bowl 7 is not limited to being a floor-standing type as shown in the figure, and may be of any type, such as a wall-mounted type, as long as the biometric information measurement system 1 is applicable. The toilet bowl 7 has a rim portion around the entire edge of the opening facing the bowl portion 8. For example, a flush water tank that stores flush water may be installed near the toilet bowl 7 in the toilet room R, or a so-called tankless type may be used, in which no flush water tank is installed.

For example, when a user operates a flushing operation unit (not shown) provided in the toilet room R, a toilet flush is performed by supplying flush water to the bowl portion 8 of the toilet 7. The flushing operation unit may be an operation lever or a touch operation on a toilet flush object displayed on the operation device 30. Note that the flushing operation unit is not limited to an operation lever or the like that allows the user to manually flush the toilet, but may also be one that flushes the toilet when a sensor that detects the user's body, such as a seat sensor, detects the user's presence.

The toilet seat device 2 is attached to the top of the toilet bowl 7 and comprises a main body 3, a measuring device 4, a toilet seat 5, a cleaning nozzle 6, and a first detection unit 21. The measuring device 4 and the first detection unit 21 may be provided as separate devices from the toilet seat device 2, as will be described later. The toilet seat device 2 is placed on top of the toilet bowl 7, which is formed with a bowl 8 that receives excrement. The toilet seat device 2 is placed on top of the toilet bowl 7 so that the cleaning nozzle 6 advances into the bowl 8 before spraying cleaning water. The toilet seat device 2 may be attached detachably to the toilet bowl 7, or may be attached integrally with the toilet bowl 7.

The toilet seat device 2, using components such as the measuring device 4, measures the biometric information of the user of the toilet room R based on the feces gas discharged into the bowl portion 8 of the toilet stool 7 installed in the toilet room R. The measuring device 4 has a suction device 10 and a second detection unit 22. The toilet seat device 2, using components such as the first detection unit 21, measures the biometric information of the user of the toilet room R based on the feces discharged into the bowl portion 8 of the toilet stool 7 installed in the toilet room R. The measuring device 4 and the first detection unit 21 are described in detail in Figure 2.

As shown in Figure 1, the toilet seat 5 is formed in an annular shape and is positioned along the edge (rim) of the bowl portion 8 so as to overlap the opening of the toilet bowl 7. A user sits on the toilet seat 5. The toilet seat 5 functions as a seating portion that supports the buttocks of the seated user. A toilet lid 9 is attached to the toilet seat device 2 as needed, but the toilet seat device 2 does not necessarily have to have a toilet lid 9.

The cleaning nozzle 6 is a nozzle for spraying water for cleaning. The cleaning nozzle 6 is configured to be movable forward and backward relative to the housing of the main body 3 by being driven by a drive source such as an electric motor (such as the nozzle motor 61 in Figure 5). The cleaning nozzle 6 is also connected to a water source such as a water pipe (not shown). When the cleaning nozzle 6 is in an advanced position relative to the housing of the main body 3 (also referred to as the "advanced position") as shown in Figure 1, it sprays water from the water source onto the user's body to cleanse their private parts.

In Figure 1, the cleaning nozzle 6 is shown in the advanced position. The cleaning nozzle 6 may also be used to clean the inside of the toilet bowl 7 (bowl portion 8, etc.). The cleaning nozzle 6 may be used to switch between a private parts cleaning mode, which cleans the private parts of the user, and a toilet bowl cleaning mode, which sprays water inside the toilet bowl 7. For example, the cleaning nozzle 6 may be used to switch between the private parts cleaning mode and the toilet bowl cleaning mode in accordance with control by the toilet seat device 2.

The operating device 30 is provided in the toilet room R. The operating device 30 is provided in a position where it can be operated by a user. The operating device 30 is provided in a position where it can be operated by a user when seated on the toilet seat 5. In FIG. 1, the operating device 30 is provided on the wall W to the left of the user seated on the toilet seat 5. Note that the operating device 30 may be provided in various ways, not just on a wall, as long as it is accessible to a user seated on the toilet seat 5. For example, the operating device 30 may be provided integrally with the toilet seat device 2.

The operating device 30 is connected to the toilet seat device 2 via a predetermined network so that they can communicate with each other via a wired or wireless connection. For example, the toilet seat device 2 and the operating device 30 may be connected in any manner that allows for the transmission and reception of information, and may be connected to each other so that they can communicate with each other via a wired connection or a wireless connection.

The operation device 30 accepts various operations from the user via a display surface (e.g., display screen 31) using, for example, a touch panel function. The operation device 30 may also be equipped with switches and buttons, and may accept various operations via the switches and buttons. The display screen 31 is the display screen of a tablet terminal or the like, realized by, for example, a liquid crystal display or an organic EL (Electro-Luminescence) display, and is a display device for displaying various information. In other words, the operation device 30 accepts input from the user via the display screen 31 and also outputs information to the user. The display screen 31 is a display device that displays various information.

The operating device 30 accepts user operations to control various functions provided within the toilet room R. The operating device 30 accepts user operations to control the execution of local cleansing by the toilet seat device 2. For example, the operating device 30 may have switches, buttons, etc. that accept the user operations described above, and may execute various processes in response to the user's contact with the switches, buttons, etc. Note that the above is just one example, and the operating device 30 may also accept user operations to execute various processes. Furthermore, a user terminal such as a user's smartphone (corresponding to the display device 300 in Figure 3) may have functions equivalent to those of the operating device 30.

The biological information measurement system 1 uses various configurations and processes described below to measure the biological information of a user of the toilet room R based on the stool and defecation gas discharged into the bowl portion 8 of the toilet 7 installed in the toilet room R. The biological information measurement system 1 executes control to appropriately measure the stool and defecation gas. The biological information measurement system 1 provides information to a user terminal such as the user's smartphone (corresponding to the display device 300 in Figure 3) based on information collected through measurements, etc. The biological information measurement system 1 may also provide information to the operating device 30 (or display screen 31) of the toilet room R based on information collected through measurements, etc.

<1-2. Configuration of the measuring device>
Next, the configuration of the measuring device 4 will be described with reference to Fig. 2. Fig. 2 is a plan view showing an example of the configuration of a measuring device according to an embodiment. In the example shown in Fig. 2, the measuring device 4 and the first detection unit 21 are disposed inside the main body 3. Fig. 2 illustrates the configuration of the measuring device 4 and the first detection unit 21 with the housing (cover) of the main body 3 removed from the location where the measuring device 4 and the first detection unit 21 are disposed.

The measuring device 4 has a suction device 10 that sucks gas from within the bowl portion 8 of the toilet 7, and a second detection unit 22 that detects the components of the sucked gas.

The suction device 10 has a fan for sucking gas within the bowl portion 8 of the toilet 7. A duct 11 that communicates with the inside of the bowl portion 8 of the toilet 7 is connected to the suction device 10. The duct 11 functions as a flow path for allowing gas within the bowl portion 8 to flow into the measuring device 4. By driving the fan, the suction device 10 sucks gas within the bowl portion 8 using the duct 11 as a flow path. For example, the suction device 10 performs suction-related processing under the control of the control device 100. Note that if the suction device 10 is used in common with a deodorizing device or the like incorporated in the toilet seat device 2, the suction device 10 may be controlled by a control means (device) separate from the control device 100.

The second detection unit 22 detects fecal gas. The second detection unit 22 detects information related to the intestinal environment. The second detection unit 22 performs processing related to the detection of components of gas aspirated by the suction device 10. In FIG. 2, the second detection unit 22 is located downstream of the suction device 10 when viewed from the bowl portion 8 side. Note that FIG. 2 is merely an example, and the second detection unit 22 may be located in any position as long as it is capable of introducing gas aspirated by the suction device 10. The second detection unit 22 is connected to a duct 12 that communicates with the outside of the main body portion 3. The duct 12 functions as a flow path for discharging gas within the second detection unit 22 from the measuring device 4. For example, when the suction device 10 is driven, gas within the second detection unit 22 is released to the outside of the measuring device 4 via the duct 12 as a flow path.

For example, the second detection unit 22 executes processing related to gas detection under the control of the control device 100. The second detection unit 22 includes a gas sensor 40 that reacts to gas contained in the air. The gas sensor 40 detects specific components of the gas. For example, a semiconductor gas sensor is used as the gas sensor 40. Note that the above is merely an example, and the gas sensor is not limited to the semiconductor gas sensor 40, and multiple types of sensors of any type may be used. Note that the gas sensor 40 may also be used as a single unit that combines sensors of multiple principles, such as a semiconductor type and an infrared absorption type. For example, the gas sensor 40 detects fecal gas, which indicates the user's intestinal environment; this will be discussed later.

The first detector 21 detects stool. The first detector 21 detects information related to the peristaltic movement of the intestines. The first detector 21 detects stool (defecation) excreted by the user by capturing an image of the inside of the bowl portion 8 of the toilet 7. The first detector 21 is an image sensor. The first detector 21 has a light-receiving unit 50. For example, the light-receiving element is a line sensor in which a CCD (Charge Coupled Device) sensor or a CMOS (Complementary Metal Oxide Semiconductor) sensor is arranged in a row. Note that the light-receiving element is not limited to a line sensor (one-dimensional image sensor), and various types of sensors such as an area sensor (two-dimensional image sensor) may also be used. Note that the first detector 21 may have a configuration that emits light of a predetermined wavelength (such as the light-emitting element 51 in Figure 7), but this will be discussed later.

In Figure 2, the light receiving unit 50 of the first detection unit 21 is positioned to receive light from area AD1 within the bowl portion 8 of the toilet bowl 7. For example, the light receiving unit 50 is positioned to receive light reflected from stool falling within the bowl portion 8 of the toilet bowl 7. Image capture of falling stool by the first detection unit 21 will be described in Figure 7. Note that the light receiving unit 50 of the first detection unit 21 may detect stool in any state, such as stool after it has hit water, as long as it is able to acquire information necessary to estimate (determine) the properties of the stool, not just while it is falling.

For example, the light receiving unit 50 may detect the stool after it has fallen. In this case, the light receiving unit 50 may be positioned to capture an image of the water seal portion of the toilet bowl 7 (for example, the portion of the bowl portion 8 where the water seal collects). The light receiving unit 50 may be an area sensor (two-dimensional image sensor). In this way, the first detection unit 21 may be positioned in any location and any image sensor may be used, as long as it is capable of detecting stool excreted in the toilet bowl 7 and is capable of estimating the desired information.

<1-3. Example of an overall overview of a biological information measurement system>
Next, an example of an overall overview of the biological information measurement system 1 will be described with reference to Fig. 3 and Fig. 4. Fig. 3 is a diagram showing an example of an overall overview of the biological information measurement system according to an embodiment. Fig. 4 is a diagram showing an example of the configuration of the biological information measurement system according to an embodiment. Note that Figs. 3 and 4 only show a portion of the configuration of the biological information measurement system 1 that is necessary for explanation, and explanations of points similar to those described above will be omitted as appropriate.

As shown in FIG. 4, the biological information measurement system 1 includes a toilet seat device 2 having components such as a first detection unit 21, a second detection unit 22, and a control device 100, a display device 300, and a server device 400. The biological information measurement system 1 may include multiple toilet seat devices 2, multiple display devices 300, and multiple server devices 400.

The toilet seat device 2 is a device placed in the toilet room R. The toilet seat device 2 communicates with other devices such as the display device 300 and the server device 400. The toilet seat device 2 may also perform processing (personal identification) to acquire information for identifying a user who uses the toilet bowl 7 in the toilet room R to defecate. The toilet seat device 2 uses personal identification to collect information on each of multiple users, such as a family, separately. For example, the toilet seat device 2 acquires information for identifying a user who uses the toilet bowl 7 to defecate, and identifies the user, by communicating with the display device 300 owned by the user or by the user operating the operating device 30. For example, the toilet seat device 2 communicates with the display device 300 owned by the user and receives from the display device 300 a user ID (also simply referred to as "ID"), which is user identification information for identifying the user. The toilet seat device 2 may use any method to identify a user, as long as it is possible to identify a user who uses the toilet bowl 7 in the toilet room R.

As shown in FIG. 3, the first detection unit 21 has a light receiving unit 50 and detects stool. The second detection unit 22 has a gas sensor 40 and detects defecation gas. The control device 100 is a computer (information processing device) that executes a process (also referred to as an "estimation process") to estimate information about the user's health based on the detection results of the first detection unit 21 and the second detection unit 22, and controls the output of the results of the estimation process to the outside. The control device 100 estimates provided information or a score (hereinafter referred to as a "bowel score") about the user's health through the estimation process, which will be described later.

The control device 100 also communicates with devices that display information to users, such as the display device 300, using short-range wireless communication functions such as Bluetooth (registered trademark), BLE (Bluetooth Low Energy), and infrared. The control device 100 may also be able to communicate with the display device 300 without going through network N. Note that the control device 100 may be connected to devices such as the display device 300 in any way as long as it is possible to send and receive information; for example, it may be connected so that communication is possible via a specified network (such as network N) such as the Internet, either wired or wirelessly.

Note that while Figure 4 shows a case in which the toilet seat device 2 has a first detection unit 21, a second detection unit 22, and a control device 100, this is not limited to this. For example, the control device 100 may be provided separately from the first detection unit 21 and the second detection unit 22, and may control the first detection unit 21 and the second detection unit 22 and acquire each piece of information by communicating with the first detection unit 21 and the second detection unit 22 wirelessly or via a wired connection.

The control device 100 may also be a device located outside the toilet room R. In this case, the control device 100 may be communicably connected to devices located inside the toilet room R, such as the toilet seat device 2, the first detection unit 21, and the second detection unit 22, via a predetermined network (e.g., network N) such as the Internet, either wired or wirelessly, and may be able to acquire desired information.

Furthermore, the first detection unit 21 and the second detection unit 22 may be controlled by a control means separate from the control unit 100. In this case, the control unit 100 is a first control unit that performs various information processing such as estimation processing, and the biological information measurement system 1 may have a second control unit that is a device separate from the control unit 100 as a device that controls the first detection unit 21 and the second detection unit 22. In this way, the biological information measurement system 1 may have the control unit 100, which is a first control unit that performs various information processing such as estimation processing using information from the first detection unit 21 and the second detection unit 22, and a detection unit control unit, which is a second control unit that controls the first detection unit 21 and the second detection unit 22.

For example, the first control device and the second control device may be connected to each other via a predetermined network (e.g., network N) such as the Internet, either wired or wirelessly, and the first control device may perform estimation processing using the detection results of the first detection unit 21 and the detection result information of the second detection unit 22 received from the second control device. For example, the first control device may be a mobile terminal (device) such as a smartphone or laptop computer that can be carried by an administrator of the biometric information measurement system 1.

The display device 300 is a display device (computer) that displays information to be provided to a user. For example, the display device 300 may be a user terminal (mobile terminal) owned by the user. In this case, the display device 300 is realized by, for example, a smartphone, mobile phone, PDA (Personal Digital Assistant), tablet terminal, or notebook PC (Personal Computer). For example, the display device 300 is connected to devices included in the biometric information measurement system 1, such as the control device 100, via a predetermined network (such as network N) so as to be able to communicate with each other via wired or wireless communication.

The display device 300 transmits and receives information to and from the control device 100. The display device 300 receives information to be provided to the user from the control device 100. The display device 300 receives information about the user's health estimated by the estimation process of the control device 100. The display device 300 receives provided information or a score (intestinal score) about the user's health as information about the user's health. The display device 300 displays the information about the user's health received from the control device 100. Examples of information displayed by the display device 300 will be described later.

As shown in FIG. 3, the server device 400 is a computer such as a cloud server. The server device 400 is communicatively connected to devices such as the display device 300 via a predetermined network (e.g., network N) such as the Internet, either wired or wirelessly. Note that the server device 400 may be connected to devices such as the display device 300 in any manner as long as it is possible to send and receive information; it may be communicatively connected via a wired or wireless connection. The server device 400 may also be communicatively connected to the control device 100, etc., to receive raw data from measurements, process the data, and transmit the results to the display device 300.

The server device 400 stores the information collected from the display device 300 in a storage unit. The server device 400 collects information about the health of each user and stores it in a storage unit. For example, the server device 400 stores the health information of each user in a storage unit in association with information that identifies the user (such as an ID).

<1-3-1. Other configuration examples of biological information measurement system>
Note that the above is merely an example, and any device configuration that can realize the desired processing can be adopted for the biological information measurement system 1. In this regard, several examples of system configurations other than those described above will be described below.

Furthermore, the biological information measurement system 1 does not need to have at least one of the first detection unit that detects stool and the second detection unit that detects defecation gas. In this case, the control device 100 receives information from a detection unit not included in the biological information measurement system 1, and performs various information processing such as estimation processing using the received information. For example, the biological information measurement system 1 does not need to have at least one of the measurement device 4 and the first detection unit 21.

For example, if the biological information measurement system 1 does not include a measuring device 4, the control device 100 of the biological information measurement system 1 is communicatively connected to the measuring device 4 via wired or wireless communication and receives information about the fecal gas detected by the second detection unit 22 from the measuring device 4. In this case, the control device 100 of the biological information measurement system 1 performs the estimation process using the information about the fecal gas received from the measuring device 4 that is not included in the biological information measurement system 1.

For example, if the biological information measurement system 1 does not have a first detection unit 21, the control device 100 of the biological information measurement system 1 is communicatively connected to the first detection unit 21 via wired or wireless communication and receives information about the stool detected by the first detection unit 21 from the first detection unit 21. In this case, the control device 100 of the biological information measurement system 1 performs estimation processing using information about fecal gas received from the first detection unit 21 that is not included in the biological information measurement system 1.

Note that if the biological information measurement system 1 does not have both the measurement device 4 and the first detection unit 21, the control device 100 of the biological information measurement system 1 performs estimation processing using information related to defecation gas received from the measurement device 4 and information related to stool received from the first detection unit 21.

Alternatively, the biological information measurement system 1 may only have a configuration for acquiring detected information and performing estimation processing using the acquired information. In this case, the biological information measurement system 1 may only have the control device 100, which may acquire (receive) desired information by communicating with other devices, perform various information processing such as estimation processing using the acquired information, and transmit the desired information to the other devices.

Furthermore, the display device 300 does not have to be included in the biological information measurement system 1, or it may be included in the biological information measurement system 1. For example, if the display device 300 is an operation device 30 in the toilet room R, the display device 300 may be included in the biological information measurement system 1. In this case, the operation device 30 has the function of displaying information related to the user's health.

Furthermore, the device configuration and placement of the server device 400 in the biometric information measurement system 1 can be any configuration as long as it can communicate with devices such as the display device 300 and perform processing. For example, when the server device 400 is configured on the cloud as shown in FIG. 3, it may be configured from multiple computers (servers). For example, the server device 400 may be a mobile terminal (device) such as a laptop computer that can be carried by an administrator of the biometric information measurement system 1. Furthermore, the server device 400 may be placed in the toilet room R.

<1-4. Functional configuration of the toilet seat device>
Next, the functional configuration of the toilet seat device 2 will be described with reference to Fig. 5. Fig. 5 is a block diagram showing an example of the configuration of a toilet seat device according to an embodiment. As shown in Fig. 5, the toilet seat device 2 includes a human presence sensor 32, a seating sensor 33, an illuminance sensor 34, a control device 100, a nozzle motor 61, and a cleaning nozzle 6.

Note that the configuration of the toilet seat device 2 shown in FIG. 5 is merely an example, and if each component is provided separately, the toilet seat device 2 may have only the toilet seat 5. As such, the configuration of the toilet seat device 2 shown in FIG. 5 is merely an example, and the toilet seat device 2 can have any configuration. The human presence sensor 32, seating sensor 33, illuminance sensor 34, etc. may be disposed in any location as long as the desired sensing is possible. Furthermore, the toilet seat device 2 only needs to be able to detect a user sitting on the toilet seat 5, and it only needs to have at least one of the human presence sensor 32, seating sensor 33, and illuminance sensor 34. The toilet seat device 2 transmits and receives information to and from information processing devices such as the display device 300 and server device 400 via a predetermined network (such as the Internet) via a communication device (such as the communication unit 110 of the control device 100 in FIG. 6), either wired or wirelessly.

The human presence sensor 32 has the function of detecting a human body. For example, the human presence sensor 32 is used as a seating detection means for detecting a user sitting on the toilet seat 5. For example, the human presence sensor 32 is implemented by a pyroelectric sensor that uses an infrared signal. For example, the human presence sensor 32 may be implemented by a μ (microwave) wave sensor. For example, the human presence sensor 32 is an infrared light-emitting/receiving distance sensor, and may detect a human body present near the toilet seat 5 immediately before the person (user) sits on the toilet seat 5, or a user who has sat on the toilet seat 5.

The human presence sensor 32 also functions as a seat-leaving detection sensor that detects when a user leaves the toilet seat 5. The human presence sensor 32 detects whether the user is seated on the toilet seat 5. The human presence sensor 32 outputs a detection signal to the control device 100. Note that the above is just one example, and the human presence sensor 32 may detect a human body by various means, not limited to the above. For example, the human presence sensor 32 detects a person (such as a user) approaching the toilet seat 5.

The seat sensor 33 has the function of detecting a person sitting on the toilet seat device 2. For example, the seat sensor 33 is used as a seat detection means for detecting a user sitting on the toilet seat 5. For example, the seat sensor 33 is realized by a load sensor or the like. The seat sensor 33 detects when a user sits on the toilet seat 5. The seat sensor 33 can detect when a user sits on the toilet seat 5.

The seat sensor 33 also functions as a seat-vacation detection sensor that detects when a user leaves the toilet seat 5. The seat sensor 33 detects whether the user is seated on the toilet seat 5. Note that the above is just one example, and the seat sensor 33 may detect whether a person is seated on the toilet seat device 2 by various means, not limited to the above. The seat sensor 33 outputs a seat detection signal to the control device 100.

The illuminance sensor 34 is a sensor that detects illuminance. For example, the illuminance sensor 34 is used as a seating detection means that detects when a user is sitting on the toilet seat 5. For example, the illuminance sensor 34 is positioned facing the bowl portion 8 and detects the illuminance within the bowl portion 8.

The illuminance sensor 34 also functions as a seat-leave detection sensor that detects when a user leaves the toilet seat 5. The illuminance sensor 34 detects whether the user is seated on the toilet seat 5. Note that the above is just one example, and the illuminance sensor 34 may be placed in any position as long as it can detect whether a user is sitting on the toilet seat 5 based on the illuminance.

The control device 100 controls various components and processes. The control device 100 is a computer (information processing device) that performs various information processing related to the detection (measurement) of feces and gas. The control device 100 may be any device that has the necessary components for control, such as a microcomputer.

The control device 100 controls various components for detecting (measuring) stool. The control device 100 controls the first detection unit 21. The control device 100 transmits control information to the first detection unit 21 for controlling the electronic shutter function of the light receiving unit 50. Note that the shutter function of the light receiving unit 50 is not limited to an electronic shutter, and any method such as a mechanical shutter can be used as long as the desired detection is possible. Furthermore, if the first detection unit 21 has a light emitting unit such as a light emitting element, the control device 100 may transmit control information to the first detection unit 21 for controlling the lighting and extinguishing of the light emitting unit.

For example, the control device 100 causes the first detection unit 21 to emit light and receive light. The control device 100 controls the first detection unit 21 to cause the light-emitting unit to emit light and the light-receiving unit 50 to receive light. The control device 100 causes the first detection unit 21 to emit light and receive light during the period when the seating sensor 33 detects that a user is sitting on the toilet seat 5.

The control device 100 controls various components for detecting (measuring) gas. The control device 100 controls the second detection unit 22. The control device 100 transmits control information to the second detection unit 22 via a wired connection. The control device 100 may also transmit control information to the second detection unit 22 wirelessly. For example, if the control device 100 is configured as a separate device from the toilet seat device 2, it may transmit control information for the second detection unit 22 to the toilet seat device 2 wirelessly. In this case, the control device of the toilet seat device 2 may control the second detection unit 22 based on the control information received.

For example, the control device 100 may control the second detection unit 22 so that the measurement value from the gas sensor 40 falls within a predetermined range when the user is not using the toilet 7, and may perform reference value control to control the measurement value used as the reference value (baseline) to a predetermined value. The control device 100 may also perform reference value control to control the reference value to a predetermined value by changing the resistance value of the resistive element of the gas sensor 40.

The control device 100 may also control the suction device 10. For example, the control device 100 controls the start and stop of suction by the suction device 10. The control device 100 transmits control information to the suction device 10 via a wired connection. The control device 100 may also transmit control information to the suction device 10 wirelessly. For example, if the control device 100 is configured as a separate device from the toilet seat device 2, it may transmit control information for the suction device 10 to the toilet seat device 2 wirelessly. In this case, the control device of the toilet seat device 2 may control the suction device 10 based on the control information received.

The control device 100 may also control various other components of the biological information measurement system 1. The control device 100 controls the nozzle motor 61, etc. The control device 100 controls the nozzle motor 61, etc. based on signals transmitted from the operation device 30.

The control device 100 controls the nozzle motor 61 based on a control instruction signal related to local cleaning sent from the operating device 30. The control device 100 controls the nozzle motor 61 to move the cleaning nozzle 6 forward and backward. Note that the control device 100 may control various mechanisms other than the nozzle motor 61. For example, the control device 100 controls the opening and closing of a solenoid valve that functions as a valve that electromagnetically controls the flow of fluid. For example, the control device 100 controls the solenoid valve to switch on and off the supply of tap water from a water supply pipe, for example.

The control device 100 transmits control information to the nozzle motor 61, etc. via a wired connection. The control device 100 may also transmit control information to the nozzle motor 61, etc. wirelessly. For example, if the control device 100 is configured as a separate device from the toilet seat device 2, it may transmit control information for the nozzle motor 61, etc. to the toilet seat device 2 wirelessly. In this case, the control device of the toilet seat device 2 may control the nozzle motor 61, etc. based on the control information received.

The nozzle motor 61 is a drive source (motor) that drives the cleaning nozzle 6 to move forward and backward. The nozzle motor 61 controls the movement of the cleaning nozzle 6 forward and backward relative to the main body 3. The nozzle motor 61 controls the movement of the cleaning nozzle 6 forward and backward in response to instructions from the control device 100.

The control device 100 may also control the toilet lid 9 and toilet seat 5 as shown in FIG. 1. In this case, the control device 100 controls the toilet lid 9 and toilet seat 5 based on signals transmitted from the operating device 30. The control device 100 controls the toilet lid 9 based on control instruction signals transmitted from the operating device 30 regarding the opening and closing of the toilet lid. The control device 100 controls the toilet seat 5 based on control instruction signals transmitted from the operating device 30 regarding the opening and closing of the seat. The control device 100 transmits control information to the toilet lid 9 and toilet seat 5 via a wired connection. The control device 100 may also transmit control information to the toilet lid 9 and toilet seat 5 wirelessly.

The control device 100 determines whether a user is seated using seat detection means such as the human sensor 32, seat sensor 33, and illuminance sensor 34. For example, the control device 100 determines whether a user is seated based on detection by the seat sensor 33.

In the configuration shown in FIG. 5, the toilet seat device 2 includes the control device 100, etc., as an example. However, the control device 100, the human presence sensor 32, the seating sensor 33, the illuminance sensor 34, etc. may be configured as separate devices from the toilet seat device 2. For example, the control device 100 may be configured as a separate device from the toilet seat device 2. For example, the control device 100 may be a server device located at a distance from the toilet seat device 2. In this case, the control device 100 communicates with each device, such as the toilet seat device 2, the human presence sensor 32, the seating sensor 33, and the illuminance sensor 34, and receives various pieces of information from each device. In this case, the toilet seat device 2 may also have a configuration (such as a control circuit) for controlling various components of the toilet seat device 2, such as the nozzle motor 61. Note that the above is merely an example, and the biometric information measurement system 1 can employ any device configuration as long as it is capable of performing the desired processing.

<1-5. Functional configuration of the control device>
The functional configuration of the control device will be described below with reference to FIG. 6. FIG. 6 is a block diagram showing an example of the configuration of the control device according to the embodiment. As shown in FIG. 6, the control device 100 has a communication unit 110, a storage unit 120, and a control unit 130. Note that the configuration of the control device 100 is not limited to the configuration shown in FIG. 6, and other configurations may be used as long as the desired processing can be realized. For example, the control device 100 does not need to have the communication unit 110.

The communication unit 110 is realized, for example, by a communication circuit or the like. The communication unit 110 is connected to a predetermined network via a wired or wireless connection, and transmits and receives information to and from an external information processing device. For example, the communication unit 110 is connected to a predetermined network via a wired or wireless connection, and transmits and receives information to and from other devices such as the operating device 30. Note that the communication unit 110 may be configured as a separate device (communication device) from the control device 100, and may be included in the toilet seat device 2.

The storage unit 120 is realized, for example, by a semiconductor memory element such as RAM (Random Access Memory) or flash memory, or a storage device such as a hard disk or optical disk. For example, the storage unit 120 is a computer-readable recording medium that non-temporarily records data used by various information processing programs, etc.

The memory unit 120 according to the embodiment stores various information required for processing. The memory unit 120 stores various information acquired from other devices, such as various sensors. The memory unit 120 stores various information used in various information processing. For example, the memory unit 120 stores information related to reference value control, such as target values.

The memory unit 120 stores various information used in the estimation process related to stool, such as the properties of stool. For example, the memory unit 120 stores thresholds used in the estimation process related to stool. For example, the memory unit 120 stores various models (also called "estimation models") used to estimate the properties of stool. For example, the memory unit 120 stores various estimation models used to estimate the shape, color, amount, etc. of stool. Note that the above is merely an example, and the memory unit 120 stores various information related to stool detection.

The memory unit 120 stores various information used in gas-related estimation processing, such as the amount or concentration of gas. For example, the memory unit 120 stores thresholds used in gas-related estimation processing. For example, the memory unit 120 stores various functions (also referred to as "gas estimation functions") used to estimate (calculate) the amount or concentration of gas. For example, the memory unit 120 stores various gas estimation functions used to estimate the amount or concentration of gas of a specified component. For example, the memory unit 120 stores a function (also referred to as an "evaluation estimation function") that calculates (estimates) an evaluation of fecal gas from the amount or concentration of gas of a specified component. Note that the above is merely an example, and the memory unit 120 stores various information related to gas detection.

Returning to Figure 6, the explanation will continue. The control unit 130 is realized, for example, by an MPU (Micro Processing Unit) or CPU (Central Processing Unit) executing programs stored within the control device 100 (such as various information processing programs related to the present disclosure) using RAM or the like as a working area. The control unit 130 may also be realized, for example, by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or FPGA (Field Programmable Gate Array).

As shown in FIG. 6, the control unit 130 has an acquisition unit 131, a processing unit 132, and an output unit 133, and realizes or executes the information processing functions and actions described below. Note that the internal configuration of the control unit 130 is not limited to the configuration shown in FIG. 6, and other configurations may be used as long as they perform the information processing described below.

The acquisition unit 131 acquires various types of information. The acquisition unit 131 acquires various types of information from the storage unit 120. The acquisition unit 131 receives information from other devices. The acquisition unit 131 receives information detected by various sensors (detection information, etc.) from the various sensors.

The acquisition unit 131 acquires information (detection information, etc.) detected by the seating detection means from the seating detection means. The acquisition unit 131 receives information (detection information, etc.) detected by at least one of the human presence sensor 32, seating sensor 33, and illuminance sensor 34 from that sensor.

The acquisition unit 131 acquires the detection results from the first detection unit 21, which detects stool. The acquisition unit 131 acquires the detection results from the first detection unit 21, which detects information related to intestinal peristaltic movement. The acquisition unit 131 acquires the detection results from the second detection unit 22, which detects fecal gas. The acquisition unit 131 acquires the detection results from the second detection unit 22, which detects information related to the intestinal environment.

The acquisition unit 131 receives information based on detection by the first detection unit 21 from the first detection unit 21. The acquisition unit 131 receives information indicating the detection results related to feces detected by the first detection unit 21. The acquisition unit 131 also receives information based on detection by the second detection unit 22 from the second detection unit 22. The acquisition unit 131 receives information indicating the detection results related to fecal gas detected by the second detection unit 22.

The processing unit 132 performs various types of processing. The processing unit 132 performs various types of processing using information stored in the memory unit 120. The processing unit 132 performs estimation processing. The processing unit 132 performs estimation processing using various types of information stored in the memory unit 120.

The processing unit 132 executes an estimation process to estimate at least one of the provided information or score related to the user's health based on the detection results of the first detection unit 21 and the detection results of the second detection unit 22. The processing unit 132 executes control to output the results of the estimation process to the outside. The processing unit 132 executes control to output the results of the estimation process to the output unit 133 by instructing the output unit 133.

The processing unit 132 estimates first biological information based on the properties of the stool from the detection results of the first detection unit 21. The processing unit 132 estimates second biological information based on the amount or concentration of fecal gas from the detection results of the second detection unit 22. The processing unit 132 executes control to output the first biological information and the second biological information.

The processing unit 132 performs the estimation process using a larger number of samples of the detection results from the second detection unit 22 than the number of samples of the detection results from the first detection unit 21. The processing unit 132 estimates the first biological information using the detection results from the first detection unit 21, which are data obtained from a single toilet use. The processing unit 132 estimates the second biological information using the detection results from the second detection unit 22, which are data obtained from multiple toilet uses.

The processing unit 132 estimates a higher score the higher the first evaluation corresponding to each classification of stool properties based on the detection results of the first detection unit 21. The processing unit 132 estimates a higher score the higher the second evaluation based on the detection results of the second detection unit 22.

The processing unit 132 performs estimation processing using information detected by the first detection unit 21. The processing unit 132 performs estimation processing using an image captured by the first detection unit 21. The processing unit 132 estimates (determines) whether feces are contained in the image captured by the first detection unit 21. The processing unit 132 uses image recognition technology to estimate whether feces are contained in the image.

For example, the processing unit 132 receives an image as input and uses a model (feces estimation model) that outputs information (score) indicating whether the input image contains feces to estimate whether the image contains feces. In this case, the processing unit 132 compares the score output by the feces estimation model to which the image is input with a threshold (first threshold), and if the score is equal to or greater than the first threshold, estimates that the image contains feces. The processing unit 132 also compares the score output by the feces estimation model to which the image is input with the first threshold, and if the score is less than the first threshold, estimates that the image does not contain feces. Note that the above is merely an example, and the processing unit 132 may use various information as appropriate to estimate whether an image contains feces.

The processing unit 132 estimates (classifies) the stool properties from the detection results by the first detection unit 21. The processing unit 132 estimates the classification of the stool properties as first biological information. The processing unit 132 classifies the stool properties corresponding to an image containing stool (also referred to as a "stool image") captured by the first detection unit 21, based on that image. For example, the processing unit 132 uses the stool image to classify the shape (also simply referred to as "shape") of the stool corresponding to that stool image. For example, the processing unit 132 uses the stool image to classify the shape of the stool corresponding to that stool image into multiple types (7 levels) based on the Bristol scale. In this case, the processing unit 132 classifies the stool into categories based on the Bristol scale, with the banana-shaped stool (normal stool), which is the middle row of the 7 levels (i.e., the fourth level), corresponding to the best condition, and categories further away from that corresponding to worse conditions.

The processing unit 132 uses a stool image to classify the shape of the stool corresponding to the stool image into one of several shape-based levels. For example, the processing unit 132 uses a stool image to classify the shape of the stool corresponding to the stool image into one of the following: round, hard, cracked, banana-shaped, soft (semi-paste-like), muddy, and watery. For example, the processing unit 132 may classify (determine) the shape of the stool based on various information (features) such as the length of the stool image in the falling direction and the number of stool pieces (lumps).

The processing unit 132 may classify the shape of stool using AI (artificial intelligence) technology. For example, the processing unit 132 may classify the shape of stool using a learning model (shape estimation model) generated by machine learning. In this case, the shape estimation model is trained in advance using training data that indicates classification judgments. This training data includes multiple combinations of stool images and labels (correct answer information) that indicate the shape of the clumps (stool) contained in the stool images (either round, hard, cracked, banana-shaped, soft, muddy, or watery). For example, the shape estimation model is a model that receives a stool image as input and outputs information indicating the shape of the clumps (stool) contained in the input stool image. For example, the shape estimation model is trained to output label (stool shape) information corresponding to the input stool image when a stool image is input. The shape estimation model is trained using various so-called supervised learning techniques as appropriate.

In this case, the shape estimation model may be stored in the memory unit 120, and the processing unit 132 may classify the stool shape using the shape estimation model stored in the memory unit 120. The control device 100 may perform a learning process to generate various estimation models, or the control device 100 may acquire various estimation models from an external device such as the server device 400. The above is merely an example, and the processing unit 132 may classify the stool shape using various information as appropriate. The seven levels of round, hard, cracked, banana-shaped, soft, muddy, and watery are merely examples of shapes, and the processing unit 132 may classify shapes other than these, or may classify into six levels or less. While an example of classifying stool shapes into one of multiple levels has been shown here, this is not a limitation, and if multiple stool shapes are included in a single excretion act, multiple stool shapes may be classified.

Furthermore, the processing unit 132 may estimate various information other than the shape of the stool. For example, the processing unit 132 may estimate (classify) the amount of stool based on the image captured by the first detection unit 21. For example, the processing unit 132 may classify the amount of stool based on the proportion of stool in the image. For example, the processing unit 132 may classify the amount of stool using the score output by a stool estimation model. If the score output by the stool estimation model to which an image is input is equal to or greater than a first threshold and less than a second threshold, the processing unit 132 may classify the amount of stool as "very small." The second threshold is assumed to be a value greater than the first threshold. Furthermore, the processing unit 132 may classify the amount of stool as "small" if the score output by the stool estimation model to which an image is input is equal to or greater than a second threshold and less than a third threshold. The third threshold is assumed to be a value greater than the second threshold.

The processing unit 132 may also classify the amount of stool as "medium" if the score output by the stool estimation model to which an image has been input is equal to or greater than a third threshold and less than a fourth threshold. The fourth threshold is assumed to be a value greater than the third threshold. The processing unit 132 may also classify the amount of stool as "large" if the score output by the stool estimation model to which an image has been input is equal to or greater than a fourth threshold and less than a fifth threshold. The fifth threshold is assumed to be a value greater than the fourth threshold. The processing unit 132 may also classify the amount of stool as "very large" if the score output by the stool estimation model to which an image has been input is equal to or greater than a fifth threshold. Note that the above five-level classification is merely an example, and the processing unit 132 may classify the amount of stool using various information as appropriate. For example, the processing unit 132 may perform three-level classification using four thresholds.

Furthermore, for example, the processing unit 132 may use a stool image to estimate (classify) the color of the stool corresponding to that stool image. The processing unit 132 uses the stool image to classify whether the color of the stool corresponding to that stool image is one of multiple color-based levels. For example, the processing unit 132 uses the stool image to classify whether the color of the stool corresponding to that stool image is one of yellow, light ochre, ochre, brown, dark brown, and dark brown.

The processing unit 132 classifies the color of the stool based on the detection results from the first detection unit 21. The processing unit 132 appropriately uses various techniques for classifying stool colors to classify the color of the stool as yellow, light ochre, ochre, brown, dark brown, or dark brown. For example, the processing unit 132 classifies (determines) the color of the stool based on various information (features) such as the brightness and luminosity of the color image (RGB). For example, the processing unit 132 may classify the color of the stool using a learning model (color estimation model) generated by machine learning.

The processing unit 132 estimates an evaluation of peristaltic movement (also referred to as the "first evaluation") using the stool properties based on detection by the first detection unit 21. Here, we will explain as an example a case where the stool properties are classified into seven stages based on the Bristol scale.

The processing unit 132 estimates the first evaluation highest when the stool properties are banana-shaped (normal stool), which is the middle level (i.e., level 4) of the seven-level scale. Furthermore, the processing unit 132 estimates the first evaluation lower as the stool properties move away from the middle level of the seven-level scale. The processing unit 132 estimates the first evaluation low when the stool properties are hard (hard stool), which is the lowest level (i.e., level 1) of the seven-level scale. Furthermore, the processing unit 132 estimates the first evaluation low when the stool properties are watery (watery stool), which is the highest level (i.e., level 7) of the seven-level scale.

Note that the above is merely one example, and the processing unit 132 may estimate the first evaluation in any manner. For example, in the case of the Bristol scale described above, the center corresponds to the best condition and the extreme levels correspond to the worst, but depending on the classification mode, the lowest level (classification) may correspond to the worst condition, and higher levels (classifications) may correspond to better conditions, with the highest level (classification) corresponding to the worst condition. In this case, the processing unit 132 may estimate the first evaluation to be the lowest when the stool properties are in the lowest level (classification), and the first evaluation to be the highest when the stool properties are in the highest level (classification). In this way, the processing unit 132 estimates the first evaluation using a method that corresponds to the classification mode of the stool properties.

The processing unit 132 also performs estimation processing using information detected by the second detection unit 22. The processing unit 132 also performs estimation processing using information on the gas detected by the second detection unit 22. The processing unit 132 also performs calculation processing. The processing unit 132 also performs calculation processing using various types of information stored in the memory unit 120. The processing unit 132 also performs calculation processing using various types of information acquired by the acquisition unit 131.

The processing unit 132 calculates various pieces of information related to the gas. The processing unit 132 calculates values based on the measurement values measured by the second detection unit 22. The processing unit 132 calculates the resistance value of the sensor element based on the voltage value measured by the gas sensor 40. For example, the processing unit 132 calculates the resistance value of the sensor element from the measured voltage value using a function that indicates the relationship between the voltage value and the resistance value of the sensor element. The processing unit 132 calculates the resistance value of the sensor element using equation (1).

The processing unit 132 calculates the amount or concentration of gas based on the calculated resistance value of the sensor element. The processing unit 132 estimates (calculates) the amount or concentration of gas from the calculated resistance value using a function (gas estimation function) that indicates the relationship between the resistance value and the amount or concentration of gas. For example, the processing unit 132 may calculate the amount or concentration of gas associated with the intestinal environment from the amount of change from the baseline of the sensor data detected by the second detection unit 22 (e.g., the voltage value before measuring fecal gas). In this case, the processing unit 132 may convert the amount or concentration of gas into a unique score (e.g., an intestinal environment score) and generate information indicating changes over time.

The processing unit 132 estimates an evaluation of the intestinal environment (also referred to as the "second evaluation") using the amount or concentration of gas detected by the second detection unit 22. For example, the processing unit 132 estimates the second evaluation based on the amount or concentration of fecal gas as second biological information. For example, the processing unit 132 estimates the second biological information using an evaluation estimation function that takes the amount or concentration of gas detected by the second detection unit 22 as input and outputs an evaluation of the fecal gas (second evaluation).

When the processing unit 132 can detect a gas (also called a "health-related gas") whose amount or concentration indicates a high probability of a healthy intestinal environment, the processing unit 132 estimates the second evaluation using the amount or concentration of the health-related gas. For example, the processing unit 132 estimates a higher second evaluation the greater the amount or concentration of the health-related gas. The processing unit 132 estimates (calculates) the second evaluation using a gas estimation function that increases the value of the second evaluation the greater the amount or concentration of the health-related gas.

When the processing unit 132 can detect a gas (also called an "odorous gas") whose amount or concentration indicates a high likelihood of a poor intestinal environment, the processing unit 132 estimates the second evaluation using the amount or concentration of the odorous gas. For example, the processing unit 132 estimates a lower second evaluation the greater the amount or concentration of the odorous gas. The processing unit 132 estimates the second evaluation using a gas estimation function that reduces the value of the second evaluation the greater the amount or concentration of the odorous gas.

Note that the above is merely an example, and the processing unit 132 may estimate the second rating in any manner. For example, the processing unit 132 may estimate the second rating based on the ratio between the amount or concentration of health-related gases and the amount or concentration of odorous gases in the user's defecation gas. Based on the calculated ratio, the processing unit 132 estimates a higher second rating the more health-related gases there are relative to odorous gases in the user's defecation gas. Based on the calculated ratio, the control device 100 estimates a lower second rating the more odorous gases there are relative to health-related gases in the user's defecation gas. Note that the above is merely an example, and the control device 100 may make any estimation based on the calculated score.

The processing unit 132 controls the components that perform various detections. For example, the processing unit 132 controls the first detection unit 21. Also, for example, the processing unit 132 controls the second detection unit 22. The processing unit 132 controls the second detection unit 22 so that the measurement value from the gas sensor 40 falls within a predetermined range when the user is not using the toilet 7, and performs reference value control to control the measurement value used as the reference value to a predetermined value. The processing unit 132 performs reference value control to control the reference value to a predetermined value by changing the resistance value of the resistive element of the gas sensor 40. The processing unit 132 performs reference value control each time a fecal gas measurement is completed. The processing unit 132 performs reference value control by processing to feed back the measurement value from the gas sensor 40.

The output unit 133 executes output processing to output various types of information. The output unit 133 functions as a transmission unit that transmits various types of information. The output unit 133 executes output processing by transmitting information to an external information processing device. The output unit 133 transmits information to an external information processing device. For example, the output unit 133 transmits various types of information to the display device 300. For example, the output unit 133 transmits various types of information to an administrator device such as a personal computer or smartphone used by the administrator. The output unit 133 may also execute output processing by transmitting information to the operation device 30 (or display screen 31).

The output unit 133 transmits information indicating the processing results by the processing unit 132. The output unit 133 transmits various information to the display device 300 that is used for display by the display device 300. The output unit 133 outputs the results of the estimation process to the outside. The output unit 133 transmits the results of the estimation process to the outside via the communication unit 110. The output unit 133 controls the display device 300 to output the results of the estimation process by transmitting the results of the estimation process to the display device 300. For example, the output unit 133 transmits the results of the estimation process to the display device 300 and causes the display device 300 to display the results of the estimation process.

<1-6. Processing example>
From here, various processing examples will be described based on the configuration of the above-described biological information measurement system 1. Note that explanations of points similar to those described above will be omitted as appropriate.

<1-6-1. Processing overview>
First, an overall outline of the processing will be described with reference to Fig. 7. Fig. 7 is a diagram showing an example of processing executed by the biological information measuring system according to the embodiment.

Below, an example of the detection of stool by the first detection unit 21 and the detection of defecation gas by the second detection unit 22 will be described, followed by an overview of the estimation process based on that detection. Note that the detection of stool by the first detection unit 21 and the detection of defecation gas by the second detection unit 22 are merely examples, and any detection mode can be adopted for the detection by the first detection unit 21 and the second detection unit 22 as long as the desired information can be detected.

<1-6-1-1. Feces detection>
First, an example of feces detection by the first detection unit 21 will be described. Below, specific operations of a method for acquiring feces images (data) by the first detection unit 21 will be described with reference to first detection process MS1 in Fig. 7. The first detection process MS1 in Fig. 7 is a diagram showing an example of a method for acquiring data.

The elements shown in the first detection process MS1 in Figure 7 will now be described. Objects OB1 and OB2 schematically represent the falling image of stool (excrement) to be detected (measured). Specifically, object OB1, shown by a solid line, schematically represents the position of the falling stool at a certain point in time (first point in time), and object OB2, shown by a dotted line, schematically represents the position of the falling stool at a point in time later than the first point in time (second point in time). In other words, object OB1 and object OB2 in Figure 7 represent a single piece of stool falling at different times, and object OB2 corresponds to stool at a later time than object OB1. Hereinafter, when objects OB1 and OB2 are described without distinction, they will be referred to as object OB.

The first detection process MS1 in Figure 7 shows a case where the first detection unit 21 has three light-emitting elements 51a, 51b, and 51c. For example, the light-emitting elements 51a, 51b, and 51c are each LEDs (Light Emitting Diodes) that emit light of different wavelengths. Hereinafter, when the light-emitting elements 51a, 51b, and 51c are described without distinction, they will be referred to as light-emitting elements 51.

The first detection process MS1 in Figure 7 conceptually illustrates the process of irradiating a falling object OB with light from a light-emitting element 51 and acquiring (generating) a stool image (two-dimensional image) based on the light reception by the light-receiving unit 50. The dotted line extending from the light-emitting element 51 to the object OB schematically illustrates the light being irradiated from the light-emitting element 51 to the object OB, and the dotted line extending from the object OB to the light-receiving unit 50 schematically illustrates the light reflected from the object OB and received by the light-receiving unit 50. That is, the first detection process MS1 in Figure 7 schematically illustrates the case where, when detecting the object OB corresponding to object OB1, data (one-dimensional image) of the bottom end of the object OB (the leading end in the direction of fall) is detected, and the case where, when detecting the object OB corresponding to object OB2, data (one-dimensional image) of the top end of the object OB (the trailing end in the direction of fall) is detected.

In the first detection process MS1 in Figure 7, the first detection unit 21 generates stool information (two-dimensional image) by arranging in chronological order the data (one-dimensional images) acquired over time for each wavelength emitted by each of the light-emitting elements 51a, 51b, and 51c. Note that various processes are possible for generating color images using light-emitting elements and line sensors with different wavelengths, and a detailed explanation will be omitted, but a brief example of the process will be described below.

The first detection unit 21 generates a two-dimensional image corresponding to the first light-emitting element (light-emitting element 51a) by arranging in chronological order the light reception data (one-dimensional image) obtained by emitting light from the light-emitting element 51a, which is a first light-emitting element that emits light of a first wavelength. For example, the first detection unit 21 generates delivery information (first two-dimensional image) corresponding to the first wavelength by arranging in chronological order the light reception data (one-dimensional image) obtained by emitting light of a first wavelength, such as 590 nm.

The first detection unit 21 also generates a two-dimensional image corresponding to the second light-emitting element (light-emitting element 51b) by arranging in chronological order the light reception data (one-dimensional image) obtained by emitting light from the second light-emitting element, light-emitting element 51b, which emits light of the second wavelength. For example, the first detection unit 21 generates stool information (second two-dimensional image) corresponding to the second wavelength by arranging in chronological order the light reception data (one-dimensional image) obtained by emitting light of the second wavelength, such as 670 nm.

The first detection unit 21 also generates a two-dimensional image corresponding to the third light-emitting element (light-emitting element 51c) by arranging in chronological order the light reception data (one-dimensional image) obtained by emitting light from the third light-emitting element, light-emitting element 51c, which emits light of the third wavelength. For example, the first detection unit 21 generates stool information (third two-dimensional image) corresponding to the third wavelength by arranging in chronological order the light reception data (one-dimensional image) obtained by emitting light of the third wavelength, such as 870 nm.

In this way, the first detection unit 21 can obtain a color image by generating two-dimensional images for each of the three wavelengths corresponding to the first light-emitting element, the second light-emitting element, and the third light-emitting element. For example, the first detection unit 21 may generate a color image by combining the first two-dimensional image, the second two-dimensional image, and the third two-dimensional image described above. Furthermore, the light-receiving element of the light-receiving unit 50, such as a line sensor, may be a color light-receiving element, and light-emitting elements of multiple colors may emit light simultaneously, and the color of the reflected light may be detected by the light-receiving unit to generate a color image.

The first detection unit 21 may also be a camera that captures images and generates two-dimensional images. For example, the first detection unit 21 may have, as the light receiving unit 50, an area sensor (two-dimensional image sensor) in which CCD sensors or CMOS sensors are arranged in a planar (two-dimensional) pattern.

<1-6-1-2. Detection of fecal gas>
Next, an example of detection of fecal gas by the second detection unit 22 will be described. Specific operations of a method for acquiring gas information by the second detection unit 22 will be described below with reference to the second detection process MS2 in Fig. 7. The second detection process MS2 in Fig. 7 is a diagram showing an example of a method for acquiring data. Explanations of points similar to those described above will be omitted where appropriate.

First, an example of the gas sensor 40 in the biological information measurement system 1 will be described. The second detection unit 22 has a gas sensor 40 that detects gases indicative of the user's intestinal environment. For example, the gas sensor 40 may be a gas sensor (also referred to as an "odor gas sensor") that can detect gases (odor gases) resulting from intestinal putrefaction and indicating poor health. For example, odor gases are gases produced by putrefaction caused by harmful bacteria in the intestines. For example, odor gases may be fecal gases that contain sulfur components. Examples of odor gases include ammonia, trimethylamine, hydrogen sulfide, methyl mercaptan, indole, and skatole.

The second detection unit 22 may also have multiple gas sensors 40, including a gas sensor (also referred to as a "health gas sensor") that can detect gases (health gases) derived from intestinal fermentation and indicating a high level of health, in addition to odorous gases. For example, health gases are gases produced by fermentation by beneficial bacteria in the intestines. For example, health gases may be gases derived from intestinal fermentation that increase in amount as the level of intestinal health increases. Examples of health gases include hydrogen, carbon dioxide, acetic acid, methane, ethanol, and water.

The second detection unit 22 may have multiple gas sensors 40. For example, the second detection unit 22 may be a hydrogen gas sensor and may include multiple gas sensors 40 such as an odorous gas sensor and a methane gas sensor.

For example, the biological information measurement system may detect (estimate) the amount or concentration of an odorous gas by removing the influence of the amount or concentration of a gas (health-related gas) detected by the second detection unit 22 from the amount or concentration of an odorous gas detected by the second detection unit 22.

Next, an example configuration of a gas sensor will be described using Figure 8. Figure 8 is a diagram showing an example configuration of a gas sensor. Specifically, Figure 8 is a diagram showing an example of the circuit configuration CR of a semiconductor gas sensor 40.

The gas sensor 40 comprises a sensor element and a measurement resistor element. In FIG. 8, the gas sensor 40 has a circuit configuration CR in which a sensor element (corresponding to the sensor resistor RS in FIG. 8) and a measurement resistor element (corresponding to the resistor element RL in FIG. 8) are connected in series.

In the semiconductor gas sensor 40, a value related to the gas amount is calculated using the following equation (1). Equation (1) corresponds to the circuit configuration CR shown in Figure 8 and is the same as the function FC1 in Figure 8.

RS = ((Vc-Vout)/Vout)×RL... (1)

In equation (1), "RS" represents the resistance value of the sensor element. For example, "RS" in equation (1) represents the resistance value of the sensor resistor RS, which is an example of a value calculated based on measurements by the gas sensor 40. In this way, equation (1) is a formula for calculating the resistance value.

In equation (1), "RL" represents the resistance value of the resistive element RL. "Vc" in equation (1) represents the voltage value of the circuit voltage Vc. "Vout" in equation (1) represents the voltage value of the output voltage Vout at the resistive element. For example, "Vout" in equation (1) represents the voltage value of the resistive element RL, which is an example of a measured value measured by the gas sensor 40.

The resistance value of the sensor resistor RS in formula (1) is an index related to the amount or concentration of fecal gas. The biological information measurement system 1 calculates an index (resistance value) related to the amount or concentration of fecal gas from the measured value (voltage value), and calculates the amount of gas from the calculated resistance value. While a detailed explanation of the principles of semiconductor gas sensors will be omitted, for example, "RH" shown only in the circuit configuration CR in Figure 8 corresponds to a heater (resistance) for heating the sensor element, and " _VH " corresponds to the heater voltage. The gas sensor in the present invention is not limited to a semiconductor sensor, and any sensor that satisfies the above formula (1) can be used instead.

The above is merely an example, and the second detection unit 22 may have any type of gas sensor, not limited to the above. For example, the second detection unit 22 may have a gas sensor such as an infrared _CO2 sensor (carbon dioxide concentration measuring device). The second detection unit 22 may also have multiple types or multiple gas sensors of any type. For example, the second detection unit 22 may have an electrochemical gas sensor in addition to an infrared _CO2 sensor.

<1-6-1-3. Estimation process>
Hereinafter, an example of estimation processing based on the detection of stool by the first detection unit 21 and the detection of defecation gas by the second detection unit 22 will be described. The control device 100 executes the estimation processing as shown below. Note that explanations of points similar to those described above will be omitted as appropriate.

The control device 100 estimates the classification of the stool properties as first biological information based on the detection of stool by the first detection unit 21. In Figure 7, as shown in the first biological information DT1 based on the stool detection information, the control device 100 estimates that the detected stool is banana-shaped, in the middle section of the seven-level Bristol scale. For example, the first biological information DT1 is information (first information) related to peristaltic movement.

The control device 100 then uses the estimated stool properties to estimate a first evaluation of peristaltic movement. An example of this process will be described later, including with reference to Figure 10.

The control device 100 estimates the amount or concentration of gas used to estimate the second evaluation based on the detection of fecal gas by the second detection unit 22. In Figure 7, the control device 100 estimates the amount or concentration of gas X (e.g., an odorous gas) used to estimate the second evaluation from the calculated resistance value using a function (gas estimation function) that indicates the relationship between the resistance value and the amount or concentration of gas X.

The control device 100 then estimates the second evaluation as second biological information using an evaluation estimation function that inputs the estimated amount or concentration of gas X and outputs a second evaluation. In Figure 7, the control device 100 estimates the value indicated by ● in the time series data DT2 based on the fecal gas detection information as the second evaluation (also referred to as the "intestinal environment score") based on the estimated amount or concentration of gas X. For example, the time series data DT2 is time series data from one month ago (1M ago) to the day of processing, and is information regarding the intestinal environment (second evaluation). Note that the second evaluation may also be calculated from multiple intestinal environment scores, as will be discussed below.

The control device 100 estimates at least one of the provided information or score related to the user's health based on the first evaluation and the second evaluation. Note that while Figure 7 illustrates both intestinal score information INF1 related to the intestinal score or intestinal rank, which are examples of scores related to the user's health, and recommendation information INF2, which are examples of provided information, the control device 100 may estimate either one. For example, in Figure 8, the control device 100 estimates that the intestinal score or intestinal rank is high, as shown in intestinal score information INF1, because both the first evaluation and the second evaluation are good. Note that for the sake of explanation, Figure 8 shows a case in which both a intestinal score of "90 points" and a intestinal rank rated "A" are estimated as scores, but the control device 100 may estimate only one of 90 points or an A rating, depending on the score type. Note that when the intestinal score and intestinal rank are not distinguished, they are collectively referred to as the intestinal score.

Furthermore, if the second evaluation, out of the first evaluation and the second evaluation, is getting worse, the control device 100 estimates, as the provided information, information indicating a deterioration in the intestinal environment, as shown in recommendation information INF2. Furthermore, the control device 100 estimates, as the provided information, information indicating recommended actions to take to address the deterioration of the intestinal environment.

In this way, the biological information measurement system 1 can estimate the health condition of the user's intestines based on information on both peristalsis and the intestinal environment, thereby appropriately estimating the health condition of the user. In other words, the biological information measurement system 1 can estimate the health condition of the user's intestines based on information on both the movement of the intestines themselves and the balance of intestinal bacteria living in the intestines.

In the above example, the biological information measurement system 1 estimates the properties of the stool based on detection by the line sensor, and estimates the intestinal environment based on detection by the gas sensor. For example, by sensing the shape, amount, color, and bowel gas (farts, etc.) of the stool, the biological information measurement system 1 visualizes the state of the intestines from peristalsis and the intestinal environment, and by understanding the state of the intestines, can inform the user of the state of the intestines, which is linked to physical and mental health. In this way, the biological information measurement system 1 can estimate and inform the user of daily intestinal conditions and changes from stool and bowel gas, and provide awareness of how to improve lifestyle behaviors.

Furthermore, in the above example, the biological information measurement system 1 can estimate the state and changes of the user's entire intestines based on the user's daily excretory behavior, and provide the user with information based on the estimation results. For example, with regard to peristalsis, the biological information measurement system 1 can display information on the estimated stool properties (color, shape, amount). The biological information measurement system 1 displays first biological information indicating the stool properties on the user's display device 300. In FIG. 7, the biological information measurement system 1 displays the first biological information DT1 on the user's display device 300. For example, the biological information measurement system 1 displays information indicating the estimated stool properties, such as that shown in the first biological information DT1, on the user's display device 300.

Regarding the intestinal environment, the biological information measurement system 1 can acquire the composition of fecal gas using a gas sensor and display changes over time. For example, the biological information measurement system 1 displays second biological information, such as a second evaluation, on the user's display device 300. In FIG. 7, the biological information measurement system 1 displays time-series data DT2 on the user's display device 300. For example, the biological information measurement system 1 displays information on the estimated intestinal environment score, as shown in the time-series data DT2, on the user's display device 300.

Also, in FIG. 7, the biological information measurement system 1 displays a score such as intestinal score information INF1 or provided information such as recommended information INF2 on the user's display device 300. This allows the biological information measurement system 1 to display a combination of peristalsis and the intestinal environment. In this way, the biological information measurement system 1 estimates and displays information about the user's health from information on both stool properties and bowel gas, thereby allowing the biological information measurement system 1 to appropriately estimate and display information about the user's health.

<1-6-2. Estimated example>
The provided information or score related to the user's health shown in Figure 7 is merely an example, and the biological information measurement system 1 may estimate the provided information or score using various information as appropriate. In this regard, several examples will be described below. Note that explanations of points similar to those described in Figure 7 etc. will be omitted as appropriate.

<1-6-2-1. Evaluation and estimation example>
First, an example of evaluation estimation by the biometric information measurement system 1 will be described using FIGS. 9 to 11 . For example, the biometric information measurement system 1 may perform an estimation process by using a larger number of samples for estimating the second evaluation than for estimating the first evaluation. For example, the biometric information measurement system 1 may use data obtained from multiple toilet visits to estimate the second evaluation. For example, the data used to estimate the first evaluation may be data obtained from a single toilet visit, and the data used to estimate the second evaluation may be data obtained from multiple toilet visits. For example, the number of toilet visits referred to here may be the number of times the user has used the toilet room R, with one visit counting from when the user entered the toilet room R to when they left. In this case, if multiple pieces of information are obtained from one toilet visit, the average or representative value may be used as the information for that single toilet visit. For example, if the amount or concentration of gas is detected twice during one toilet visit, the biometric information measurement system 1 may use the average of the two detected gas amounts or concentrations as the amount or concentration of gas for that single toilet visit. Any information can be used as the number of times the toilet is used, and it may be, for example, the number of times the user has had a bowel movement.

For example, as shown in FIG. 9, the biological information measurement system 1 estimates the second evaluation based on multiple data. FIG. 9 is a diagram showing an example of a second evaluation based on multiple data. Points PT indicated by white circles in the time series data DT21 in FIG. 9 indicate the intestinal environment score corresponding to each toilet use, and the calculated value CV indicated by black circles indicates the second evaluation calculated using information from multiple points PT. In FIG. 9, the biological information measurement system 1 estimates the calculated value CV, which is information calculated using multiple data such as a moving average, as the second evaluation, as shown in the time series data DT21. The curve in the time series data DT21 in FIG. 9 shows the time series change in the second evaluation calculated using multiple data such as a moving average.

In this way, the biological information measurement system 1 estimates the second evaluation of the intestinal environment based on multiple detection results, making it possible to appropriately estimate the second evaluation of the intestinal environment.

Next, the estimation of the first evaluation will be described using FIG. 10. FIG. 10 is a diagram showing an example of the estimation of the first evaluation according to the embodiment. As shown in FIG. 10, the bioinformation measurement system 1 estimates that the middle (median) section of a seven-point scale for stool properties is the best, and estimates the first evaluation so that the further away from the center the section, the lower the evaluation. In this case, the bioinformation measurement system 1 estimates that the closer the estimation result based on the stool properties is to the median, the better the first evaluation. The bioinformation measurement system 1 estimates (determines) that the middle section is the best stool properties. For example, if the stool properties are banana, which is the middle section of a seven-point scale, the control device 100 estimates the first evaluation to be the highest. For example, if the first evaluation is a rating of 0 to 100 points, the control device 100 may estimate the first evaluation to be 100 points when the stool properties are banana. Furthermore, if the first evaluation is based on seven ranks (scales) from S to A to F, with S being the best evaluation and the evaluations getting worse from A to F, the control device 100 may infer that the first evaluation is S if the stool has banana-like properties. As mentioned above, the classification and evaluation based on the Bristol scale are merely an example, and any classification such as "hard," "ideal," or "soft" can be used, and any resolution (number of classifications) and notation can be used. Furthermore, as mentioned above, it is not limited to the case where the center corresponds to the best state and the extreme stages correspond to the worst state. As long as a corresponding evaluation is associated with each classification, any association can be used, and the highest evaluation does not have to be associated with the median.

Next, the estimation of the second evaluation will be described using Figure 11. Figure 11 is a diagram showing an example of the estimation of the second evaluation according to the embodiment. As shown in Figure 11, the biological information measurement system 1 estimates a higher second evaluation the larger the value estimated based on fecal gas, such as the intestinal environment score. In this case, the biological information measurement system 1 estimates that the larger the value indicated by the estimation result based on fecal gas, the better the second evaluation. In this way, the biological information measurement system 1 estimates (determines) that the higher the score of information based on fecal gas (odor information), the better.

<1-6-2-2. Example of information output>
The biological information measurement system 1 outputs information according to the result of the estimation process. For example, if the information (e.g., evaluation) on the properties of the user's excrement (stool) is poor, the biological information measurement system 1 may provide the user with advice on stress and sleep. For example, the biological information measurement system 1 may generate information to be provided including content such as "Your peristalsis is getting worse. Please get enough sleep," and provide the generated information to the user.

Furthermore, if the odor information of the user's bowel movement gas is bad, the biological information measurement system 1 may provide the user with dietary advice. For example, the biological information measurement system 1 may generate information to be provided that includes content such as "Your intestinal environment is deteriorating. Eat yogurt," and provide the generated information to the user.

For example, when the biological information measurement system 1 acquires information about a user, such as the time series data DT12 of stool properties and the time series data DT22 of the intestinal environment score in FIG. 12, it generates information to be provided INF22 based on the time series data DT12 and the time series data DT22. The biological information measurement system 1 then displays the generated information to be provided INF22 on the display device 300 of the target user. FIG. 12 is a diagram showing an example of estimation of information to be provided according to an embodiment. For example, the time series data DT12 and the time series data DT22 are time series data from one month ago (1M ago) to the day of processing.

In Figure 12, as shown in time series data DT12 and time series data DT22, the intestinal environment score is decreasing, so the biological information measurement system 1 generates provided information INF22 containing content such as "Your intestinal environment is deteriorating. Take healthy actions," and provides the generated provided information INF22 to the user. In this way, the biological information measurement system 1 compares two pieces of information on changes over time: information on changes over time in the properties of excrement, as shown in time series data DT12, and information on changes over time in odor, as shown in time series data DT22, and generates provided information that prioritizes advice related to the information that is showing a greater deterioration trend, and displays the generated provided information.

<1-6-2-3. Examples of provided information and score estimation>
Next, an example of estimation of provided information or a score by the biological information measurement system 1 will be described with reference to Figs. 13 to 15. Fig. 13 is a diagram showing an example of information used to estimate a score according to the embodiment. Fig. 14 is a diagram showing an example of information used to estimate provided information according to the embodiment. Fig. 15 is a diagram showing an example of information used to estimate provided information according to the embodiment.

The estimation table MT1 shown in Figure 13 is a list of estimated intestinal ranks based on a combination of the classification shown in the "Feces Properties" section and the intestinal environment ranks A to D based on the intestinal environment score shown in the "Odor" section. The "Feces Properties" section corresponds to an estimation based on the detection results (feces detection) by the first detection unit 21. The "Odor" section corresponds to an estimation based on the detection results (defecation gas detection) by the second detection unit 22.

In Figure 13, the intestinal rank is divided into seven ranks (stages) from S to A to F, with S being the best intestinal condition, A being the next best, and F being the worst intestinal condition. Note that the health score is not limited to the intestinal rank, and any information (for example, a numerical value (score) such as 0 to 100 points) can be used. For example, the biological information measurement system 1 may output the intestinal score by adding up information on stool properties (evaluation, etc.) and odor information.

In FIG. 13, the "Odor" item includes four levels of intestinal environment rank, A to D. For example, the intestinal environment rank indicates a four-level evaluation in which A is the best and D is the worst. For example, the biological information measurement system 1 may estimate four levels of intestinal environment rank by converting the estimated intestinal environment score. In this case, for example, the biological information measurement system 1 may estimate the intestinal environment rank as A if the intestinal environment score is 75 points or higher.

In addition, the biological information measurement system 1 estimates the intestinal environment rank as B if the intestinal environment score is 50 or more and less than 75 points, as C if the intestinal environment score is 25 or more and less than 50 points, and as D if the intestinal environment score is less than 25 points. Note that the intestinal environment ranks shown in Figure 13 are merely examples, and any information (e.g., intestinal environment score, second evaluation, etc.) can be used for the "Odor" item.

In Figure 13, the "Feces Characteristics" item includes four taxonomic groups: the first taxonomic group of "banana," the second taxonomic group of "cracked" and "soft," the third taxonomic group of "hard" and "mud," and the fourth taxonomic group of "round" and "watery." Note that the taxonomic groups shown in Figure 13 are merely examples, and any combination of taxonomic groups can be used. Furthermore, any information (e.g., first evaluation) can be used for the "Feces Characteristics" item.

In FIG. 13, the biological information measurement system 1 estimates the user's intestinal rank as a score using the user's intestinal environment rank, stool property classification, and estimation table MT1. For example, if the user's intestinal environment rank is A and the stool property is banana, the biological information measurement system 1 estimates the user's intestinal rank to be S based on the corresponding elements in estimation table MT1.

The estimation table MT2 shown in Figure 14 is a list of provided information based on combinations of two categories (good or bad) shown in the "fecal properties" category and two categories (good or bad) shown in the "odor" category. Figure 14 shows four pieces of provided information corresponding to the number of combinations of the two categories of "fecal properties" and the two categories of "odor." Note that the provided information shown in Figure 14 is merely an example, and each piece of provided information may include any content corresponding to the state of stool properties or the state of odor.

In Figure 14, the "Odor" category has two categories: "Good" and "Bad." Note that the "Odor" categories shown in Figure 14 are merely examples, and any combination of categories can be used.

For example, if the second evaluation is equal to or greater than a predetermined value, the biological information measuring system 1 classifies the odor as "good" as shown in FIG. 14, and if the second evaluation is less than the predetermined value, the biological information measuring system 1 classifies the odor as "bad" as shown in FIG. 14. Note that the classification process described above is merely an example, and the biological information measuring system 1 may use various information to classify the odor as either "good" or "bad" as shown in FIG. 14. For example, if the intestinal environment score is equal to or greater than a predetermined value, the biological information measuring system 1 may classify the odor as "good" as shown in FIG. 14, and if the intestinal environment score is less than the predetermined value, the biological information measuring system 1 may classify the odor as "bad" as shown in FIG. 14.

In Figure 14, the "Fecal Properties" category has two categories: "Good" and "Bad." Note that the "Fecal Properties" categories shown in Figure 14 are merely examples, and any combination of categories can be used.

For example, if the first evaluation is equal to or greater than a predetermined value, the biological information measurement system 1 classifies it as "good" as shown in FIG. 14, and if the first evaluation is less than the predetermined value, it classifies it as "bad" as shown in FIG. 14. Note that the classification process described above is merely an example, and the biological information measurement system 1 may use various information to classify the stool properties as either "good" or "bad" as shown in FIG. 14. For example, if the stool properties are "banana," the biological information measurement system 1 may classify it as "good" as shown in FIG. 14, and if the stool properties are other than "banana," it may classify it as "bad" as shown in FIG. 14.

In FIG. 14, the biological information measurement system 1 estimates the information to be provided for a user using the user's odor classification, stool property classification, and estimation table MT2. For example, if the "Odor" item for a user is "bad" and the "Stool Property" item is "bad," the biological information measurement system 1 estimates, based on the corresponding elements in estimation table MT2, that the information to be provided for that user would be "Your intestinal health tends to be very bad. Why don't you start by reviewing your diet?"

The estimation table MT3 shown in Figure 15 is a list of provided information based on combinations of the three categories shown in the "feces properties" section and the three categories shown in the "odor" section. Figure 15 shows nine pieces of provided information corresponding to the number of combinations of the three categories of "feces properties" and the three categories of "odor." Note that the provided information shown in Figure 15 is merely an example, and each piece of provided information may include any content corresponding to the state of the stool properties or the state of the odor.

In Figure 15, the "Odor" category has three categories: "Good," "Average," and "Bad." Note that the "Odor" categories shown in Figure 15 are merely examples, and any combination of categories can be used.

For example, if the second evaluation is equal to or greater than the first threshold, the biological information measurement system 1 classifies it as "good" as shown in FIG. 15; if the second evaluation is less than the first threshold and equal to or greater than the second threshold, the biological information measurement system 1 classifies it as "average" as shown in FIG. 15; and if the second evaluation is less than the second threshold, the biological information measurement system 1 classifies it as "bad" as shown in FIG. 15. Any value can be used as the first threshold, and any value smaller than the first threshold can be used as the second threshold. Note that the biological information measurement system 1 may use the intestinal environment score to classify the "odor" category into one of three categories: "good," "average," or "bad."

In Figure 15, the "Feces Properties" category includes three taxonomic groups: the first taxonomic group of "muddy" and "watery," the second taxonomic group of "cracked," "banana," and "soft," and the third taxonomic group of "hard" and "hard." Note that the taxonomic groups shown in Figure 15 are merely examples, and any combination of taxonomic groups can be used.

In FIG. 15, the biometric information measurement system 1 estimates the information to be provided to a user using the user's odor classification, stool property classification, and estimation table MT3. For example, if the "Odor" category for a user is "Normal" and the "Stool Properties" category is the third classification group of "Roll" and "Hard," the biometric information measurement system 1 estimates, based on the corresponding elements in estimation table MT3, that information such as "Start exercising twice a week" would be appropriate to provide to the user.

<1-6-3. Examples of information provision>
Based on the above-described processing, an example of information provided to a user by the biological information measurement system 1 will now be described. For example, the biological information measurement system 1 generates the various pieces of information shown below and displays the generated information on the display device 300 used by the corresponding user. For example, the display device 300 used by the user has installed thereon a health management application (also called a "gut activity app") for displaying information related to the user's health, and the intestinal activity app displays various pieces of information related to the user's health.

Note that, as long as the display device 300 is capable of displaying information relating to the user's health, it may also display information relating to the user's health using an application other than the intestinal health app. The following description will be given as an example in which the user of the display device 300 displaying information is user U.

First, Figure 16 shows an example of information about the basic functions of the intestinal activity app that is provided by the biological information measurement system 1 and displayed by the display device 300. Figure 16 is a diagram showing an example of information provided by the biological information measurement system.

Content CT1 in Figure 16 corresponds to, for example, the home screen of a gut health app displayed on the display device 300. Content CT1 includes a display area AR1 that displays various information. In Figure 16, intestinal condition information IM1 including the intestinal rank at the time of display, a schematic diagram of a person, and an illustration of the intestines corresponding to the intestinal rank at the time of display is displayed in the display area AR1. Figure 16 shows the case where user U's intestinal rank at the time of display is A.

Content CT1 includes button IC1 labeled "Recommended information for you." Content CT1 also includes button IC2 labeled "What is intestinal rank?" Content CT1 includes button IC3 labeled "Intestinal movement." Content CT1 includes button IC4 labeled "Intestinal environment." Content CT1 includes button IC5 labeled "Intestinal activity diary." Content CT1 includes button IC6 labeled with information about user U's family. Examples of information displayed when buttons IC1 to IC6 are selected (specified) will be described later.

For example, when button IC3 in content CT1 displayed on display device 300 is selected, display device 300 displays information such as content CT2 shown in Figure 17. Figure 17 is a diagram showing an example of information provided by the biometric information measurement system.

Content CT2 in Figure 17 corresponds to, for example, a screen related to intestinal movement displayed by display device 300. Content CT2 includes feature information FT1 to FT3 that indicates information about user U's stool at the time of display. Note that Figure 17 shows a case where feature information FT1 to FT3 is text information, but feature information FT1 to FT3 may be displayed in any manner, such as an icon, as long as it can indicate the corresponding information.

For example, characteristic information FT1 indicates the amount of stool of user U at the time of display, and in Figure 17 indicates that the amount of stool is large. For example, characteristic information FT2 indicates the color of user U's stool at the time of display, and in Figure 17 indicates that the color of the stool is brown. For example, characteristic information FT3 indicates the nature of user U's stool at the time of display, and in Figure 17 indicates that the nature of the stool is normal (banana, etc.). Figure 17 shows a case where the nature of the stool is displayed as one of three: soft, normal, or hard stool, but the nature of the stool may also be displayed as the Bristol scale content, such as banana or hard.

Content CT2 includes a button IC11 labeled "Calendar display." For example, when button IC11 in content CT2 displayed on display device 300 is selected, display device 300 displays a calendar showing the measurement results of intestinal movement (e.g., stool characteristics, etc.).

Content CT2 includes a button IC12 labeled "Today's Introduction: Peristaltic Movement Version." For example, when button IC12 in content CT2 displayed on display device 300 is selected, display device 300 displays today's Introduction regarding peristaltic movement.

Content CT2 includes a button IC13 labeled "Related Column." For example, when button IC13 in content CT2 displayed on display device 300 is selected, display device 300 displays a related column about intestinal movement (e.g., stool characteristics, etc.).

Content CT2 includes a button IC14 labeled "Score." For example, when button IC14 in content CT2 displayed on display device 300 is selected, display device 300 displays information related to the score related to bowel movement (e.g., first evaluation, etc.).

For example, when button IC4 in content CT1 displayed on display device 300 is selected, display device 300 displays information such as content CT3 shown in Figure 18. Figure 18 is a diagram showing an example of information provided by the biometric information measurement system.

Content CT3 in Figure 18 corresponds to, for example, a screen related to the intestinal environment displayed by the display device 300. Content CT3 includes time-series data showing the changes in the intestinal environment index indicating the intestinal environment of user U up to the time of display, and information provided based on those changes. Note that in Figure 18, the intestinal environment index may be any index such as an intestinal environment score or an intestinal environment rank.

Content CT3 includes a button IC21 labeled "Today's Quick Commentary: Intestinal Environment Version." For example, when button IC21 in content CT3 displayed on display device 300 is selected, display device 300 displays today's quick commentary on the intestinal environment.

Content CT3 includes a button IC22 labeled "Related Column." For example, when button IC22 in content CT3 displayed on display device 300 is selected, display device 300 displays a related column about the intestinal environment.

Content CT3 includes a button IC23 labeled "Explanation of intestinal environment index." For example, when button IC23 in content CT3 displayed on the display device 300 is selected, the display device 300 displays an explanation of the intestinal environment index displayed in content CT3.

Furthermore, the information displayed in display area AR1 is not limited to the information shown in FIG. 16, and may be any information. In this regard, examples will be described using FIG. 19 and FIG. 20. FIG. 19 and FIG. 20 show examples of information according to the estimation results.

As shown in FIG. 19, the display device 300 may display in the display area AR1 provided information suggesting maintaining the current state, such as "You're in good condition!", and intestinal condition information IM2 including a schematic diagram of a person and an illustration of the intestines corresponding to the intestinal rank at the time of display. In this case, the display device 300 displays intestinal condition information IM2 in place of intestinal condition information IM1 in the display area AR1 in the content CT1 shown in FIG. 16. Furthermore, as shown in FIG. 20, the display device 300 may display in the display area AR1 provided information suggesting maintaining the current state, such as "You're getting better!", and intestinal condition information IM3 including an illustration of the intestines showing changes in the intestinal condition. In this case, the display device 300 displays intestinal condition information IM3 in place of intestinal condition information IM1 in the display area AR1 in the content CT1 shown in FIG. 16.

In this way, the display device 300 displays any information in the display area AR1. For example, the display device 300 displays information in the display area AR1 indicating the overall condition of the intestines, such as a score or ranking, a good or bad judgment, or changes from the past. In this way, the display device 300 may display a score or ranking as an indicator of the intestinal condition. In addition to the above information, the display device 300 may also display a graph of the above-mentioned trend of change over time.

For example, when button IC5 in content CT1 displayed on display device 300 is selected, display device 300 displays information such as content CT4 shown in Figure 21. Figure 21 shows an example of information related to the user's intestinal health.

Content CT4 in FIG. 21 corresponds to, for example, a screen related to intestinal health displayed by the display device 300. Content CT4 includes calendar information of an intestinal health diary showing the intestinal health of user U up to the time of display.

Content CT4 includes a button IC31 labeled "Intestinal Health Related Column." For example, when button IC31 in content CT4 displayed on display device 300 is selected, display device 300 displays the intestinal health related column.

Content CT4 includes a button IC32 labeled "Everyone's Intestinal Health." For example, when button IC32 in content CT4 displayed on display device 300 is selected, display device 300 displays information about the intestinal health of users other than user U; examples of this will be provided later.

Content CT4 includes a button IC33 labeled "Look back on past intestinal health." For example, when button IC33 in content CT4 displayed on display device 300 is selected, display device 300 displays historical information about user U's intestinal health, etc.

For example, when button IC1 in content CT1 displayed on display device 300 is selected, display device 300 displays information such as content CT5 shown in FIG. 22. FIG. 22 is a diagram showing an example of recommended information for a user. FIG. 22 shows an example of the display when user U's intestinal condition is poor (for example, intestinal rank D, etc.).

Content CT5 in FIG. 22 corresponds to a screen related to provided information such as recommended information displayed by the display device 300, for example. Content CT5 includes provided information reports etc. corresponding to the intestinal condition of the user U up to the time of display. Content CT5 includes provided information INF5 including suggestions to encourage improvement of eating habits, such as "You're feeling worse than before" or "Your intestinal environment indicators tend to be getting worse. Is your eating habits out of whack?"

Content CT5 includes a button IC41 labeled "Recommended Information." For example, when button IC41 in content CT5 displayed on display device 300 is selected, display device 300 displays various information such as content CT6 shown in Figure 23. Figure 23 is a diagram showing an example of recommended information for the user.

Content CT6 in FIG. 23 corresponds to a screen related to provided information such as recommended information displayed by the display device 300, for example. Content CT6 includes provided information INF6 including suggestions for foods to consume, such as "It is said that the intestinal environment is affected by diet. Water-soluble dietary fiber is said to be good!" Content CT6 also includes information on related websites, videos, recommended products, etc. that may lead to improvements in diet.

For example, when button IC32 in content CT4 displayed on display device 300 is selected, display device 300 displays information such as content CT7 shown in Figure 24. Figure 24 shows an example of information about other users provided to the user.

Content CT7 in FIG. 24 corresponds to, for example, a screen related to information about other users displayed by the display device 300. Content CT7 includes information related to intestinal health of other users who have similar attributes to user U, such as age, gender, physique, and lifestyle. In FIG. 24, content CT7 includes information related to intestinal health recorded in an intestinal health app by other users in their 30s who have similar attributes to user U, who is in his 30s, and information related to intestinal health posted on SNS (Social Networking Service).

Note that other users similar to user U are not limited to users with similar attributes, but may also be users with similar evaluations such as intestinal scores. For example, if user U's intestinal score is B, other users similar to user U may also be users with a intestinal score of B. In this way, the display device 300 displays intestinal health methods of people with similar attributes or intestinal scores. For example, the bioinformation measurement system 1 may acquire records in intestinal health apps or SNS information of other people that are linked to attributes or intestinal scores associated with information that identifies the user (such as an ID), and use this information as information related to the intestinal health of other users similar to user U.

Content CT8 in Figure 25 corresponds to the screen that appears when, for example, a specific date is selected from the intestinal activity diary calendar included in content CT4. Figure 25 is a diagram showing an example of the display format of information provided to the user. Content CT8 includes calendar information from the intestinal activity diary that shows user U's intestinal activity up to the time of display, as well as the intestinal score and icon corresponding to the selected date.

For example, the display device 300 may prompt the user U to manually input their sensory information or select an icon. In FIG. 25, the display device 300 may prompt the user U to select an overall rating of A to E based on their own sensory (subjective) experience. The display device 300 may also prompt the user U to select from subjective icons based on their own sensory (subjective) experience. The biometric information measurement system 1 may then use the sensory information acquired through the user's selection to reevaluate or correct the user U's score, or set a target score for the user U.

The display device 300 may also prompt the user U to manually input or select an icon for each of multiple items. In FIG. 25, the display device 300 may display icons for each item, such as diet, lifestyle habits, and exercise, and prompt the user U to select from these icons. The display device 300 may also acquire information by linking with other applications on a smartphone or a smartwatch. This allows the bioinformation measurement system 1 to collect information to determine whether to exclude outliers (such as outliers) in the intestinal activity information and measurement values. The bioinformation measurement system 1 may then manage the information acquired through the user's selection by linking it to the estimation results as information indicating intestinal activity events or conditions. The bioinformation measurement system 1 may also perform outlier exclusion processing based on the information acquired from the user.

The display device 300 may also provide information according to changes in the user's intestinal condition. In FIG. 26, the display device 300 displays content CT9 including provided information according to changes in user U's score (intestinal score), diet, and exercise, and a button IC91 encouraging the purchase of a product corresponding to the provided information. FIG. 26 is a diagram showing an example of recommended information for the user.

In FIG. 26, the biometric information measurement system 1 estimates that user U's score is good when he consumes XX yogurt, and therefore that XX yogurt is suitable for user U. Therefore, the biometric information measurement system 1 generates content CT9 including provided information suggesting that XX yogurt is suitable for user U and that he consumes it, as well as a button IC91 for purchasing XX yogurt, and displays this on the display device 300.

When button IC91 in content CT9 displayed on display device 300 is selected, display device 300 displays information such as an EC (electronic commerce) site selling XX yogurt. In this way, when the score starts to deteriorate, display device 300 displays information suggesting products related to intestinal health tools that have been effective in the past.

When button IC32 in content CT4 displayed on display device 300 is selected, display device 300 may display information other than content CT7 shown in FIG. 24. For example, when button IC32 in content CT4 displayed on display device 300 is selected, display device 300 may display information such as content CT10 shown in FIG. 27. FIG. 27 is a diagram showing an example of information about other users provided to a user.

Content CT10 in Figure 27 corresponds to, for example, a screen related to information about other users displayed by the display device 300. Content CT10 includes information related to the intestinal activity of other users who are similar to user U. In Figure 27, content CT10 includes information related to the intestinal activity records of other users in their 30s who have similar attributes to user U, who is in his 30s.

For example, the display device 300 outputs a group of information linked to attributes and intestinal scores associated with information (such as IDs) that identifies other users similar to user U. For example, the display device 300 displays content CT10 including intestinal activity records showing the intestinal activity content and duration of each of the other users, as well as information such as fluctuations in the intestinal score during that intestinal activity period. In this way, the display device 300 allows users to view information linked to the intestinal activity events and results of other users (people).

For example, when button IC6 in content CT1 displayed on display device 300 is selected, display device 300 displays information such as content CT11 shown in FIG. 28. FIG. 28 is a diagram showing an example of information about users who have relationships with the user. FIG. 28 shows an example of a display in which user U's family consists of four people: user U (me), spouse (father), and two children (child A and son B). For example, biometric information measurement system 1 manages, for each user, information (ID, etc.) that identifies users who have relationships with that user, by linking it to information (ID, etc.) that identifies that user, thereby making it possible to identify users who have relationships with each user.

Content CT11 in FIG. 28 corresponds, for example, to a screen displaying a list of users who have relationships with the user, as displayed by the display device 300. Content CT11 includes the four ranks of each of user U's family members up to the time of display. Content CT11 includes a button IC101 with the rank B for spouse (father) and the label "→View details." Content CT11 also includes a button IC102 with the rank A for user U (me). Content CT11 also includes a button IC103 with the rank B for child (child A) and the label "→View details." Content CT11 also includes a button IC104 with the rank C for child (boy B) and the label "→View details."

When the "View details" button corresponding to a user is selected, the display device 300 transitions the display to display information showing the results for that individual user. For example, when button IC101 is selected, the display device 300 displays information showing the individual estimation results for the spouse (father). For example, the display device 300 switches the information displayed in the display area AR1 from information about user U (me) to information about the spouse (father).

In this way, the biometric information measurement system 1 can display the results of other people through ID linking. The biometric information measurement system 1 transmits data to a third party when certain conditions, such as ID linking, are met. Note that in the above example, family members were used as examples of users who have a relationship with the user, but users who have a relationship with the user are not limited to family members; they could also be users who belong to a common institution, such as a hospital or gym, or people who provide health management support to the user, such as doctors or gym trainers.

For example, when button IC2 in content CT1 displayed on display device 300 is selected, display device 300 displays information such as content CT12 shown in Figure 29. Figure 29 shows an example of rank information related to a user.

Content CT12 in FIG. 29 corresponds, for example, to a screen related to intestinal health displayed by display device 300. Content CT12 includes rank information based on user U's intestinal rank at the time of display. In FIG. 29, content CT12 includes information regarding the distribution of intestinal ranks among a group of users in their 30s who have attributes similar to user U's. In this case, bioinformation measurement system 1 extracts information about users in their 30s from the user information it manages, generates information indicating the distribution of intestinal ranks among the group of users in their 30s based on the extracted information, and generates content CT12 by adding information indicating user U's rank to the generated distribution information. In FIG. 29, display device 300 displays content CT12 indicating that user U's intestinal rank is C, which is average for a group of users in their 30s. This allows display device 300 to enable users to compare evaluations such as ranks with other users (people) who are similar (in attributes, etc.). Additionally, CT12 may also be a rank evaluation of a score related to intestinal movement (e.g., a first evaluation) or a rank evaluation of an intestinal environment index.

The biological information measurement system 1 may also notify the user at a predetermined timing. The biological information measurement system 1 may display any information in the display area AR11 of the display device 300 shown in FIG. 30. FIG. 30 is a diagram showing an example of information notification to the user.

For example, if the score of the user (the user) using the display device 300 starts to deteriorate, the display device 300 displays content CT13 in the display area AR11, including information such as "Caution! Your intestinal rank is dropping!" For example, if user U's intestinal rank starts to deteriorate, the display device 300 of user U displays content CT13 in the display area AR11. In this way, the display device 300 calls the user's attention when their own score starts to deteriorate.

Furthermore, if the score of another person (another user) who has a relationship with the user (the user himself/herself) using the display device 300 starts to deteriorate, the display device 300 displays content CT14 in the display area AR11, including information such as "Caution! Boy B's intestinal rank is dropping! Let's check it out." For example, if the intestinal rank of Boy B, the child of user U, starts to deteriorate, the display device 300 of user U displays content CT14 in the display area AR11. In this way, the display device 300 calls attention when the score of another person who has a relationship with the user starts to deteriorate.

The biological information measurement system 1 may also notify the user based on the user's usage status. This will be explained using Figures 31 and 32. Figures 31 and 32 are diagrams showing examples of information notifications based on the user's usage status. For example, the biological information measurement system 1 may send push notifications based on the user's login history to the intestinal health app. The biological information measurement system 1 may also evaluate the user's level of interest in intestinal health based on the number of times the user logs in to the intestinal health app and the frequency of inputting intestinal health information.

For example, if a user is actively engaged in activities, the bioinformation measurement system 1 may evaluate the user as having a high level of interest in intestinal health and notify the user of information praising the user for their active activities. In FIG. 31, if a user logs in to an intestinal health app for 10 consecutive days, the bioinformation measurement system 1 notifies the user of information such as content CT15. For example, if user U logs in to the intestinal health app for 10 consecutive days, user U's display device 300 displays content CT15. For example, when user U logs in to the intestinal health app on the 10th day, the display device 300 displays content CT15 superimposed on content CT1 (pop-up display).

For example, if a user has not logged in to the intestinal health app for a period of time (e.g., no login for a week), the biological information measurement system 1 may assess that the user has a low level of interest in intestinal health and notify the user of information encouraging active activity. If the biological information measurement system 1 assesses that the user has a low level of interest in intestinal health, it displays information encouraging the user to be active in the display area AR12 of the display device 300 shown in FIG. 32.

For example, if a user using the display device 300 has not logged in to the intestinal activity app for a predetermined period of time (e.g., 7 days), the display device 300 will display content CT16 in the display area AR12, including information such as "You haven't logged in for xx days. Why not restart your intestinal activity?" For example, if user U has not logged in to the intestinal activity app for xx days, user U's display device 300 will display content CT16 in the display area AR12. In this way, the biological information measurement system 1 may provide notifications according to the user's level of interest in intestinal activity, in order to maintain the user's motivation.

As described above, the biological information measurement system 1 can provide various types of information to inform the user of desired information. For example, if the user's intestinal condition is poor, the biological information measurement system 1 can encourage the user to improve that condition. The biological information measurement system 1 can satisfy the user's desire to know when their health condition is deteriorating, and by notifying the user when their score is declining, can motivate the user to reconsider their lifestyle.

In addition, if the condition of the intestines is good, the biological information measurement system 1 can encourage the user to maintain that condition. The biological information measurement system 1 can fulfill the user's desire to manage their health in conjunction with their lifestyle habits, and by informing the user that their score is good, it can give the user a sense of security. In addition, the biological information measurement system 1 can fulfill the desires of users who want to use it to help manage the health of their family members and patients, for example, to know the condition of their family members' stomachs and plan their meal plans.

In addition, if the user's intestinal condition shows signs of improvement, the bioinformation measurement system 1 can encourage them to further improve their condition. The bioinformation measurement system 1 can satisfy the user's desire to find an intestinal activity that suits their body, or to use the information as an indicator of the effectiveness of intestinal activity, and can recognize the effects of foods such as yogurt that the user has started to eat, and encourage them to continue consuming that food. Furthermore, the bioinformation measurement system 1 can serve as a tool to maintain motivation for intestinal activity, motivating the user to work hard to achieve their goals.

The biological information measurement system 1 may also output an alert when the score falls below a predetermined level when compared with past data. The biological information measurement system 1 may also notify the completion of measurement when the first biological information, second biological information, provided information, or score are all collected. The biological information measurement system 1 may also prioritize and output information with poor results from the first biological information and second biological information, along with the rationale. The biological information measurement system 1 may also update the recommendation information or score after each excretory act. The biological information measurement system 1 also detects the properties of the stool using an image sensor and detects fecal gas using a gas sensor.

In addition to the characteristics of the stool, the biological information measurement system 1 may also detect the user's subjective information, such as the amount, color, density, and degree of relief after defecation, as information regarding intestinal peristalsis. In addition to defecation gas, the biological information measurement system 1 may also detect the user's subjective information regarding the color and odor of the stool as information regarding the intestinal environment.

The biological information measurement system 1 generates various types of content as described above and provides the generated content to the user. For example, the control device 100 of the biological information measurement system 1 generates various types of information such as content CT1 to CT16. The control device 100 then transmits the various types of information such as the generated content CT1 to CT16 to the user's display device 300. The display device 300 receives the various types of information such as content CT1 to CT16 and displays the received various types of information such as content CT1 to CT16.

In this case, for example, the processing unit 132 of the control device 100 functions as a generation unit that performs generation processing of various types of information. The processing unit 132 generates various types of information, such as content to be displayed on the display device 300. The processing unit 132 generates the screens (content) shown in Figures 16 to 32. For example, the processing unit 132 generates content (image information) to be provided to the display device 300 by appropriately using various technologies related to image generation, image processing, etc. For example, the processing unit 132 generates screens (image information) to be provided to the display device 300 by appropriately using various technologies such as Java (registered trademark). Note that the processing unit 132 may generate content (image information) to be provided to the display device 300 based on the format of CSS (Cascading Style Sheets), JavaScript (registered trademark), or HTML (Hyper Text Markup Language). Furthermore, for example, the processing unit 132 may generate content in various formats, such as JPEG (Joint Photographic Experts Group), GIF (Graphics Interchange Format), and PNG (Portable Network Graphics).

The above-described embodiments and variations can be combined as appropriate as long as they do not cause inconsistencies in the processing content.

Further advantages and modifications may readily occur to those skilled in the art. Therefore, the invention in its broader aspects is not limited to the specific details and representative embodiments shown and described above. Accordingly, various modifications may be made without departing from the spirit or scope of the general inventive concept as defined by the appended claims and their equivalents.

The above-described embodiments and modifications may have the following configurations, but are not limited to these.
(1)
A biological information measurement system that measures biological information of a user of a toilet room based on information about excrement discharged into a bowl of a toilet installed in the toilet room,
a first detection unit that detects feces;
a second detection unit that detects fecal gas;
a control unit that executes an estimation process to estimate at least one of the provided information or a score related to the health of the user based on the detection result of the first detection unit and the detection result of the second detection unit, and executes control to output the result of the estimation process to an external device;
A biological information measuring system comprising:
(2)
The control unit
estimating first biological information based on the properties of the stool from the detection result of the first detection unit;
second biological information based on the amount or concentration of the defecation gas from the detection result of the second detection unit;
The biological information measuring system according to (1), characterized in that it executes control so as to output the first biological information and the second biological information.
(3)
The control unit
The biological information measuring system described in (1) or (2) is characterized in that the estimation process is performed using a larger number of samples of the detection results of the second detection unit than the number of samples of the detection results of the first detection unit.
(4)
The biometric information measurement system described in (3) is characterized in that the estimation process uses the detection result of the first detection unit obtained from a single toilet use and multiple detection results of the second detection unit obtained from multiple toilet use.
(5)
The control unit
the higher the first evaluation corresponding to each classification of the stool properties based on the detection result of the first detection unit, the higher the score is estimated to be;
The biometric information measuring system according to any one of (1) to (4), characterized in that the estimation process is performed in such a way that the higher the second evaluation based on the detection result of the second detection unit, the higher the score is estimated to be.
(6)
A biological information measurement system that measures biological information of a user of a toilet room based on information about excrement discharged into a bowl of a toilet installed in the toilet room,
a first detection unit that detects information regarding intestinal peristalsis;
a second detection unit that detects information about the intestinal environment;
a control unit that executes an estimation process to estimate at least one of the provided information or a score related to the health of the user based on the detection result of the first detection unit and the detection result of the second detection unit, and executes control to output the result of the estimation process to an external device;
A biological information measuring system comprising:
(7)
A biological information measurement system that measures biological information of a user of a toilet room based on information about excrement discharged into a bowl of a toilet installed in the toilet room,
a control unit that executes an estimation process to estimate at least one of the provided information or score related to the health of the user based on the detection result by the first detection unit that detects stool and the detection result by the second detection unit that detects defecation gas, and controls to output the result of the estimation process to an external device;
A biological information measuring system comprising:
(8)
A biological information measurement system that measures biological information of a user of a toilet room based on information about excrement discharged into a bowl of a toilet installed in the toilet room,
a control unit that executes an estimation process to estimate at least one of the provided information or score related to the health of the user based on a detection result by a first detection unit that detects information related to intestinal peristalsis and a detection result by a second detection unit that detects information related to the intestinal environment, and controls to output the result of the estimation process to an external device;
A biological information measuring system comprising:

REFERENCE SIGNS LIST 1 Biometric information measurement system 2 Toilet seat device 3 Main body 4 Measurement device 5 Toilet seat 6 Cleaning nozzle 7 Toilet bowl 8 Bowl 9 Toilet lid 10 Suction device 21 First detection unit (imaging device)
22 Second detection unit (gas detection device)
40 Gas sensor 50 Light receiving unit 100 Control device 110 Communication unit 120 Storage unit 130 Control unit 131 Acquisition unit 132 Processing unit 133 Output unit R Toilet room

Claims (10)

A biological information measurement system that measures biological information of a user of a toilet room based on information about excrement discharged into a bowl of a toilet installed in the toilet room,
a first detection unit that detects feces;
a second detection unit that detects fecal gas;
a control unit that executes an estimation process to estimate at least one of the intestinal score of the user or recommended information for improving the intestinal environment based on the detection result of the first detection unit and the detection result of the second detection unit, and executes control to output the result of the estimation process to an external device;
Equipped with
The control unit
estimating a first evaluation based on the properties of the stool from the detection result of the first detection unit;
estimating a second evaluation based on time-series data of the detection results of the second detection unit during multiple toilet visits during a predetermined period;
The biological information measuring system is characterized in that the estimation process is performed based on the first evaluation and the second evaluation . The second detection unit detects health gases and odorous gases contained in the feces gas,
The control unit
The biological information measuring system according to claim 1 , wherein the second evaluation is estimated based on a ratio of the amounts or concentrations of the health-related gas and the odorous gas from the detection result of the second detection unit. The control unit
The biological information measuring system according to claim 1 , wherein the estimation process is performed using a larger number of samples of the detection results of the second detection unit than the number of samples of the detection results of the first detection unit. The biometric information measuring system of claim 3, characterized in that the estimation process uses the detection result of the first detection unit obtained from a single toilet use and multiple detection results of the second detection unit obtained from multiple toilet use. The control unit
the higher the first evaluation corresponding to each classification of the stool properties based on the detection result of the first detection unit, the higher the score is estimated to be;
The biological information measuring system according to any one of claims 1 to 4, characterized in that the estimation process is performed in such a way that the higher the second evaluation based on the detection result of the second detection unit, the higher the score is estimated to be. A biological information measurement system that measures biological information of a user of a toilet room based on information about excrement discharged into a bowl of a toilet installed in the toilet room,
a first detection unit that detects information regarding intestinal peristalsis;
a second detection unit that detects information about the intestinal environment;
a control unit that executes an estimation process to estimate at least one of the intestinal score of the user or recommended information for improving the intestinal environment based on the detection result of the first detection unit and the detection result of the second detection unit, and executes control to output the result of the estimation process to an external device;
Equipped with
The control unit
estimating a first evaluation based on the properties of the stool from the detection result of the first detection unit;
estimating a second evaluation based on time-series data of the detection results of the second detection unit during multiple toilet visits during a predetermined period;
The biological information measuring system is characterized in that the estimation process is performed based on the first evaluation and the second evaluation . A biological information measurement system that measures biological information of a user of a toilet room based on information about excrement discharged into a bowl of a toilet installed in the toilet room,
a control unit that executes an estimation process to estimate at least one of the intestinal score of the user or recommended information for improving the intestinal environment based on the detection result by the first detection unit that detects stool and the detection result by the second detection unit that detects defecation gas, and executes control to output the result of the estimation process to the outside;
Equipped with
The control unit
estimating a first evaluation based on the properties of the stool from the detection result of the first detection unit;
estimating a second evaluation based on time-series data of the detection results of the second detection unit during multiple toilet visits during a predetermined period;
The biological information measuring system is characterized in that the estimation process is performed based on the first evaluation and the second evaluation . A biological information measurement system that measures biological information of a user of a toilet room based on information about excrement discharged into a bowl of a toilet installed in the toilet room,
a control unit that executes an estimation process to estimate at least one of the intestinal score of the user or recommended information for improving the intestinal environment based on a detection result by a first detection unit that detects information related to intestinal peristalsis and a detection result by a second detection unit that detects information related to the intestinal environment , and controls to output the result of the estimation process to the outside;
Equipped with
The control unit
estimating a first evaluation based on the properties of the stool from the detection result of the first detection unit;
estimating a second evaluation based on time-series data of the detection results of the second detection unit during multiple toilet visits during a predetermined period;
The biological information measuring system is characterized in that the estimation process is performed based on the first evaluation and the second evaluation . The control unit
outputting content relating to the properties of the stool estimated from the detection result of the first detection unit obtained in one toilet use, while
Outputting time-series data based on the amount or concentration of the defecation gas estimated from the detection results of the second detection unit for a predetermined period as a graph.
2. The biological information measuring system according to claim 1. The control unit
outputting, as a graph, time series data of the properties of the stool estimated from the detection results of the first detection unit for a predetermined period of time and time series data based on the amount or concentration of the fecal gas estimated from the detection results of the second detection unit;
outputting the score or the recommendation information based on the detection result of the first detection unit and the detection result of the second detection unit during the predetermined period;
2. The biological information measuring system according to claim 1.