JP7567219B2 - BEHAVIORAL INFORMATION ANALYSIS METHOD, PROGRAM, AND INFORMATION PROCESSING APPAR - Google Patents

Description

This disclosure relates to the analysis of information regarding the behavior of care recipients.

Conventionally, technology has been proposed for reliably providing the care services required by care recipients in care facilities where the care recipients live by detecting their behavior using various sensors. For example, JP 2001-307257 A (Patent Document 1) discloses a care support system that detects the condition of the care recipient by using a room detection device installed in the room where the care recipient lives in a hospital, facility, home, etc., in order to detect the need for care (seriousness, urgency, danger, etc.).

JP 2001-307257 A

In nursing care facilities, it is considered important not only to provide care but also to improve the quality of life of those receiving care. Improving the quality of life of those receiving care can generate benefits for both the care recipients and the nursing care facility in terms of reducing the amount of care services that must be provided. Therefore, there is a demand for technology that can utilize the detection output of the condition of those receiving care to improve their quality of life.

This disclosure was conceived in light of the above-mentioned circumstances, and its purpose is to provide technology for utilizing the detection output of the condition of a care recipient to improve the quality of life of the care recipient.

According to one aspect of the present disclosure, there is provided a behavioral information analysis method comprising the steps of: acquiring in-room behavioral information as information on one or more types of behavior in a room assigned to the care recipient over a certain period of time, using detection outputs over a certain period of time of one or more sensors that detect the condition of the care recipient; acquiring outside-room behavioral information as information on one or more types of behavior outside the room over a certain period of time, using detection outputs over a certain period of time of one or more sensors; and deriving correlations between types of the one or more types of in-room behavioral information and the one or more types of outside-room behavioral information.

The one or more sensors may include an activity meter worn by the person being cared for.
The activity meter may have a location information detection function.

The one or more sensors may include a camera that images the room.
The behavior information in the room may include the sleeping time.

The activity information in the room may include statistical values regarding the activities in the room.
The statistics may include at least one of the following: range of movement, time spent outside the sleeping area, number of times a given movement pattern is repeated, and time when movement is stopped.

The behavior information within the room may include information describing the nature of walking within the room.
The information representing the nature of walking within the room may include at least one of walking speed, an area extending beyond a frequently traveled path, and a distance extending beyond a frequently traveled path.

The outside-room activity information may include the number of steps taken outside the room.
The outside-room behavior information may include at least one of the time the care recipient was outside the room and the time the care recipient was in a given state outside the room.

The given state may include at least one of a standing state, a sitting state, and a lying state.

According to another aspect of the present disclosure, a program is provided that, when executed by a processor of an information processing device, causes the information processing device to perform the above method.

According to yet another aspect of the present disclosure, there is provided an information processing device including a processor and a memory storing the above program.

According to the present disclosure, one or more types of in-room behavioral information and one or more types of outside-room behavioral information for a resident are generated, and correlations between the types are derived. This allows the present disclosure to provide insight into which type of behavior should be changed in order to improve another type of behavior, which can contribute to improving the quality of life of the resident.

FIG. 1 is a diagram illustrating an example of the configuration of a monitoring system. 13 is a diagram for explaining an example of the detection range of a sensor in a room 900. FIG. 1 is a diagram showing the hardware configuration of a sensor box 100, a management server 200, and a mobile terminal 300 of a monitoring system. FIG. 4 is a diagram illustrating a hardware configuration of a cloud server 400. FIG. 4 is a diagram illustrating an example of a data structure of behavior information. FIG. 4 is a diagram showing the contents of each item of behavior information in a room. FIG. 13 is a diagram for explaining an example of a calculation method for the item "activity range." FIG. 13 is a diagram for explaining an example of a calculation method for the item “degree of wobble.” FIG. 13 is a diagram showing the contents of each item of outside-room activity information. FIG. 4 is a diagram illustrating an example of a data structure of related information. 11 is a diagram showing an example of an acquisition mode of information for generating behavior information of the management server 200. FIG. 13 is a flowchart of a process for generating correlation information for each resident. FIG. 13 is a diagram illustrating an example of a combination of items for which a correlation is derived. FIG. 13 is a diagram showing another example of a combination of items for which a correlation has been derived. FIG. 13 is a diagram showing yet another example of a combination of items for which a correlation has been derived. FIG. 13 is a diagram showing yet another example of a combination of items for which a correlation has been derived.

Below, an embodiment of a behavioral information analysis method implemented in a monitoring system will be described with reference to the drawings. In the following description, identical parts and components are given the same reference numerals. Their names and functions are also the same. Therefore, their description will not be repeated.

[Configuration of monitoring system]
Fig. 1 is a diagram showing an example of the configuration of a monitoring system. As an example of a monitoring target, the residents in each room provided in a room area RM of a facility are adopted. In the monitoring system of Fig. 1, rooms 900A and 900B are provided in the room area RM. The room 900A is assigned to a resident 800A. The room 900B is assigned to a resident 800B. In the example of Fig. 1, the number of rooms included in the monitoring system is two, but the number is not limited to this.

In the monitoring system, a sensor box 100A installed in a room 900A, a sensor box 100B installed in a room 900B, a management server 200 installed in a management center ST, and an access point AP are connected via a network NT.

In the monitoring system, the mobile terminal 300A carried by staff member NA and the mobile terminal 300B carried by staff member NB are connected to the network NT via the access point AP. Furthermore, the sensor boxes 100A and 100B, the management server 200, and the access point AP can communicate with the cloud server 400 via the network NT.

The room 900A includes, as equipment, a bed 901A, a toilet 902A, and furniture 903A. A door sensor 510A is installed on the door of the room 900A to detect whether the door is open or closed. A toilet sensor 520A is installed on the door of the toilet 902A to detect whether the toilet 902A is open or closed. An odor sensor 530A is installed on the bed 901A to obtain excretion information of the resident 800A. The resident 800A wears a vital sensor 540A that detects vital information of the resident 800A. One example of the detected vital information is the resident's body temperature. Another example is the resident's breathing. Yet another example is the resident's heart rate. Yet another example is two or more types of information among these types of information. In the room 900A, the resident 800A can operate the care call handset 500A.

In this specification, when referring to matters common to the multiple sensor boxes 100A and 100B, the term "sensor box 100" is used to collectively refer to the sensor boxes 100A and 100B. Similarly, the terms "resident 800," "room 900," "toilet 902," "furniture 903," "care call handset 500," "door sensor 510," "toilet sensor 520," "odor sensor 530," and "vital sensor 540" are used for the residents 800A and 800B, rooms 900A and 900B, beds 901A and 901B, toilets 902A and 902B, furniture 903A and 903B, care call handset 500A and 500B, door sensors 510A and 510B, toilet sensors 520A and 520B, odor sensors 530A and 530B, and vital sensors 540A and 540B, respectively.

The sensor box 100A has a built-in sensor for detecting the behavior of an object in the living room 900A. One example of a sensor is a Doppler sensor for detecting the movement of an object. Another example is a camera. Further examples are a care call handset 500, a door sensor 510, a toilet sensor 520, an odor sensor 530, or a vital sensor 540. The sensor box 100A includes at least one of these sensors as a sensor.

Figure 2 is a diagram illustrating an example of the detection range of a sensor in a room 900. In the example of Figure 2, the sensor box 100 is installed on the ceiling CL of the room 900.

The range AR generally represents the detection range of the sensor. If the sensor is a Doppler sensor, the Doppler sensor detects behavior that occurs within the range AR. If the sensor is a camera, the camera captures images within the range AR.

Returning to FIG. 1, the management server 200 installed in the management center ST is connected to a display 206 and an input device 209. The input device 209 is, for example, a keyboard.

In the monitoring system of FIG. 1, the number of mobile terminals connected to the network NT via the access point AP is two (mobile terminals 300A and 300B), but the number is not limited to this. In this specification, when referring to matters common to mobile terminals 300A and 300B, the term "mobile terminal 300" is used to collectively refer to mobile terminals 300A and 300B.

Communication between each element in the monitoring system of Figure 1 may be wired or wireless.

The sensor box 100 does not necessarily have to include the camera 105 and/or the Doppler sensor 106. The camera 105 and/or the Doppler sensor 106 may be provided outside the sensor box 100, similar to the door gate sensor 510, etc. The control device 101 may acquire the detection output of the camera 105 and/or the Doppler sensor 106 provided outside the sensor box 100 via a given interface.

The vital sensor 540 does not necessarily have to be attached to the resident. In one example, the vital sensor 540 is realized by an infrared sensor or the like installed at a distance from the resident, and outputs vital information (body temperature) by detecting the resident's temperature. In another example, the vital sensor 540 is realized by a Doppler sensor 106. The Doppler sensor 106 irradiates microwaves toward the resident. The microwaves cause a Doppler effect due to slight displacement of the resident's chest caused by the beating of the heart, causing the frequency to fluctuate. The Doppler sensor 106 detects the resident's heartbeat based on the fluctuation in frequency. In yet another example, the Doppler sensor 106 detects the resident's breathing.

[Configuration of each element of the monitoring system]
Fig. 3 is a diagram showing the hardware configuration of the sensor box 100, the management server 200, and the mobile terminal 300 of the monitoring system. Fig. 4 is a diagram showing the hardware configuration of the cloud server 400. Below, an example of the configuration of each device in the monitoring system will be described with reference to Figs. 3 and 4.

(Sensor box 100)
The sensor box 100 includes a control device 101 , a ROM (Read Only Memory) 102 , a RAM (Random Access Memory) 103 , a communication interface 104 , a camera 105 , a Doppler sensor 106 , a wireless communication device 107 , and a storage device 120 .

The control device 101 controls the sensor box 100. The control device 101 is, for example, configured with at least one integrated circuit. The integrated circuit is, for example, configured with at least one CPU (Central Processing Unit), at least one ASIC (Application Specific Integrated Circuit), at least one FPGA (Field Programmable Gate Array), or a combination of these.

An antenna (not shown) and the like are connected to the communication interface 104. The sensor box 100 exchanges data with external communication devices via the antenna. External communication devices include, for example, a management server 200, a mobile terminal 300, an access point AP, a cloud server 400, and other communication terminals.

In one implementation, the camera 105 is a near-infrared camera. The near-infrared camera includes an IR (Infrared) projector that projects near-infrared light. By using the near-infrared camera, an image showing the interior of the room 900 can be captured even at night. In another implementation, the camera 105 is a surveillance camera that receives only visible light. In still another implementation, a 3D sensor or a thermography camera may be used as the camera 105. The sensor box 100 and the camera 105 may be configured as an integral unit or as separate units.

The Doppler sensor 106 is, for example, a microwave Doppler sensor that emits and receives radio waves to detect the behavior (movement) of objects in the room 900. This allows the biometric information of the resident 800 in the room 900 to be detected. In one example, the Doppler sensor 106 emits microwaves in the 24 GHz band toward the bed 901 in each room 900 and receives the reflected waves reflected by the resident 800. The reflected waves are Doppler shifted due to the movements of the resident 800. The Doppler sensor 106 can detect the breathing condition and heart rate of the resident 800 from the reflected waves.

The wireless communication device 107 receives signals from the care call handset 500, the door sensor 510, the toilet sensor 520, the odor sensor 530, and the vital sensor 540, and transmits the signals to the control device 101. For example, the care call handset 500 has a care call button 501, and when the care call button 501 is operated, it transmits a signal indicating that operation has occurred to the wireless communication device 107. The door sensor 510, the toilet sensor 520, the odor sensor 530, and the vital sensor 540 each transmit their respective detection outputs to the wireless communication device 107.

The storage device 120 is, for example, a storage medium such as a hard disk or an external storage device. The storage device 120 stores the programs executed by the control device 101 and various data used to execute the programs. The various data may include behavioral information of the resident 800.

At least one of the above programs and data may be stored in a storage device other than the storage device 120 (for example, a storage area of the control device 101 (e.g., cache memory, etc.), ROM 102, RAM 103, an external device (e.g., management server 200, mobile terminal 300, etc.)) as long as the storage device is accessible by the control device 101.

(Behavioral Information)
The above behavioral information will be described. The behavioral information is, for example, information indicating that the resident 800 has performed a predetermined behavior. In one example, the predetermined behavior includes four behaviors: "getting up" indicating that the resident 800 has woken up, "getting out of bed" indicating that the resident 800 has left the bed, "falling down" indicating that the resident 800 has fallen down from the bed, and "falling down" indicating that the resident 800 has collapsed.

In one embodiment, the control device 101 generates behavioral information of the resident 800 associated with each room 900 based on images captured by a camera 105 installed in each room 900. The control device 101, for example, detects the head of the resident 800 from the images, and detects whether the resident 800 has "gotten up," "got out of bed," "fallen over," or "falled" based on the change over time in the size of the detected head of the resident 800. A specific example of generating behavioral information is described in more detail below.

First, the area in the room 900 where the bed 901 is located, the first threshold Th1, the second threshold Th2, and the third threshold Th3 are stored in the storage device 120. The first threshold Th1 distinguishes the size of the resident's head between when the resident is in a lying position and when the resident is in a sitting position within the area where the bed 901 is located. The second threshold Th2 distinguishes whether the resident is in a standing position or not based on the size of the resident's head within the room 900 excluding the area where the bed 901 is located. The third threshold Th3 distinguishes whether the resident is in a lying position or not based on the size of the resident's head within the room RM excluding the area where the bed 901 is located.

The control device 101 extracts a moving object region from the target image as the area of the resident 800, for example, by background subtraction or frame subtraction. The control device 101 further extracts the head region of the resident 800 from the extracted moving object region, for example, by a circular or elliptical Hough transform, by pattern matching using a pre-prepared head model, and by using a threshold derived by a neural network trained for head detection. The control device 101 detects "getting up," "getting out of bed," "falling over," and "falling down" from the position and size of the extracted head.

The control device 101 may determine that the action "getting up" has occurred when the position of the head extracted as described above is within the area where the bed 901 is located and when it detects that the size of the head extracted as described above has changed from the size of a lying position to the size of a sitting position by using the first threshold value Th1.

The control device 101 may determine that the action "getting out of bed" has occurred when the position of the head extracted as described above moves from within the area where the bed 901 is located to outside the area where the bed 901 is located, and when it detects that the size of the head extracted as described above has changed from a certain size to the size of a standing position by using the second threshold value Th2.

The control device 101 may determine that the behavior "fall" has occurred when the head position extracted as described above moves from within the area where the bed 901 is located to outside the area where the bed 901 is located, and when the size of the head extracted as described above changes over time from a certain size to the size of a lying position by using a third threshold value Th3.

The control device 101 may determine that the behavior "fall" has occurred if it detects that the position of the head extracted as described above is located within the room 900 excluding the area where the bed 901 is located, and that the size of the extracted head has changed from a certain size to the size of a lying position by using a third threshold value Th3.

As described above, in one specific example, the control device 101 of the sensor box 100 generates behavioral information of the resident 800. Note that in the monitoring system, other elements may generate behavioral information of the resident 800 using images of the inside of the room 900.

(Management Server 200)
The management server 200 includes a control device 201 , a ROM 202 , a RAM 203 , a communication interface 204 , a display interface 205 , an operation interface 207 , and a storage device 220 .

The control device 201 controls the management server 200. The control device 201 is, for example, configured with at least one integrated circuit. The integrated circuit is, for example, configured with at least one CPU, at least one ASIC, at least one FPGA, or a combination of these.

An antenna (not shown) and the like are connected to the communication interface 204. The management server 200 exchanges data with external communication devices via the antenna. External communication devices include, for example, the sensor box 100.

The display interface 205 is connected to the display 206, and sends image signals to the display 206 to display images in accordance with instructions from the control device 201, etc.

The operation interface 207 is, for example, a USB (Universal Serial Bus) terminal, and is connected to the input device 209. The operation interface 207 receives a signal indicating a user operation from the input device 209. The input device 209 is, for example, a mouse, a keyboard, a touch panel, or any other device capable of receiving an input operation from the user.

The storage device 220 is, for example, a storage medium such as a hard disk or an external storage device. In one implementation example, the storage device 220 stores a program executed by the control device 201, but the program may be stored in another storage device accessible to the control device 201.

(Mobile terminal 300)
The mobile terminal 300 includes a control device 301 , a RAM 303 , a communication interface 304 , a display 305 , an input device 306 , and an internal memory 320 .

The control device 301 controls the mobile terminal 300. The control device 301 is, for example, configured with at least one integrated circuit. The integrated circuit is, for example, configured with at least one CPU, at least one ASIC, at least one FPGA, or a combination thereof.

An antenna (not shown) and the like are connected to the communication interface 304. The mobile terminal 300 exchanges data with external communication devices via the antenna and the access point AP (FIG. 1). External communication devices include, for example, the sensor box 100 and the management server 200.

The display 305 is realized, for example, by an organic EL (Electro Luminescence) display. The input device 306 is realized, for example, by a touch sensor overlaid on the display 305. The touch sensor accepts various operations on the mobile terminal 300 by touch operations, and outputs the contents of the operations to the control device 301.

The built-in memory 320 is, for example, a storage medium such as an eMMC (Embedded MultiMediaCard). As an example, the built-in memory 320 stores a program executed by the control device 301, but the program may be stored in a storage device other than the built-in memory 320 as long as the storage device is accessible by the control device 301.

(Cloud server 400)
The cloud server 400 includes a control device 401 , a ROM 402 , a RAM 403 , a communication interface 404 , and a storage device 420 .

The control device 401 controls the cloud server 400. The control device 401 is, for example, configured with at least one integrated circuit. The integrated circuit is, for example, configured with at least one CPU, at least one ASIC, at least one FPGA, or a combination of these.

An antenna (not shown) and the like are connected to the communication interface 404. The cloud server 400 exchanges data with external communication devices via the antenna. External communication devices include, for example, the sensor box 100 and the management server 200.

The storage device 420 is, for example, a storage medium such as a hard disk or an external storage device. In one implementation example, the storage device 420 stores a program executed by the control device 401, but the program may be stored in another storage device accessible to the control device 401.

(The meaning of the term "program" in this specification)
In the monitoring system, various "programs" may be provided not as standalone programs but as part of any program. Various "programs" may be realized by any multiple programs working together. In one example, when the control device 101 of the sensor box 100 executes a first program to realize the function described in this specification, the first program may use some modules of the second program. Even if the first program does not include some modules for realizing the function, if it mainly contributes to the realization of the function, it does not deviate from the purpose of the program for realizing the function. In addition, the functions described in this specification may be realized in part or in whole by dedicated hardware. Furthermore, the device providing the functions described in this specification may provide some or all of its functions from an external device as a so-called cloud service.

[Tenant behavior information]
The management server 200 generates and stores information about the behavior of each resident (hereinafter, referred to as "behavior information") using the detection output of one or more sensors. Fig. 5 is a diagram showing an example of the data structure of the behavior information. The behavior information of each resident is stored in the storage device 220, for example.

Figure 5 shows the behavioral information of a resident assigned ID "0001". The behavioral information is composed of data for each day, and includes behavioral information of the resident in the room (behavioral information inside the room) and behavioral information of the resident outside the room (behavioral information outside the room).

In-room activity information includes eight items ("sleep," "range of activity," "amount of activity," "walking speed," "change in movement route," "unsteadiness," "repetitive behavior," and "stopping"). Outside-room activity information includes five items ("number of steps," "active time," "standing time," "sitting time," and "time in bed"). In Figure 5, information for each day is shown, and the values of activity information for "sleep," "range of activity," etc. on May 1, 2020 are indicated by symbols such as "Va(1)," "Va(2)," etc.

FIG. 6 is a diagram showing the contents of each item of the activity information in the room.
Referring to FIG. 6, in the behavior information in the room, "sleep" indicates the sleeping hours for each day.

The "activity range" represents the area calculated based on the trajectory of the resident's movements in the room. An example of a method for calculating the "activity range" is described below with reference to Figure 7.

Figure 7 is a diagram for explaining an example of a method for calculating the item "range of movement." Figure 7 shows a grid 1600 defined for a room and a trajectory T1 of the resident's movement. Of the 144 (12x12) squares that make up grid 1600, nine squares including trajectory T1 are hatched. In the example of Figure 7, the area of the square that includes trajectory T1 is calculated as the "range of movement."

Returning to Figure 6, "activity amount" represents the time a resident spent outside of bed. "walking speed" represents the speed of walking outside of bed over a given distance.

"Changes in movement path" refers to the number of times the patient deviated from the frequently used path when moving from the start point to the end point of the frequently used path outside the bed.

The management server 200 may store information specifying the positions of two or more elements in a room (such as a shelf, a television, the room door, the toilet door, etc.) in the storage device 220, and may use the history of the resident's location information to specify the resident's movement route between multiple elements in the room. Furthermore, the management server 200 may specify, among the movement routes of any two of the two or more elements (element A and element B) that match completely or at least a given percentage, as a route that is frequently used for movement between element A and element B. The management server 200 may then specify, as a "change in movement route," the number of times that the resident has moved between element A and element B via a route different from the frequently used route.

The "degree of wobble" represents the distance that the movement from a certain starting point to a certain end point deviates from the straight line trajectory from the starting point to the end point. An example of a method for calculating the "degree of wobble" is described with reference to Figure 8.

8 is a diagram for explaining an example of a method for calculating the item "degree of unsteadiness". In FIG. 8, the trajectory T2 of the resident's movement, the starting point (point P21) and the end point (point P22) of the trajectory T2 are shown, and further, a straight line (line L2) connecting point P21 and point P22 is shown. The management server 200 may specify, as the "degree of unsteadiness", a history of the distance between each point of the trajectory T2 and the line L2 (the distance from each point of the line L2 to each point of the trajectory T2 on the perpendicular line of the line L2). In specifying the "degree of unsteadiness", the management server 200 may use a position where the resident remains stationary for a certain period of time (for example, 10 seconds) or more as the starting point, and may use a position where the resident remains stationary for a certain period of time (for example, 10 seconds) or more after starting to move from the starting point as the end point. The management server 200 may determine a statistical value of the above-mentioned distance history as the "degree of wobble" instead of or in addition to the above-mentioned distance history (change in distance over time). The statistical value may be the maximum value, average value, or median value for a certain period of time (every day, every hour, etc.).

Returning to FIG. 6, "repeated behavior" represents the number of times a movement from the same starting point to the same ending point is repeated within a certain period of time. The management server 200 may use the location information of the resident to determine the value of the repeated behavior.

"Standing" refers to the time a resident stops for a certain period of time (e.g., 30 seconds) or more in a location other than a predetermined location (e.g., a location where a shelf or the like is located in a room).

Each of "range of movement," "amount of movement," "repeated movement," and "stopping" is an example of a statistical value relating to the movement of a resident in a room. Another example of a statistical value may be the number of times a particular movement (such as opening and closing the toilet door or opening and closing a window) is repeated. The management server 200 may identify these statistical values as the number of times a sensor that detects the opening and closing of doors in various locations repeatedly opens and closes at intervals of less than a certain length of time. Each of "walking speed," "change in movement route," and "degree of unsteadiness" is an example of information that represents the walking characteristics of a resident. Another example of a walking characteristic may be stride length.

The management server 200 may generate behavioral information within the room using the detection output of an activity meter worn by the resident, or may generate behavioral information within the room using the detection output of elements such as the camera 105, such as images of each room.

Figure 9 is a diagram showing the contents of each item of the outside-room activity information. Referring to Figure 9, in the outside-room activity information, "step count" indicates the number of steps. The management server 200 may determine the "step count" by using the resident's location information and acceleration information applied to the resident.

"Activity time" refers to the time that the resident was outside the room. The management server 200 may identify the "activity time" using the resident's location information.

"Standing time" refers to the time the resident spent standing outside the room. "Sitting time" refers to the time the resident spent sitting outside the room. "Bed time" refers to the time the resident spent lying down outside the room. The management server 200 may use acceleration information on the resident to obtain a history of the resident's vertical acceleration, and use this history to identify "standing time," "sitting time," and "bed time."

Each of "standing time," "sitting time," and "time in bed" is an example of a state outside the resident's room. Another example of a state outside the room may be the time spent speaking. Activity meter 600 may be equipped with a microphone, and management server 200 may identify "speaking time" as the time when the resident's voice is input into the microphone of activity meter 600. In order to identify "speaking time," voice information representing the resident's voice may be stored in advance in management server 200.

The management server 200 may generate information about activities outside the room using the detection output of an activity meter worn by the resident.

[Related Information]
The management server 200 derives a set of items having a correlation between multiple items of behavioral information. The management server 200 may propose the use of other items of behavioral information having a correlation with the behavioral information in order to propose an improvement of the behavioral information of a certain item. The management server 200 may store information representing the derived correlation in the storage device 220 as related information.

Figure 10 is a diagram showing an example of the data structure of related information. In the example of Figure 10, the related information shows other items derived as being related to each item of activity information within the room (left side of the table in Figure 10) as related items. For example, the item "number of steps" is shown as a related item to the item "sleep."

In the related information, information indicating the relationship is further added to the related items. In the example of FIG. 10, the note "increases with increase" is shown for the item "steps", which is a related item of the item "sleep". This note indicates that as the value of the related item "steps" increases, the value of "sleep" increases (sleep time becomes longer).

The annotations in the example of FIG. 10 are based on the functions used in deriving the correlations. The correlation information may also include other forms of information as annotations, such as the functions themselves that represent the functions.

The related information may include, as an appendix, a condition of the information that indicates the relevance. In the example of FIG. 10, the item "activity amount" includes the item "activity time" as a related item for the item "activity amount", and further includes the appendix "increases up to VX, decreases above VX". This appendix indicates that in the region where the activity time value is up to the value VX, the value of the activity amount increases as the activity time increases, and in the region where the activity time value exceeds VX, the value of the activity amount decreases as the activity time increases.

[Acquisition of data for generating behavioral information]
The management server 200 may use an activity meter worn by a resident as a sensor to acquire behavioral information. Fig. 11 is a diagram showing an example of how the management server 200 acquires information for generating behavioral information. In the example of Fig. 11, the management server 200 generates behavioral information of the resident 800 by using detection output acquired from an activity meter 600 worn on the arm of the resident 800.

The activity meter 600 may measure the number of steps, walking speed, walking distance, sleep time, and pulse rate of the resident 800 each day. The activity meter 600 may have a communication function and may transmit the measurement results of the activity meter 600 to the management server 200. The activity meter 600 may include a GPS (Global Positioning System) receiver and may measure location information of the activity meter 600 identified using the GPS receiver.

The management server 200 may generate behavioral information from images generated by the camera 105 in the room, and in this sense may use the camera 105 as a sensor. If the management server 200 detects an image pattern corresponding to the external pattern of the resident in the image generated by the camera 105, it may determine that the resident is located in the room, and if the management server 200 cannot detect the image pattern, it may determine that the resident is outside the room. The management server 200 may generate behavioral information of the resident by processing the images generated by the camera 105, such as by identifying the time during which the image pattern remains located within a predetermined area as the position of the bed as the resident's sleeping time.

[Process flow]
Fig. 12 is a flowchart of a process for generating correlation information (Fig. 10) for each resident. The management server 200 realizes the process of Fig. 12, for example, by causing the processor of the control device 201 to execute a given program. In the management server 200, the process of Fig. 12 may be executed by a dedicated circuit such as an ASIC.

In step S100, the management server 200 determines whether it has determined that the timing for generating data for each day has arrived. The management server 200 holds control at step S100 until it determines that the timing has arrived (NO in step S100), and when it determines that the timing has arrived (YES in step S100), it advances control to step S102. For example, if the monitoring system is set to generate the previous day's behavior information and correlation information at 1:00 a.m. each day, then at 1:00 a.m., control advances to step S102.

In step S102, the management server 200 identifies the time period when each resident was active in their room. The management server 200 may use location information acquired from an activity meter associated with each resident to identify the time period when each resident was located in their room as the time period when each resident was active in their room. The management server 200 may identify the time period when each resident was located in their room as the time period when each resident was active in their room, based on the time when an object identified as a resident was present in the image generated by the camera 105 in each room. The management server 200 may identify the time period when each resident was located in their room input by a staff member (such as staff members 810A and 810B in FIG. 1) as the time period when each resident was in their room as the time period when each resident was active in their room.

In step S104, the management server 200 uses the detection output from the sensor for the time period identified in step S102 to generate behavior information in the room for the day being processed (FIG. 6) and stores it in the storage device 220 (FIG. 5). In a monitoring system, the detection output from a sensor such as the activity meter 600 may be stored in the storage device 220 of the management server 200. The management server 200 may use the detection output stored in the storage device 220 to generate behavior information in the room for each day.

In step S106, the management server 200 uses the detection output from the sensor for a time period other than the time period identified in step S102 to generate outside-room activity information ( FIG. 9 ) for the day being processed, and stores it in the storage device 220 ( FIG. 5 ). The management server 200 may use the detection output stored in the storage device 220 to generate outside-room activity information for each day.

In step S108, the management server 200 acquires the target period for which related information is to be generated. The management server 200 stores the target period (one week, one month, etc.) for which related information is to be generated, which is specified by an administrator or the like within the monitoring system. The management server 200 may read out the specified period in step S108.

In step S110, the management server 200 uses the in-room behavior information and the out-of-room behavior information for each day of the period acquired in step S108 to derive a correlation for each exhaustive combination of the two items. For each combination, the management server 200 derives a function that approximates the relationship between the data as a correlation.

In step S112, the management server 200 stores the correlation derived in step S110 as correlation information (FIG. 10) in the storage device 220. Thereafter, the management server 200 ends the process in FIG. 12.

Figure 13 is a diagram showing an example of a combination of items for which a correlation has been derived. Figure 13 shows the results derived using 22 days' worth of behavioral information. In Figure 13, the vertical axis represents the value of the item "sleep time," the horizontal axis represents the value of the item "number of steps," and each point in the graph represents the value of the behavioral information for each day. Figure 13 also shows a straight line L1 that approximates the relationship between the items "sleep time" and "number of steps."

In the example of FIG. 13, the management server 200 derives a correlation between the item "sleep time" and the item "number of steps" that is approximated by a line L1. That is, in the example of FIG. 13, a relationship is derived in which "sleep time" increases as the "number of steps" increases, as shown by line L1.

Figure 14 is a diagram showing another example of a combination of items for which a correlation has been derived. As with Figure 13, Figure 14 shows the results derived using 22 days' worth of behavioral information. The management server 200 generates a line L2 that approximates the relationship between the item "walking speed" and the item "sitting time". In the example of Figure 14, as shown by line L2, a relationship is derived in which there is no significant change in walking speed even if the sitting time changes.

Figure 15 is a diagram showing yet another example of a combination of items for which a correlation has been derived. As with Figures 13 and 14, Figure 15 shows a result derived using 22 days' worth of behavioral information. The management server 200 generates a line L3 that approximates the relationship between the item "activity amount" and the item "activity time". In the example of Figure 15, as shown by line L3, a relationship is derived in which, in the range up to the activity time value VX, the activity amount increases as the activity time increases, and in the range after value VX, the activity amount decreases as the activity time increases.

Figure 16 is a diagram showing yet another example of a combination of items for which a correlation has been derived. As with Figures 13 to 15, Figure 16 shows results derived using 22 days' worth of behavioral information. The management server 200 generates a line L4 that approximates the relationship between the item "stopping" and the item "standing time". In the example of Figure 16, as shown by line L4, a relationship is derived in which standing time does not have a significant effect on stopping within the range up to the value VP of standing time, but in the range after value VP, stopping decreases as standing time increases.

In the example of FIG. 12, the management server 200 generates behavioral information and related information of the resident for the previous day at a specified time each day, but the timing of generating the behavioral information and related information is not limited to this. For example, the management server 200 may generate behavioral information and related information for each day once a week, once a month, or when instructed to do so by the administrator of the monitoring system.

In the example of FIG. 12, the management server 200 generates behavioral information and related information every day, but may generate only behavioral information each day and related information only on specified days.

In the present embodiment described above, information (related information) is generated for each resident regarding which items of outside-room behavioral information affect the behavioral information within the room and how. By referring to such information, the resident or staff can obtain knowledge regarding which items of outside-room behavioral information should be changed and how, if they wish to improve the behavioral information within a particular room.

For example, according to the related information generated with reference to FIG. 13 etc., the resident who is the subject of the related information can obtain the knowledge that if he/she wants to extend the amount of sleep in his/her room, it is preferable to increase the number of steps (outside the room). According to the related information generated with reference to FIG. 15 etc., the resident who is the subject of the related information can obtain the knowledge that if he/she wants to increase the amount of activity in his/her room, it is preferable to increase the amount of activity outside the room up to the value VX. When providing advice to the resident based on the knowledge, the staff may present the graph shown in FIG. 13 etc. itself.

Because a room is essentially a private space for a resident, it has been difficult to obtain objective information for adjusting the resident's behavior in the room. However, according to the present disclosure, information derived from the correlation between behavioral information inside the room and behavioral information outside the room is provided, making it possible to provide objective information for adjusting the resident's behavior in the room, which has been difficult to provide in the past, making it possible to adjust the resident's behavior in the room. As a result, the present disclosure can contribute to improving the quality of life of the resident in the room.

In addition, according to the related information generated with reference to FIG. 16 etc., it is possible to obtain the insight that, since residents who spend less time standing (inside their rooms) tend to spend more time standing (outside their rooms), it is advisable for the residents themselves or staff to take measures to encourage movement within the rooms (such as installing handrails or increasing the number of handrails) in order to promote participation in standing recreation.

In other words, according to the present disclosure, information derived from the correlation between behavioral information inside the room and behavioral information outside the room is provided, so that information based on behavior inside the room, which is a private space, can be provided as information for adjusting behavior outside the room. This makes it possible to provide information based on the behavior of the resident in the room, which was previously difficult to provide. As a result, the present disclosure can also contribute to improving the quality of life of the resident outside the room.

In addition, in this embodiment, correlations between items of behavioral information within the room and correlations between items of behavioral information outside the room can be derived. This can provide insight, such as the fact that in order to improve an item (e.g., degree of unsteadiness) that is assumed to be difficult for the resident to change directly, it is preferable to change (widen or narrow) the behavior of other items (e.g., range of activities). As a result, the present disclosure provides information for improving behavior in items that were difficult for the resident to change directly by changing behavior in other items, which can contribute to improving the quality of life of the resident.

The embodiments disclosed herein should be considered to be illustrative in all respects and not restrictive. The scope of the present invention is indicated by the claims, not by the above description, and is intended to include all modifications within the meaning and scope of the claims. Furthermore, the inventions described in the embodiments and each modified example are intended to be implemented, as far as possible, either alone or in combination.

200 management servers, 600 activity meters, T1, T2 trajectories.

Claims (14)

A behavioral information analysis method executed by an information processing device, comprising:
acquiring behavior information in a room as information on one or more types of behavior in the room assigned to the care recipient during a certain period of time by utilizing detection outputs during the certain period of time of one or more sensors that detect the state of the care recipient;
acquiring outside-room behavior information as information on one or more types of behavior outside the room during the certain period of time using detection outputs of the one or more sensors during the certain period of time;
deriving a correlation between types of one or more types of in-room activity information and one or more types of outside-room activity information;
The behavior information in the living room includes statistical values regarding behavior in the living room,
A behavioral information analysis method, wherein the statistical values include at least one of a range of movement, a time spent outside the bed, a number of times a given movement pattern is repeated, and a time when movement is stopped. A behavioral information analysis method executed by an information processing device, comprising:
acquiring behavior information in a room as information on one or more types of behavior in the room assigned to the care recipient during a certain period of time by utilizing detection outputs during the certain period of time of one or more sensors that detect the state of the care recipient;
acquiring outside-room behavior information as information on one or more types of behavior outside the room during the certain period of time using detection outputs of the one or more sensors during the certain period of time;
deriving a correlation between types of one or more types of in-room activity information and one or more types of outside-room activity information;
A behavioral information analysis method, wherein the behavioral information within the room includes information representing the nature of walking within the room. The behavioral information analysis method according to claim 2, wherein the information representing the nature of walking within the room includes at least one of walking speed, an area that strays from a frequently moving path, and a distance that strays from a frequently moving path. A behavioral information analysis method executed by an information processing device, comprising:
acquiring behavior information in a room as information on one or more types of behavior in the room assigned to the care recipient during a certain period of time by utilizing detection outputs during the certain period of time of one or more sensors that detect the state of the care recipient;
acquiring outside-room behavior information as information on one or more types of behavior outside the room during the certain period of time using detection outputs of the one or more sensors during the certain period of time;
deriving a correlation between types of one or more types of in-room activity information and one or more types of outside-room activity information;
The behavioral information analysis method, wherein the behavioral information outside the room includes the number of steps outside the room. The behavioral information analysis method according to any one of claims 1 to 4, wherein the one or more sensors include an activity meter worn by the care recipient. The behavioral information analysis method according to claim 5, wherein the activity meter has a location information detection function. The behavioral information analysis method according to any one of claims 1 to 6, wherein the one or more sensors include a camera that captures images of the room. The behavioral information analysis method according to any one of claims 1 to 7, wherein the behavioral information in the room includes sleeping time. The behavioral information analysis method according to any one of claims 2 to 8, wherein the behavioral information within the room includes statistical values regarding behavior in the room. The behavioral information analysis method according to claim 9, wherein the statistical values include at least one of the following: the range of movement, the time spent outside the bed, the number of times a given movement pattern is repeated, and the time when movement is stopped. The behavioral information analysis method according to any one of claims 1 to 10, wherein the behavioral information outside the room includes at least one of the time when the care recipient was outside the room and the time when the care recipient was in a given state outside the room. The behavioral information analysis method according to claim 11, wherein the given state includes at least one of a standing state, a sitting state, and a lying state. A program that, when executed by a processor of an information processing device, causes the information processing device to carry out the method according to any one of claims 1 to 12. A processor;
An information processing device comprising: a memory storing the program according to claim 13.

Images