JP7599124B2 - Fatigue estimation system, estimation device, and fatigue estimation method - Google Patents

Description

The present disclosure relates to a fatigue estimation system for estimating a subject's fatigue level, an estimation device used in the estimation system, and a fatigue estimation method.

In recent years, there have been many cases in which accumulated fatigue has led to poor health, injuries, accidents, and the like. In response to this, attention has been focused on technology that can prevent poor health, injuries, accidents, and the like by estimating the level of fatigue. For example, Patent Document 1 discloses a fatigue determination device as a fatigue estimation system for estimating the degree of fatigue, which determines the presence or absence of fatigue and the type of fatigue based on force measurement and bioelectrical impedance measurement.

JP 2017-023311 A

However, in the conventional fatigue assessment device exemplified in the above-mentioned Patent Document 1, the accuracy of the estimated fatigue level may not be sufficient. Therefore, the present disclosure provides a fatigue estimation system that estimates the fatigue level with higher accuracy.

A fatigue estimation system according to one aspect of the present disclosure is a fatigue estimation system that estimates a fatigue level of a subject who is partially hidden when viewed from an imaging device, and includes: an imaging device that captures an image including the subject and fixtures around the subject; an image acquisition unit that acquires the image from the imaging device; an image acquisition unit that acquires the image from the imaging device; a detection unit that detects the top surface of the fixture included in the acquired image; a posture estimation unit that estimates a posture of the subject, the posture estimation unit estimating a posture of a visible part of the subject that is not hidden when viewed from the imaging device based on the subject included in the image, and estimating a posture of a non-visible part of the subject that is hidden when viewed from the imaging device based on the detected top surface; and a fatigue estimation unit that estimates a fatigue level of the subject based on the estimated posture of the subject.

In addition, an estimation device according to one aspect of the present disclosure is an estimation device that estimates a fatigue level of a subject who is partially hidden when viewed from an imaging device, and includes an image acquisition unit that acquires an image including the subject and fixtures around the subject from the imaging device, a detection unit that detects the top surface of the fixtures included in the acquired image, a posture estimation unit that estimates the posture of the subject, the posture estimation unit estimating the posture of a visible part of the subject that is not hidden when viewed from the imaging device based on the subject included in the image, and estimating the posture of a non-visible part of the subject that is hidden when viewed from the imaging device based on the detected top surface, and a fatigue estimation unit that estimates the fatigue level of the subject based on the estimated posture of the subject.

Furthermore, a fatigue estimation method according to one aspect of the present disclosure is a fatigue estimation method for estimating a fatigue level of a subject who is partially hidden when viewed from an imaging device, which includes acquiring an image including the subject and furniture around the subject from the imaging device, detecting the top surface of the furniture included in the acquired image, estimating the posture of a visible part of the subject that is not hidden when viewed from the imaging device based on the subject included in the image, estimating the posture of a non-visible part of the subject that is hidden when viewed from the imaging device based on the detected top surface, and estimating the fatigue level of the subject based on the estimated posture of the subject.

A fatigue estimation system according to one embodiment of the present disclosure can estimate fatigue levels with greater accuracy.

FIG. 1A is a first diagram for explaining estimation of a fatigue level according to an embodiment. FIG. 1B is a second diagram for explaining estimation of a fatigue level according to the embodiment. FIG. 1C is a third diagram for explaining estimation of a fatigue level according to the embodiment. FIG. 2 is a block diagram illustrating a functional configuration of the fatigue estimation system according to the embodiment. FIG. 3A is a first diagram illustrating posture estimation according to the embodiment. FIG. 3B is a second diagram illustrating posture estimation according to the embodiment. FIG. 4A is a flowchart showing a method for estimating a fatigue level according to an embodiment. FIG. 4B is a sub-flowchart showing details of some steps according to an embodiment. FIG. 5A shows a subject standing still in posture A. FIG. 5B illustrates a subject standing still in posture B. FIG. 6A is a first diagram illustrating an estimated accumulation of a subject's fatigue level in the embodiment. FIG. 6B is a second diagram illustrating the estimated accumulation of fatigue level of a subject in the embodiment. FIG. 7 is a first diagram showing an example of displaying an estimation result according to the embodiment. FIG. 8 is a second diagram showing an example of displaying an estimation result according to the embodiment. FIG. 9 is a diagram for explaining posture estimation according to the modification of the embodiment.

The following describes the embodiments in detail with reference to the drawings. Note that the embodiments described below are all comprehensive or specific examples. The numerical values, shapes, materials, components, component placement and connection forms, steps, and order of steps shown in the following embodiments are merely examples and are not intended to limit the present disclosure. Furthermore, among the components in the following embodiments, components that are not described in an independent claim are described as optional components.

Note that each figure is a schematic diagram and is not necessarily a precise illustration. In addition, in each figure, the same reference numerals are used for substantially the same configurations, and duplicate explanations may be omitted or simplified.

(Embodiment)
[Fatigue estimation system]
The overall configuration of a fatigue estimation system according to an embodiment will be described below. Fig. 1A is a first diagram for explaining fatigue level estimation according to an embodiment. Fig. 1B is a second diagram for explaining fatigue level estimation according to an embodiment. Fig. 1C is a third diagram for explaining fatigue level estimation according to an embodiment.

In an embodiment, the fatigue estimation system 200 (see FIG. 2 described later) in the present disclosure is a system that estimates a fatigue level of a subject 11 using an image output by imaging the subject 11 using an imaging device 201. The imaging device 201 is not limited in form as long as it is a camera that images the subject 11 and outputs the image, and may be a fixed camera installed on a wall or ceiling of a building or the like as shown in FIG. 1A, or may be a camera mounted on a PC, smartphone, tablet terminal, or the like operated by the subject 11.

Here, the subject is seated on a chair 12 and performing work using a work object placed on a desk 13. In the fatigue estimation system 200 of the present disclosure, the fatigue level of the subject 11 is estimated based on the fatigue accumulated by taking a fixed, stationary posture, among the fatigue of the subject 11. In other words, the fatigue accumulated by the load on at least one of the muscles and joints and the worsening blood flow (hereinafter also referred to as a decrease in blood flow) due to the fixed posture is estimated. Therefore, the subject 11 is in a stationary posture in a sitting, lying or standing position for at least a certain period of time. The certain period is, for example, several tens of seconds or a few seconds, which is the minimum period during which fatigue can be estimated by the fatigue estimation system 200. Such a period is determined depending on the processing capacity of the imaging device 201 and the estimation device 100 (see FIG. 2 described later) that constitute the fatigue estimation system 200.

Examples of subjects 11 who assume such a stationary posture include desk workers in an office, drivers steering a moving vehicle, people performing strength training using a load in a stationary posture, residents of facilities such as hospitals, passengers and crew of an airplane, etc.

The image captured and output by the imaging device 201 is processed by the estimation device 100, and the posture of the subject 11 is estimated as shown in FIG. 1B. The estimated posture of the subject 11 is output as a rigid link model 11a, for example. Specifically, as shown in FIG. 1B, skeletons shown as straight lines are connected by joints shown by black dots, and the posture of the subject 11 can be reproduced by the positional relationship between the two skeletons connected by one joint. The posture is estimated by image recognition, and is output as the above-mentioned rigid link model 11a based on the positional relationship between the joints and skeletons.

By fitting the estimated rigid link model 11a to a musculoskeletal model 11b as shown in FIG. 1C, the load on at least one of the muscles and joints of each body part is calculated as an estimate in order to maintain the positional relationship according to the estimated posture for each body part of the muscles that pull the skeletons together and the joints that reversibly connect the positional relationship between the skeletons. Since the estimated load on at least one of the muscles and joints of each body part accumulates the longer the static posture is maintained, the degree of fatigue caused by the subject 11 maintaining the static posture is calculated by a calculation using the estimated load and the duration. In the following description, "at least one of the muscles and joints" is also expressed as "muscles and/or joints".

In addition, in this embodiment, in addition to the estimated values of the load on the muscles and/or joints, the fatigue level can be estimated based on an estimated value of the blood flow of the subject 11. In the following explanation, an example of estimating the fatigue level of the subject 11 using the estimated values of the load on the muscles and the load on the joints will be mainly described, but it is also possible to combine this with the estimated value of the blood flow to estimate the fatigue level of the subject 11 with higher accuracy. Furthermore, the fatigue level of the subject 11 can also be estimated using an estimated value of any one of the load on the muscles, the load on the joints, and the blood flow of the subject 11.

That is, the fatigue estimation system 200 estimates the posture of the subject 11, and then estimates at least one of the load on the muscles, the load on the joints, and the blood flow rate of the subject 11 based on the duration of the posture. The fatigue estimation system 200 estimates the fatigue level of the subject 11 based on at least one of the estimated values of the load on the muscles, the load on the joints, and the blood flow rate of the subject 11. Hereinafter, for simplification, the estimated value of the load may be simply expressed as the load or the estimated value. Furthermore, when the estimated value includes an estimated value of the blood flow rate, the load amount may be read as the blood flow rate, and a large load amount may be replaced with a decrease in the blood flow rate, and a small load amount may be replaced with an increase in the blood flow rate.

As described above, the blood flow rate is information for quantifying the blood flow that deteriorates when the subject 11 maintains a posture. The lower the blood flow rate, the worse the blood flow of the subject 11 is, and the blood flow rate can be used as an index of fatigue caused by the deterioration of blood flow. The blood flow rate may be obtained as an absolute value at the time of measurement, or may be obtained as a relative value between two different points in time. For example, the degree of deterioration of the blood flow of the subject 11 can be estimated based on the posture of the subject 11 and the relative values of the blood flow rate at two points in time, the start and end points of the posture. In addition, since there is a correlation between the posture of the subject 11, the duration of the posture, and the deterioration of blood flow, the blood flow rate of the subject may be estimated simply from the posture of the subject 11 and the duration of the posture.

In the following description, the above-mentioned musculoskeletal model 11b is used to estimate at least one of the load on muscles, the load on joints, and the blood flow rate from the posture of the subject 11. However, in addition to the above-mentioned musculoskeletal model 11b, a method using actual measurement data can also be applied as a method for estimating the load on muscles, the load on joints, and the blood flow rate from the posture. This actual measurement data is a database constructed by accumulating the actual measurement values of the load on muscles, the load on joints, and the blood flow rate measured for each posture in association with the posture. In this case, the fatigue estimation system 200 can input the estimated posture of the subject 11 into the database, and obtain the actual measurement values of the load on muscles, the load on joints, and the blood flow rate in the corresponding posture as output.

The actual measurement data may be constructed using actual measurement values for each individual, taking into account individual differences among the subjects 11, or the big data obtained from an unspecified number of subjects may be qualified and constructed to suit each subject 11 through analytical processing such as statistical analysis or machine learning.

Next, the functional configuration of the fatigue estimation system 200 in the present disclosure will be described with reference to Figure 2. Figure 2 is a block diagram showing the functional configuration of the fatigue estimation system in accordance with an embodiment.

As shown in FIG. 2, the fatigue estimation system 200 in the present disclosure includes an estimation device 100, an imaging device 201, a timing device 202, a pressure sensor 203, a reception device 204, a memory device 215, a height sensor 216, a display device 205, and a recovery device 206.

The estimation device 100 includes a first acquisition unit 101, a second acquisition unit 102, a third acquisition unit 103, a fourth acquisition unit 104, a fifth acquisition unit 115, a sixth acquisition unit 116, a posture estimation unit 105, a first calculation unit 106, a second calculation unit 107, a fatigue estimation unit 108 and an output unit 109.

The first acquisition unit 101 is a communication module that is connected to the imaging device 201 and acquires an image of the subject 11 from the imaging device 201. That is, the first acquisition unit 101 is an example of an acquisition unit. The first acquisition unit 101 also has a function of detecting furniture (e.g., chair 12 or desk 13) included in the acquired image and detecting the top surface of the furniture. That is, the first acquisition unit 101 is also an example of a detection unit that detects the top surface of the furniture included in the image. The connection between the first acquisition unit 101 and the imaging device 201 is made by wire or wirelessly, and there is no particular limitation on the method of communication made via the connection.

The second acquisition unit 102 is a communication module that is connected to the timing device 202 and acquires the time from the timing device 202. The connection between the second acquisition unit 102 and the timing device 202 is made by wire or wirelessly, and there is no particular limitation on the method of communication made via the connection.

The third acquisition unit 103 is a communication module that is connected to the pressure sensor 203 and acquires the pressure distribution from the pressure sensor 203. The connection between the third acquisition unit 103 and the pressure sensor 203 is made by wire or wirelessly, and there is no particular limitation on the method of communication made via the connection.

The fourth acquisition unit 104 is a communication module that is connected to the reception device 204 and acquires personal information from the reception device 204. The connection between the fourth acquisition unit 104 and the reception device 204 is made by wire or wirelessly, and there is no particular limitation on the method of communication made via the connection.

The fifth acquisition unit 115 is a communication module connected to the storage device 215 and acquires the length L (see FIG. 3B) of the lumbar skeleton 11m (see FIG. 3A) of the subject 11. That is, the first acquisition unit 101 is an example of an acquisition unit. The fifth acquisition unit 115 is an example of a length acquisition unit that acquires the length of the lumbar skeleton 11m. The fifth acquisition unit 115 acquires the length L of the lumbar skeleton 11m of the subject 11, which is stored in advance in the storage device 215, by accessing the storage device 215. For example, the fifth acquisition unit 115 transmits information about the subject 11 (identification information for identifying the subject 11 from others) to the storage device 215 as a query, and acquires the length L of the lumbar skeleton 11m of the subject 11 as a response result to the query. The length of the lumbar skeleton is one of the skeletons that connect joints, extending from the back joint 11l (see FIG. 3A) of the subject 11 and connecting to the lumbar joint 11n (see FIG. 3A). The fifth acquisition unit 115 may or may not be used depending on the extent of the invisible part 11c (see FIG. 3A) of the subject. In other words, the fifth acquisition unit 115 may not be necessary depending on which part of the subject 11 corresponds to the boundary between the visible part 11d (see FIG. 3A) of the subject 11 that is not hidden from the perspective of the imaging device 201 and the hidden invisible part 11c. In such a case, the fifth acquisition unit 115 may not be provided. In other words, the fifth acquisition unit 115 is not an essential component. The storage device 215 may also function as a storage device not shown in the drawings described below.

Furthermore, the fifth acquisition unit 115 acquires the height H2 (see FIG. 3B) from the seat surface to the lumbar joint 11n when the subject 11 is seated. This height H2 is affected by the subject 11's weight and the thickness of the buttocks involved in sitting, etc. For example, when information on the subject 11's weight, buttocks thickness, etc. is input into the storage device 215, the height H2 calculated from these numerical values is stored. The fifth acquisition unit 115 then transmits information on the subject 11 to the storage device 215 as a query, and acquires the height H2 of the subject 11 as a response result to the query.

The connection between the fifth acquisition unit 115 and the memory device 215 is made via a wired or wireless connection, and there are no particular limitations on the method of communication made via this connection.

The sixth acquisition unit 116 is a communication module that is connected to the height sensor 216 and acquires the height H1 (see FIG. 3B) of the seat of the chair 12 on which the subject 11 is seated. The height sensor 216 is attached to the chair 12 and detects and transmits the height H1 when the subject 11 is seated on the chair 12. Meanwhile, the sixth acquisition unit 116 receives the height H2 detected by the height sensor 216. The height H2, when combined with the height H1, matches the height of the waist joint 11n of the subject 11. In other words, the fifth acquisition unit 115 and the sixth acquisition unit 116 receive the height H2 and the height H1, respectively, and acquire the height of the waist joint 11n. Therefore, the fifth acquisition unit 115 and the sixth acquisition unit 116 together can be said to be an example of a height acquisition unit.

Alternatively, the height acquisition unit may be realized by a processing unit that acquires an image of the subject 11 in a seated state and calculates the height of the waist joint 11n of the subject 11 from the image. In this case, the image may be acquired by the imaging device 201, but the waist joint 11n may not appear in the image depending on the positional relationship between the imaging device 201 and the subject 11. In this case, the subject 11 may be guided in advance to move to a range that appears in the image and seated on the chair 12 within this range, so that the height of the waist joint 11n can be acquired from the image captured by the imaging device 201.

The connection between the sixth acquisition unit 116 and the height sensor 216 is made via a wired or wireless connection, and there are no particular limitations on the method of communication made via this connection.

The posture estimation unit 105 is a processing unit that is realized by executing a predetermined program using a processor and a memory. Through processing by the posture estimation unit 105, the posture of the subject 11 is estimated based on the image acquired by the first acquisition unit 101 and the pressure distribution acquired by the third acquisition unit 103.

The first calculation unit 106 is a processing unit that is realized by executing a predetermined program using a processor and a memory. Through processing by the first calculation unit 106, the load on each muscle and/or joint is calculated based on the estimated posture of the subject 11 and the personal information acquired by the fourth acquisition unit.

The second calculation unit 107 is a processing unit that is realized by executing a predetermined program using a processor and a memory. Through processing by the second calculation unit 107, the amount of recovery of fatigue in each muscle and/or joint is calculated based on the amount of change in the estimated change in the posture of the subject.

The fatigue estimation unit 108 is a processing unit that is realized by executing a predetermined program using a processor and a memory. The fatigue estimation unit 108 estimates the fatigue level of the subject 11 based on the duration of the estimated posture using the posture estimated by the posture estimation unit 105 and the time acquired by the second acquisition unit 102.

The output unit 109 is a communication module that is connected to the display device 205 and the recovery device 206, and outputs content based on the fatigue level estimation result by the estimation device 100 to the display device 205 and the recovery device 206. The connection between the output unit 109 and the display device 205 or the recovery device 206 is made by wire or wirelessly, and there is no particular limitation on the method of communication made through the connection.

As described above, the imaging device 201 is a device that captures an image of the subject 11 and outputs the image, and is realized by a camera. As the imaging device 201, an existing camera such as a security camera or a fixed camera in the space in which the fatigue estimation system 200 is applied may be used, or a dedicated camera may be newly installed. Such an imaging device 201 is an example of an information output device that outputs an image as information related to the position of the body parts of the subject 11. Therefore, the output information is an image, and is information including the positional relationship of the body parts of the subject 11 on the projected imaging element.

The timing device 202 is a device that measures time, and is realized by a clock. The timing device 202 can transmit time to the connected second acquisition unit 102. Here, the time measured by the timing device 202 may be an absolute time, or may be the elapsed time from a relative starting point. The timing device 202 may be realized in any form as long as it can measure the time between the time when the subject 11's stillness is detected and the time when the fatigue level is estimated (i.e., the duration of the still posture).

The pressure sensor 203 is a sensor having a detection surface, and measures the pressure applied to each of the unit detection surfaces that divide the detection surface into one or more. The pressure sensor 203 measures the pressure for each unit detection surface in this manner, and outputs the pressure distribution on the detection surface. The pressure sensor 203 is provided so that the subject 11 is positioned on the detection surface.

For example, the pressure sensor 203 is provided on the seat and backrest of a chair on which the subject 11 sits. Also, for example, the pressure sensor 203 may have a marker on its detection surface, and guide the subject 11 onto the detection surface by displaying, for example, "Please sit on the marker." Also, by guiding the subject 11 onto the detection surface of the pressure sensor 203 provided on a portion of the floor in this manner, the pressure sensor 203 may output the pressure distribution of the subject 11 on the floor. Note that since the pressure distribution is used for the purpose of improving the accuracy of the estimation of the fatigue level, the fatigue estimation system 200 may be realized without the pressure sensor 203 if sufficient accuracy is ensured.

The reception device 204 is a user interface that receives input of personal information of the subject 11, and is realized by an input device such as a touch panel or a keyboard. The personal information includes at least one of age, sex, height, weight, muscle mass, stress level, body fat percentage, and exercise proficiency. The age of the subject 11 may be a specific numerical value, may be an age band divided in 10-year intervals such as teens, twenties, and thirties, may be a two-band age band with a predetermined age boundary such as 59 years or younger or 60 years or older, or may be something else.

The gender of the subject 11 is selected from either male or female, whichever is appropriate for the subject 11. The height and weight are accepted as the numerical values of the height and weight of the subject 11, respectively. The muscle mass is accepted as the muscle composition ratio of the subject 11 measured using a body composition scale or the like. The stress level of the subject 11 is selected by the subject 11 himself from options such as high, medium, and low as the subjective level of stress felt by the subject 11.

In addition, the body fat percentage of subject 11 is the ratio of the weight of body fat to the body weight of subject 11, and is expressed, for example, as a percentage.

In addition, the subject's 11 exercise proficiency may be quantified by the score the subject 11 gets when performing a specified exercise program, or by the state of the exercise that the subject 11 usually engages in. In the former case, it is quantified, for example, by the time it takes to perform 10 back exercises, the time it takes to run 50 meters, or the distance of a long throw. In the latter case, it is quantified, for example, by how many days a week the subject exercises, or how many hours the subject exercises. Since the personal information is used for the purpose of improving the accuracy of the fatigue level estimation, the fatigue estimation system 200 may be realized without the reception device 204 if sufficient accuracy is ensured.

As described above, the storage device 215 is a device capable of storing information. The storage device 215 is realized by a semiconductor memory, an optical disk, a magnetic disk, or the like.

As described above, the height sensor 216 is a sensor for detecting the height of an object. Here, the height sensor 216 is configured to detect the height of the seat of the chair 12.

The display device 205 is a device for displaying the content based on the fatigue level estimation result output by the output unit 109. The display device 205 displays an image showing the content based on the fatigue level estimation result, for example, by a display panel such as a liquid crystal panel or an organic EL (Electro Luminescence) panel. The content displayed by the display device 205 will be described later. Furthermore, when the fatigue estimation system 200 is configured to only reduce the fatigue level of the subject 11 using the recovery device 206, it is sufficient to include only the recovery device 206, and the display device 205 is not required.

The recovery device 206 is a device that reduces the fatigue level of the subject 11 by promoting blood circulation in the subject 11. Specifically, the recovery device 206 actively changes the posture of the seated subject 11 by applying voltage, pressurizing, vibrating, or heating, or by changing the arrangement of each part of the chair 12 using a mechanism provided in the chair 12. In this way, the recovery device 206 changes the load on at least one of the muscles and joints of the subject 11, and also promotes blood circulation. In terms of blood flow, the promotion of blood circulation in this way reduces the effect of poor blood flow due to the subject 11 being in a stationary posture, and the fatigue level is restored. The recovery device 206 is attached to or contacted in advance with an appropriate body part of the subject 11 depending on the configuration of the device.

When promoting blood circulation in subject 11 by heating, the entire space around subject 11 is heated, and in such a case, it is not necessary for the device to be attached to or in contact with an appropriate body part of subject 11. Furthermore, when fatigue estimation system 200 is configured only to display the fatigue level estimation result to subject 11, it is sufficient to include only display device 205, and recovery device 206 is not required.

Here, the visible part 11d and the non-visible part 11c of the subject 11 will be described with reference to Figures 3A and 3B. Figure 3A is a first diagram for describing posture estimation according to the embodiment. Figure 3B is a second diagram for describing posture estimation according to the embodiment.

3A and 3B show subject 11 seated in chair 12 and working with a work object (not shown) placed on desk 13. 3A and 3B show a plan view of subject 11 from the left and right directions of subject 11 (directions perpendicular to the plane on which subject 11, chair 12, and desk 13 are arranged).

As shown in the figure, depending on the positional relationship between the subject 11, the desk 13, and the imaging device 201, a part of the subject 11 (non-visible part 11c) is located behind the desk 13 as seen from the imaging device 201, and it is difficult to estimate the posture of such non-visible part 11c in the image captured by the imaging device 201. On the other hand, in estimating the fatigue level of the subject 11, the angle 11x between the lumbar skeleton 11m and the femoral skeleton 11o is an important part that determines the posture of the trunk part. However, when the subject 11 uses the desk 13, the femoral skeleton 11o is often included in the non-visible area, and there are many situations in which it is difficult to estimate the angle 11x.

The inventors of the present disclosure have found that even in such a case, it is highly likely that the thigh skeleton 11o forms a predetermined angle with the horizontal plane according to a certain rule, and therefore it is possible to estimate the extension direction of the thigh skeleton 11o from the end of the visible part 11d on the side of the non-visible part 11c. The above-mentioned certain rule means, for example, that when the subject 11 is in a sitting position, the extension direction of the thigh skeleton 11o is close to parallel to the horizontal plane (the predetermined angle is 0 degrees), that is, the predetermined angle is within the range of -10 degrees to 10 degrees. Also, the certain rule means, for example, that when the subject 11 is in an upright position, the extension direction of the thigh skeleton 11o is close to perpendicular to the horizontal plane (the predetermined angle is 90 degrees), that is, the predetermined angle is within the range of 80 degrees to 100 degrees.

Furthermore, the certain rule is, for example, that when the subject 11 is in a supine position, the direction in which the femoral skeleton 11o extends is close to parallel to the horizontal plane (the specified angle is 0 degrees), that is, the specified angle is within the range of -10 degrees to 10 degrees. Note that the above angle range for the specified angle is one example, and a wider angle range may be applied in accordance with the posture habits of the subject 11. Furthermore, there is no directionality in such relative angle relationships, and the above 0 degrees is the same as 180 degrees. Similarly, the above 90 degrees is the same as 270 degrees. In other words, in this explanation, adding or subtracting a multiple of 180 degrees to the specified angle will still be treated as the same as the specified angle.

In this description, the thigh skeleton 11o is used as an example, but if the skeleton can determine a predetermined angle with respect to the horizontal plane according to a certain rule, it is possible to apply the present invention to estimate the posture of the invisible part 11c. In other words, the subject of posture estimation here is not limited to the thigh skeleton 11o.

In addition, in order to detect a horizontal plane from an image, it is usually necessary to use the top surface of a furniture such as a desk 13 to detect the horizontal plane, and based on the degree of deformation of the desk top surface 13a in the image, it is possible to efficiently detect the horizontal plane in the image as a relative direction to the imaging direction of the imaging device 201. For example, the rectangular top surface becomes a right-angled rectangle as it approaches a direction perpendicular to the imaging direction, and becomes a trapezoid with a large difference in length between the upper and lower bases as it approaches a direction parallel to the imaging direction. The furniture used to detect the horizontal plane may be any furniture that is around the subject 11. In other words, furniture other than the desk 13 may be used as long as it is included in the image together with the subject 11. For example, if a storage unit or the like is present near the subject 11, the top surface of the storage unit can be detected as the top surface and used as the horizontal plane.

Using the above, we will explain the estimation of the posture of the subject 11 including the visible part 11d and the invisible part 11c shown in Figures 3A and 3B. First, in Figure 3A, the invisible part 11c includes the thigh skeleton 11o and the joints and skeletons further towards the toes, as indicated by the dashed lines and open circles included in the rigid link model 11a in the figure. The visible part 11d includes the waist joint 11n and the joints and skeletons further towards the head, as indicated by the solid lines and filled circles included in the rigid link model 11a in the figure.

In this example, if the orientation of the non-visible part 11c is estimated so that the thigh skeleton 11o extends from the position of the waist joint so as to be parallel to the horizontal plane (dashed two-dot line) estimated from the desk surface 13a, it is possible to easily estimate the angle 11x.

3B, the non-visible portion 11c includes the lumbar vertebrae skeleton 11m, the lumbar joint 11n, the thigh skeleton 11o, and the joints and skeletons further to the toes. The visible portion 11d includes the back joint 11l included in the rigid link model 11a in the figure, and the joints and skeletons further to the head.

In this example, first, it is estimated from the position of the back joint that there is a lumbar joint 11n that matches on a sphere with a radius of length L centered on the back joint 11l, which is within the movable range of the length L of the lumbar skeleton 11m acquired by the fifth acquisition unit 115, and on a circumference that intersects with the height plane of the height (H1+H2) of the lumbar joint acquired by the fifth acquisition unit 115 and the sixth acquisition unit 116. If there are multiple candidates for the position of the estimated lumbar joint 11n, one of them may be selected. As a method of such selection, for example, several past postures of the subject 11 may be stored, and the above selection may be made based on the tendency of the possible postures. Then, if the posture of the invisible part 11c is estimated so that the femoral skeleton 11o extends from the estimated position of the lumbar joint 11n so as to be parallel to the horizontal plane (two-dot chain line) estimated from the desk surface 13a, it becomes possible to easily estimate the angle 11x.

As described above, the posture of the non-visible part 11c is estimated only for a few parts that can be estimated. Other parts (such as the knee joint) may be ignored or may be estimated using a different method.

[Action]
Next, the estimation of the fatigue level of the subject 11 using the fatigue estimation system 200 according to the embodiment will be described with reference to Fig. 4A to Fig. 6B. Fig. 4A is a flowchart showing a method for estimating a fatigue level according to the embodiment. Fig. 4B is a sub-flowchart showing details of some steps according to the embodiment.

The fatigue estimation system 200 first acquires personal information of the subject 11 (step S101). The personal information is acquired by the subject 11 himself/herself or an administrator who manages the subject 11's fatigue level by inputting it into the reception device 204. The input personal information of the subject 11 is stored in a storage device or the like (not shown) and is read out and used when estimating the fatigue level.

The fatigue estimation system 200 detects the subject 11 using the imaging device 201 (step S102). The subject 11 is detected by determining whether or not the subject 11 has entered the angle of view of the camera, which is the imaging device 201. Note that the subject 11 may be a specific subject 11, or a person who has entered the angle of view of the camera from an unspecified number of people may become the subject 11. When the subject 11 is selected from an unspecified number of people, input of personal information may be omitted. When detecting a specific subject 11, a step of identifying the subject 11 by image recognition or the like is added.

In this embodiment, an example is described in which the subject 11 himself/herself inputs personal information, grasps the detection area of the imaging device 201, and enters the detection area, whereby the fatigue level is estimated. Therefore, image recognition or the like is not required, and the fatigue level is estimated taking into account the personal information.

If the fatigue estimation system 200 determines that the subject 11 has not been detected (No in step S102), it repeats step S102 until the subject 11 is detected. On the other hand, if the subject 11 is detected (Yes in step S102), the image output by the imaging device 201 is acquired by the first acquisition unit 101 (step S103, an example of an acquisition step). Here, if it is detected in the acquired image that the subject 11 is stationary (in a stationary posture) (step S104), the posture of the subject 11 is estimated in the estimation device 100. Specifically, first, the third acquisition unit 103 acquires the pressure distribution applied to the detection surface from the pressure sensor 203 (step S105).

The posture estimation unit 105 estimates the posture of the subject 11 based on the acquired image and pressure distribution (posture estimation step S106). Here, the posture estimation step S106 is executed according to the sub-flowchart shown in FIG. 4B. First, the first acquisition unit 101 detects the furniture (here, the desk 13) in the acquired image and detects its top surface (desk top surface 13a) (step S106a). This makes it possible to estimate the direction parallel to the horizontal plane in the image. Next, the posture estimation unit 105 estimates the posture of the visible part 11d based on the subject included in the image (step S106b). As a result, the positions of the joints and skeleton included in the visible part 11d are estimated.

Next, the posture estimation unit 105 estimates the posture of the non-visible part 11c based on the detected top surface (step S106c). Here, for example, the position of the thigh skeleton 11o is estimated. Then, the posture estimation unit 105 corrects the estimated posture (the posture of the visible part 11d and the non-visible part 11c) based on the pressure distribution acquired by the third acquisition unit 103 (step S106d).

Correction of posture based on pressure distribution is performed, for example, as follows. When biased pressure is applied, the pressure distribution is used to correct the estimated posture so that the bias is formed. Next, the first calculation unit 106 calculates the load on each muscle and/or joint of the subject 11 from the posture estimation result. At this time, the load is corrected and calculated using personal information acquired in advance (step S107). Note that the estimation of the posture of the subject 11 has been explained using FIG. 1B, and the calculation of the load has been explained using FIG. 1C, so a detailed explanation will be omitted.

When correcting the load amount using personal information, for example, the load amount is decreased the closer the age of subject 11 is to the peak age of muscle development, and increased the further the age is from that peak age. Such peak values may be based on the gender of subject 11. Furthermore, the load amount may be decreased if subject 11 is male, and increased if subject 11 is female. Furthermore, the load amount may be decreased the smaller the height and weight of subject 11 are, and increased the larger the height and weight are.

In addition, the load may be set so that the greater the muscle mass of subject 11 is in the composition ratio, the less the load, and the smaller the muscle mass is in the composition ratio, the more the load. In addition, the lower the stress level of subject 11 is, the less the load, and the higher the stress level, the more the load. In addition, the higher the body fat percentage of subject 11 is, the more the load, and the lower the body fat percentage, the less the load. In addition, the higher the exercise proficiency of subject 11 is, the less the load, and the lower the exercise proficiency, the more the load.

Here, the duration of the stationary posture of the subject 11 is measured based on the time acquired by the second acquisition unit 102 (step S108). The fatigue estimation unit 108 adds the load calculated above each unit time of the duration, and estimates the fatigue level of the subject 11 at this point in time (fatigue estimation step S109). The processing of steps S108 and fatigue estimation step S109 is continued until the stationary state of the subject 11 is released. Specifically, whether the stationary state has been released is determined based on whether the posture estimated by the posture estimation unit 105 has been changed from a certain stationary posture (step S110).

If it is not determined that the stationary state has been released (No in step S110), the process returns to step S108, measures the duration, and proceeds to fatigue estimation step S109, where the load is added to accumulate the fatigue level of the subject 11 as long as the stationary posture continues. In other words, the fatigue estimation unit 108 repeats steps S108 and fatigue estimation step S109 to estimate the fatigue level of the subject 11 using an increasing function of the fatigue level having a slope corresponding to the calculated load level with respect to the duration. Therefore, the greater the calculated load level, the greater the increase in the fatigue level of the subject 11 per unit time. In this accumulation of fatigue level, the fatigue level of the subject 11 is initialized (set to fatigue level 0) at the start of the stationary posture, which is the starting point.

On the other hand, if it is determined that the stationary state has been released (Yes in step S110), the posture estimation unit 105 calculates the amount of change in posture from the original stationary posture to the changed current posture. The amount of change in posture is calculated for each muscle and/or joint, similar to the load amount described above. When posture changes in this way, the load on at least one of the muscles and joints changes, and in terms of blood flow, the worsening blood flow is temporarily alleviated, and the fatigue level of the subject 11 begins to recover. The fatigue level reduced by recovery is related to the amount of change in posture. Accordingly, the second calculation unit 107 calculates the amount of recovery, which is the degree of recovery of fatigue level, based on the amount of change in posture (step S111).

Based on the time acquired by the second acquisition unit 102, a change time, which is the time during which the change in posture of the subject 11 continues, is measured (step S112). The relationship between the recovery amount and the change time is similar to the relationship between the load amount and the duration, and the recovery amount of the subject 11 is accumulated as long as the change in posture continues. In other words, when the posture of the subject 11 changes in this way, the fatigue estimation unit 108 estimates the fatigue level of the subject 11 by subtracting the recovery amount every unit time (step S113).

The processing of steps S111, S112, and S113 is continued until the posture of the subject 11 becomes stationary. Specifically, whether or not the posture estimated by the posture estimation unit 105 is a certain stationary posture is determined based on whether or not the subject 11 is detected to be stationary (step S114). If the subject 11 is not detected to be stationary (No in step S114), the process returns to step S111, calculates the amount of recovery, proceeds to step S112, measures the change time, proceeds to step S113, and subtracts the amount of recovery, thereby accumulating the fatigue level of the subject 11 so that it is recovered as long as the posture change continues.

In other words, the fatigue estimation unit 108 repeats steps S111, S112, and S113 to estimate the fatigue level of the subject 11 using a fatigue level decreasing function having a slope corresponding to the calculated recovery amount with respect to the change time. Since the recovery amount of the fatigue level depends on the amount of change in posture, the greater the amount of change in posture, the greater the decrease in the fatigue level of the subject 11 per unit time.

On the other hand, if the subject 11 is detected to be stationary (Yes in step S114), the process returns to step S105, and the posture and fatigue level are estimated again for the new stationary posture. In this way, the fatigue estimation system 200 calculates the fatigue level of the subject 11 based on the image and taking into account the duration of the stationary posture, so that the fatigue level of the subject 11 can be estimated with less burden on the subject 11 and with higher accuracy.

The above will be explained in more detail using Figures 5A to 6B. Figure 5A is a diagram showing a subject standing still in posture A. Figure 5B is a diagram showing a subject standing still in posture B.

The subject 11 shown in Figures 5A and 5B is in a static posture, seated in a chair 12, similar to that shown in Figure 1A. Note that in Figures 5A and 5B, a table, PC, etc., which are not shown, are actually present, but only the subject 11 and chair 12 are shown here. The static posture of subject 11 shown in Figure 5A is posture A, which places a relatively heavy load on the shoulders. On the other hand, the static posture of subject 11 shown in Figure 5B is posture B, which places a relatively light load on the shoulders.

The fatigue level estimated for the subject 11 resting in such posture A or posture B is accumulated as shown in Figures 6A and 6B. Figure 6A is a first diagram explaining the accumulation of the subject's estimated fatigue level according to the embodiment. Also, Figure 6B is a second diagram explaining the accumulation of the subject's estimated fatigue level according to the embodiment.

As shown in Figure 6A, when the subject 11 remains stationary in posture A shown in Figure 5A or posture B shown in Figure 5B, the fatigue level of the subject 11 is expressed by a linear function whose slope is the amount of load calculated from the posture.

As described above, posture A is a posture that imposes a greater load on the subject 11 than posture B. Therefore, for example, in a certain muscle of the subject 11 (here, the muscle related to shoulder movement), the load on posture A (the slope of the straight line in posture A) is greater than the load on posture B (the slope of the straight line in posture B). For this reason, in posture A, subject 11 accumulates (accumulates) a greater degree of fatigue in a shorter period of time than when he or she is stationary in posture B.

On the other hand, as shown in Figure 6B, when the posture of subject 11 changes from posture A shown in Figure 5A to posture B shown in Figure 5B, the fatigue level of subject 11 is expressed by a function that combines a linear function whose slope is the amount of load calculated from the posture and a linear function whose slope is the amount of change in posture.

Therefore, for example, while subject 11 is stationary in posture A, the fatigue level of subject 11 is estimated as an accumulation (addition) of fatigue level by an increasing function with a positive slope corresponding to the load of posture A, as in FIG. 6A, and the accumulation (addition) turns to recovery (decrease) at the change point where subject 11 starts to change his posture. Subject 11's fatigue level recovers (decreases) by an amount shown as the change width in the figure during the period when the change in posture continues, shown as the change time in the figure, by a decreasing function with a negative slope corresponding to the amount of change in posture. After the change point where subject 11's posture stops again in posture B, subject 11's fatigue level is estimated as an accumulation (addition) of fatigue level by an increasing function with a positive slope corresponding to the load of posture B.

In this way, the fatigue estimation system 200 in this embodiment estimates the fatigue level of the subject 11, reflecting accumulation and recovery in response to the subject 11's stillness and changes in posture.

Next, an example of the output of the output unit 109 based on the estimated fatigue level will be described. FIG. 7 is a first diagram showing an example of the display of the estimation result according to the embodiment. FIG. 8 is a second diagram showing an example of the display of the estimation result according to the embodiment.

As shown in Figures 7 and 8, in the fatigue estimation system 200, the estimated fatigue level of the subject 11 can be displayed and fed back using the display device 205. Specifically, as shown in Figure 7, by visualizing the fatigue level of the subject 11, it is possible to visually grasp how tired the subject 11 is. In the figure, a doll resembling the subject 11 and the fatigue levels of the subject 11's shoulders, back, and key parts are displayed together by the display device 205. To make it easier for the subject 11 to intuitively grasp the fatigue level, the fatigue level of the shoulders is shown as "stiff shoulder level," the fatigue level of the back as "back pain level," and the fatigue level of the lower back as "lower back pain level."

Here, in the display in the figure, the fatigue levels of three parts of the subject 11 are displayed all at once, but the fatigue levels of these three parts are estimated from an image captured at one time. In other words, the estimation device 100 estimates the fatigue levels of the muscles and/or joints in each of multiple body parts including the first part (e.g., shoulders), second part (e.g., back), and third part (e.g., waist) of the subject 11 from one posture of the subject 11. Therefore, even if the posture of the subject 11 is constant, the fatigue levels accumulated in the muscles and/or joints differ for each body part, but the fatigue estimation system 200 can estimate such different fatigue levels simultaneously and individually.

1C, in this embodiment, the load is calculated for each muscle and/or joint of the subject 11, and therefore, if there are no limitations on processing resources, the fatigue level of each muscle and/or joint can be estimated. Therefore, there is no limit to the number of body parts whose fatigue level is estimated from an image captured at one time, and it may be one, two, four or more.

The estimation device 100 calculates the load amount for each of a plurality of body parts, and in one posture of the subject 11, it is possible to estimate the fatigue level of a first part (the above-mentioned shoulder stiffness level) based on the load amount calculated for the first part, the fatigue level of a second part (the above-mentioned back pain level) based on the load amount calculated for the second part, and the fatigue level of a third part (the above-mentioned lower back pain level) based on the load amount calculated for the third part.

In the example shown in the figure, the degree of stiff shoulders is estimated from the load on the trapezius muscle, the degree of back pain is estimated from the fatigue level of the latissimus dorsi muscle, and the degree of lower back pain is estimated from the load on the lumbar paraspinal muscles. In this way, one fatigue level may be estimated from the load on one muscle and/or joint, but one fatigue level may also be estimated from the combined load on multiple muscles and/or joints. For example, the degree of stiff shoulders (i.e., one fatigue level of the shoulder) may be estimated from the average value of the load on the trapezius muscle, levator scapulae muscle, rhomboid muscle, and deltoid muscle. In addition, in estimating the fatigue level, a more realistic estimation of the fatigue level may be performed by weighting the load on the muscle and/or joint that has a particularly large effect on the fatigue level of the body part in question, rather than using a simple average value.

The fatigue level estimated in this manner may be shown as a relative position on a reference meter with a minimum value of 0 and a maximum value of 100, as shown in the figure. Here, a reference value is set at a predetermined position on the reference meter. Such a reference value is set to the relative position (or around it, etc.) of the fatigue level at which subjective symptoms such as pain may occur in a typical subject 11, which has been quantified in advance by epidemiological surveys, etc. Therefore, the reference value may be set to a different value depending on the fatigue level of each body part.

Furthermore, when the estimated fatigue level of the subject 11 reaches a reference value, the display device 205 may display a warning to the subject 11 as an estimated result. The reference value here is an example of a first threshold value. In the figure, as an example of such a warning, "The degree of stiff shoulders has exceeded the reference value," is shown at the bottom of the display device 205. In connection with such a warning, the display device 205 may also display a specific method of dealing with the situation, such as "We recommend taking a break," as also shown in the figure.

Also, as shown in FIG. 8, when the estimated fatigue level of the subject 11 reaches a reference value, the display device 205 may display to the subject 11 a recommended posture that places less strain on the body part that has reached the reference value than the currently estimated posture of the subject 11. The reference value here is an example of a second threshold value, and may be the same as or different from the first threshold value. The displayed recommended posture may be accompanied by specific points to note, such as "lean your weight on the back of the chair" and "sit deep into the seat", along with a doll taking that posture.

In addition to the above-mentioned configuration in which the estimation result is displayed to the subject 11 to encourage the subject 11 to deal with the accumulated fatigue level, a configuration in which the fatigue estimation system 200 actively recovers the fatigue level of the subject 11 can also be considered. Specifically, the fatigue level of the subject 11 is recovered by the operation of the recovery device 206 shown in FIG. 2. The specific configuration of the recovery device 206 is as described above, so an explanation is omitted. When the estimated fatigue level of the subject 11 reaches a reference value, the recovery device 206 operates to change the load on at least one of the muscles and joints of the subject 11 and promote blood circulation to reduce the subject's fatigue level. The reference value here is an example of a third threshold value, and may be the same as or different from either the first threshold value or the second threshold value.

[Effects, etc.]
As described above, the fatigue estimation system 200 in the first aspect of the present embodiment is a fatigue estimation system 200 that estimates a fatigue level of a subject 11 who is partially hidden when viewed from an imaging device 201, and includes the imaging device 201 that captures an image including the subject 11 and furniture (such as the desk 13) around the subject 11, a first acquisition unit 101 (hereinafter, the image acquisition unit) that acquires an image from the imaging device 201, and a detection unit (for example, having as one of its functions a detection unit that detects the top surface of the furniture (such as the desk top surface 13a) included in the acquired image). and included in the first acquisition unit 101), a posture estimation unit 105 that estimates the posture of the subject 11, the posture estimation unit 105 estimating the posture of the subject 11, the posture estimation unit 105 estimating the posture of the visible part 11d of the subject 11 that is not hidden when viewed from the imaging device 201 based on the subject 11 included in the image, and estimating the posture of the non-visible part 11c of the subject 11 that is hidden when viewed from the imaging device 201 based on the detected top surface, and a fatigue estimation unit 108 that estimates the fatigue level of the subject 11 based on the estimated posture of the subject 11.

Such a fatigue estimation system 200 can estimate the posture of the non-visible part 11c based on the top surface of the fixture. Therefore, compared to a case where the non-visible part 11c exists and the fatigue level of the non-visible part cannot be estimated, the fatigue level of the subject 11 can be estimated based on the estimated posture of the non-visible part 11c, and therefore the fatigue level can be estimated with higher accuracy.

Also, for example, in the second aspect of this embodiment, the visible part 11d includes the waist joint 11n of the subject 11, the non-visible part 11c includes the thigh skeleton 11o of the subject 11, which is a skeleton extending from the waist joint 11n, and the posture estimation unit 105 estimates the extension direction of the thigh skeleton 11o, which extends in a direction forming a predetermined angle with respect to the top surface, from the position of the waist joint 11n included in the estimated posture of the visible part 11d, in the fatigue estimation system described in the first aspect.

According to this, when the visible portion 11d includes the waist joint 11n of the subject 11 and the non-visible portion 11c includes the thigh skeleton 11o of the subject 11, which is a skeleton extending from the waist joint 11n, the fatigue level of the subject 11 can be estimated based on the estimated posture of the thigh skeleton 11o, thereby making it possible to estimate the fatigue level with greater accuracy.

Also, for example, in the third aspect of this embodiment, the visible portion 11d includes the back joint 11l of the subject 11, and the invisible portion 11c includes the lumbar joint 11n of the subject 11, which is connected to the back joint 11l via the lumbar skeleton 11m of the subject 11, which is a skeleton extending from the back joint 11l, and the femoral skeleton 11o of the subject 11, which is a skeleton extending from the lumbar joint 11n, and the fatigue estimation system 200 further includes a fifth acquisition unit 115 (hereinafter, the length acquisition unit) that acquires the length of the lumbar skeleton 11m, and a fifth acquisition unit 116 that acquires the length of the lumbar joint 11n. This is a fatigue estimation system described in the first aspect, which includes a fifth acquisition unit 115 and a sixth acquisition unit 116 (hereinafter referred to as the height acquisition units) that acquire height, and the posture estimation unit 105 estimates the position of the lumbar joint 11n that is within the range of the length of the acquired lumbar skeleton 11m and matches the height of the acquired lumbar joint 11n from the position of the back joint 11l included in the estimated posture of the visible part 11d, and estimates the extension direction of the femoral skeleton 11o that extends in a direction forming a predetermined angle with respect to the top surface from the estimated position of the lumbar joint 11n.

According to this, when the visible portion 11d includes the back joint 11l of the subject 11 and the non-visible portion 11c includes the lumbar joint 11n of the subject 11 connected to the back joint 11l via the lumbar skeleton 11m of the subject 11, which is a skeleton extending from the back joint 11l, and the femoral skeleton 11o of the subject 11, which is a skeleton extending from the lumbar joint 11n, the fatigue level of the subject 11 can be estimated based on the estimated posture of the lumbar joint 11n and the femoral skeleton 11o, and therefore the fatigue level can be estimated with higher accuracy.

Also, for example, in a fourth aspect of this embodiment, the fatigue estimation system is as described in the second or third aspect, in which when the subject 11 is in a standing position, the specified angle is an angle within the range of 80 degrees to 100 degrees.

This makes it possible to estimate the posture of the non-visible part 11c of the subject 11 in a standing position, which extends in a direction at a predetermined angle within the range of 80 degrees to 100 degrees relative to the top surface.

Also, for example, in a fifth aspect of this embodiment, the fatigue estimation system is as described in the fourth aspect, in which when the subject 11 is in a standing position, the specified angle is 90 degrees.

This makes it possible to estimate the posture of the non-visible part 11c, which extends at 90 degrees to the top surface, of a subject 11 in a standing position.

Also, for example, in a sixth aspect of this embodiment, the fatigue estimation system is described in either the second or third aspect, in which, when the subject 11 is in a sitting position, the specified angle is an angle within the range of -10 degrees to 10 degrees.

This makes it possible to estimate the posture of the non-visible part 11c of a seated subject 11, which extends in a direction at a predetermined angle within the range of -10 degrees to 10 degrees relative to the top surface.

Also, for example, in the seventh aspect of this embodiment, the fatigue estimation system is as described in the sixth aspect, in which when the subject 11 is in a sitting position, the specified angle is 0 degrees.

This makes it possible to estimate the posture of the non-visible part 11c, which extends in a direction of 0 degrees relative to the top surface, of a seated subject 11.

Also, for example, in an eighth aspect of this embodiment, the fixture is a desk 13 used by the subject 11, and the top surface is the desk top surface 13a of the desk 13, which is a fatigue estimation system described in any one of the first to seventh aspects.

This makes it possible to estimate the posture of the non-visible part 11c by using the desk top surface 13a as the top surface of the desk 13 as furniture.

Also, for example, in a ninth aspect of this embodiment, the non-visible portion 11c is hidden by furniture when viewed from the imaging device 201, in a fatigue estimation system described in any one of the first to eighth aspects.

This makes it possible to estimate the posture of the invisible part 11c of the subject 11 hidden by a piece of furniture using the top surface of the furniture.

The system may also include, for example, an information output device (e.g., an imaging device 201) that outputs information regarding the positions of body parts of the subject 11, and an estimation device 100 that estimates the posture of the subject 11 based on the information (e.g., an image) output by the information output device, and estimates the fatigue level of the subject 11 based on the estimated posture and the duration of the posture.

Also, for example, the information output device may be an imaging device 201 that captures an image of the subject 11 and outputs the image as information regarding the position of a body part, and the estimation device 100 may estimate the posture of the subject 11 based on the image output by the imaging device 201.

Such a fatigue estimation system 200 can estimate the fatigue level of the subject 11 using the image output by the imaging device 201. In estimating the fatigue level of the subject 11, the posture of the subject 11 estimated from the output image is used. Specifically, the fatigue level is quantified based on the duration of time that the subject 11 remains in a stationary posture, and the amount of strain on the muscles and joints due to maintaining a certain stationary posture, the amount of fatigue accumulated due to deterioration of blood flow, etc. are quantified as the fatigue level. In this way, the fatigue estimation system 200 calculates the fatigue level of the subject 11 based on the image and taking into account the duration of time in a stationary posture, so that the fatigue level of the subject 11 in a stationary posture can be estimated with less strain on the subject 11 and with higher accuracy.

For example, the estimation device 100 may calculate the amount of load on at least one of the muscles and joints of the subject 11 used to maintain the estimated posture using the musculoskeletal model 11b, and estimate the degree of fatigue using an increasing function of the degree of fatigue with respect to the duration, and the increasing function used to estimate the degree of fatigue may be such that the greater the calculated amount of load, the greater the increase in the degree of fatigue per unit time.

According to this, the load amount for at least one of the individual muscles and joints is calculated using the musculoskeletal model 11b. The fatigue level of the subject 11 can be easily estimated by an increasing function with the slope of the load amount calculated in this way. Therefore, the fatigue level of the subject 11 can be easily estimated with higher accuracy.

In addition, for example, the estimation device 100 may calculate a load on at least one of the muscles and joints in each of two or more body parts including a first part and a second part of the body parts of the subject 11, and estimate, in one posture of the subject 11, at least a first fatigue level of the first part due to the load level calculated in the first part, and a second fatigue level of the second part due to the load level calculated in the second part.

This allows the fatigue level of two or more body parts of the subject 11 to be calculated with a single image capture. There is no need to perform measurements to estimate the fatigue level for each body part, and fatigue levels can be estimated quickly and approximately simultaneously for multiple body parts. Furthermore, the fatigue levels estimated approximately simultaneously make it easy to identify the body parts of the subject 11 that are prone to fatigue, which is effective when taking measures to recover from fatigue. Therefore, a quick and effective estimation of the fatigue level of the subject 11 can be performed.

In addition, for example, when posture is changed, the estimation device 100 may estimate the degree of fatigue using a decrease function of the degree of fatigue with respect to time, and the decrease function used to estimate the degree of fatigue may be such that the greater the change in posture, the greater the decrease in the degree of fatigue per unit time.

According to this, the load on at least one of the muscles and joints is changed in accordance with a change in the posture of the subject 11, and the recovery of the degree of fatigue due to the improvement of blood flow is reflected in the estimated degree of fatigue. Therefore, it is possible to estimate the degree of fatigue in terms of the momentum of the positions of the body parts of the subject 11 in a still posture with higher accuracy.

For example, the fatigue estimation system 200 may further include a display device 205 that displays a warning to the subject 11 as an estimation result when the fatigue level of the subject 11 estimated by the estimation device 100 reaches a first threshold value.

This allows the subject 11, etc., to know that the subject 11's fatigue level has reached the first threshold value through a warning displayed on the display device 205. The subject 11 can respond to the accumulated fatigue level in accordance with the displayed warning, thereby reducing the possibility of fatigue-related illness, such as poor physical condition, injury, and accidents. Thus, using the fatigue level estimated with higher accuracy, the subject 11's fatigue-related illness is reduced.

For example, the fatigue estimation system 200 may further include a display device 205 that displays to the subject 11 a recommended posture that is less stressful than the posture when the fatigue level of the subject 11 estimated by the estimation device 100 reaches a second threshold value.

This allows the subject 11, etc. to deal with the subject 11's fatigue level that has reached the second threshold by using the recommended posture displayed on the display device 205. By changing to the recommended posture, the subject 11's fatigue level is expected to recover, so the subject 11 can suppress the accumulation of fatigue without being particularly conscious of it. Therefore, using the fatigue level estimated with higher accuracy, discomfort caused by the subject 11's fatigue is suppressed.

For example, the fatigue estimation system 200 may further include a recovery device 206 that reduces the fatigue level of the subject 11 by promoting blood circulation in the subject 11 when the fatigue level of the subject 11 estimated by the estimation device 100 reaches a third threshold value.

As a result, the recovery device 206 is expected to recover the subject 11's fatigue level, and the subject 11 can suppress the accumulation of fatigue without being particularly conscious of it. Therefore, using the fatigue level estimated with higher accuracy, the subject 11's discomfort caused by fatigue is suppressed.

For example, the fatigue estimation system 200 may further include a pressure sensor 203 that outputs a pressure distribution indicating the distribution of pressure applied on the detection surface, and the estimation device 100 may correct the estimated posture of the subject 11 based on the pressure distribution output by the pressure sensor 203 and calculate the amount of load required to maintain the corrected posture.

This allows the pressure distribution output by the pressure sensor 203 to be used to estimate the posture of the subject 11. Therefore, the posture of the subject 11 can be estimated with high accuracy by correcting with the pressure distribution. Therefore, the fatigue level of the subject 11 can be estimated with higher accuracy.

For example, the fatigue estimation system 200 may further include a reception device 204 that receives input of personal information including at least one of the subject 11's age, sex, height, weight, muscle mass, stress level, body fat percentage, and exercise proficiency, and the estimation device 100 may correct the load amount based on the personal information received as input by the reception device 204 when calculating the load amount for maintaining the estimated posture.

According to this, the personal information accepted by the acceptance device 204 can be used to calculate the load. Therefore, the load in the stationary posture can be calculated with high accuracy by correcting with the personal information. Therefore, the fatigue level of the subject 11 can be estimated with high accuracy.

In addition, the estimation device 100 in the tenth aspect of this embodiment is an estimation device 100 that estimates the fatigue level of a subject 11 who is partially hidden when viewed from an imaging device 201, and includes a first acquisition unit 101 (hereinafter, image acquisition unit) that acquires an image including the subject 11 and furniture (desk 13, etc.) around the subject 11 from the imaging device 201, and a detection unit (for example, a detection unit included in the first acquisition unit 101 as one of its functions) that detects the top surface of the furniture (desk top surface 13a, etc.) included in the acquired image. The image capturing apparatus includes a posture estimation unit 105 that estimates the posture of the subject 11, the posture estimation unit 105 estimating the posture of a visible portion 11d of the subject 11 that is not hidden when viewed from the imaging device 201 based on the subject 11 included in the image, and estimating the posture of a non-visible portion 11c of the subject 11 that is hidden when viewed from the imaging device 201 based on the detected top surface, and a fatigue estimation unit 108 that estimates the subject's fatigue level based on the estimated posture of the subject.

Such an estimation device 100 can be combined with an imaging device 201 to achieve the same effect as the fatigue estimation system 200 described above.

For example, the device may include a first acquisition unit 101 that acquires information regarding the positions of body parts of the subject 11, a posture estimation unit 105 that estimates the posture of the subject 11 based on the information acquired by the first acquisition unit 101, and a fatigue estimation unit 108 that estimates a degree of fatigue based on the duration of the posture estimated by the posture estimation unit 105.

Such an estimation device 100 can estimate the fatigue level of the subject 11 using information such as the acquired image. In estimating the fatigue level of the subject 11, the posture of the subject 11 estimated from the acquired image is used. Specifically, the load on at least one of the muscles and joints due to maintaining a certain stationary posture, and the accumulation of fatigue due to deterioration of blood flow are quantified as the fatigue level from the duration of time that the subject 11 remains in a stationary posture. In this way, the estimation device 100 calculates the fatigue level of the subject 11 taking into account the duration of time in a stationary posture, so that the fatigue level of the subject 11 in a stationary posture can be estimated with higher accuracy.

In addition, the fatigue estimation method in the eleventh aspect of this embodiment is a fatigue estimation method for estimating the fatigue level of a subject 11 who is partially hidden when viewed from the imaging device 201, and includes acquiring an image including the subject 11 and furniture (such as a desk 13) around the subject 11 from the imaging device 201, detecting the top surface of the furniture (such as the desk top surface 13a) included in the acquired image, estimating the posture of the visible part 11d of the subject 11 that is not hidden when viewed from the imaging device 201 based on the subject 11 included in the image, estimating the posture of the non-visible part 11c of the subject 11 that is hidden when viewed from the imaging device 201 based on the detected top surface, and estimating the fatigue level of the subject 11 based on the estimated posture of the subject 11.

Such a fatigue estimation method can achieve the same effects as the fatigue estimation system 200 described above.

It may also include, for example, an acquisition step (e.g., step S103) for acquiring information regarding the positions of body parts of subject 11, a posture estimation step S106 for estimating the posture of subject 11 based on the information acquired in the acquisition step, and a fatigue estimation step S109 for estimating a degree of fatigue based on the duration of the posture estimated in posture estimation step S106.

Such a fatigue estimation method achieves the same effects as the above-mentioned estimation device 100.

Other Embodiments
Although the embodiments have been described above, the present disclosure is not limited to the above-described embodiments.

For example, in the above embodiment, the processing performed by a specific processing unit may be executed by another processing unit. Also, the order of multiple processes may be changed, or multiple processes may be executed in parallel.

Furthermore, the fatigue estimation system or estimation device in the present disclosure may be realized by multiple devices each having a portion of the multiple components, or may be realized by a single device having all of the multiple components. Also, some of the functions of a component may be realized as the functions of another component, and each function may be distributed in any manner among the components. Any form having a configuration that is provided with all of the functions that can substantially realize the fatigue estimation system or estimation device of the present disclosure is included in the present disclosure.

In the above embodiment, each component may be realized by executing a software program suitable for each component. Each component may be realized by a program execution unit such as a CPU or processor reading and executing a software program recorded on a recording medium such as a hard disk or semiconductor memory.

Each component may also be realized by hardware. For example, each component may be a circuit (or integrated circuit). These circuits may form a single circuit as a whole, or each may be a separate circuit. Each of these circuits may also be a general-purpose circuit, or a dedicated circuit.

In addition, the general or specific aspects of the present disclosure may be realized in a system, an apparatus, a method, an integrated circuit, a computer program, or a computer-readable recording medium such as a CD-ROM. In addition, the general or specific aspects of the present disclosure may be realized in any combination of a system, an apparatus, a method, an integrated circuit, a computer program, and a recording medium.

In the above embodiment, the subject's posture is estimated from an image using a rigid link model generated by image recognition, the load is calculated from the estimated subject's posture, and the subject's fatigue level is estimated based on the load and duration, but the method of estimating fatigue level is not limited to this. Any existing method may be used as a method of estimating the subject's posture from an image, and any existing method may be used as a method of estimating the load from the subject's posture.

In addition, as a method for estimating the posture of a subject, the present disclosure can also be realized by a configuration using a position sensor in addition to a configuration using an imaging device. A specific description will be given using FIG. 9. FIG. 9 is a diagram for explaining posture estimation according to a modified example of an embodiment. As shown in FIG. 9, in this modified example, the posture of the subject 11 is estimated using a sensor module 207 including a position sensor 207a and an electric potential sensor 207b. Here, multiple sensor modules 207 are attached to the subject 11, but there is no particular limit to the number of sensor modules 207 attached to the subject 11. Only one sensor module 207 may be attached to the subject 11.

There is also no particular limitation on the manner in which the sensor module 207 is worn, and any manner is acceptable as long as it is possible to measure the position of a specific body part of the subject 11. As an example, in FIG. 9, a costume to which multiple sensor modules 207 are attached is worn by the subject 11, and the multiple sensor modules 207 are attached to the subject 11.

The sensor module 207 is a device that is attached to a specific body part of the subject 11 and outputs information indicating the result of detection or measurement in conjunction with the specific body part. Specifically, the sensor module 207 has a position sensor 207a that outputs position information related to the spatial position of the specific body part of the subject 11, and an electric potential sensor 207b that outputs electric potential information indicating the electric potential at the specific body part of the subject 11. In the figure, the sensor module 207 having both the position sensor 207a and the electric potential sensor 207b is shown, but the electric potential sensor 207b is not essential as long as the sensor module 207 has the position sensor 207a.

The position sensor 207a in such a sensor module 207 is an example of an information output device that outputs position information as information relating to the position of a body part of the subject 11. Therefore, the output information is position information, and is information including the relative or absolute position of a specific body part of the subject 11. The output information may also include, for example, potential information. The potential information is information including the value of the potential measured at a specific body part of the subject 11. The position information and potential information will be described in detail below together with the position sensor 207a and the potential sensor 207b.

The position sensor 207a is a detector that detects the spatial relative or absolute position of a specific body part of the subject 11 to which the sensor module 207 is attached, and outputs information related to the spatial position of the specific body part, which is the detection result. The information related to the spatial position includes information that can identify the position of the body part in space as described above, and information that can identify a change in the position of the body part due to body movement. Specifically, the information related to the spatial position includes information indicating the positions of the joints and skeleton in space and the change in said positions.

The position sensor 207a is configured by combining various sensors such as an acceleration sensor, an angular velocity sensor, a geomagnetic sensor, and a distance sensor. The position information output by the position sensor 207a can approximate the spatial position of a specific body part of the subject 11, so that the posture of the subject 11 can be estimated from the spatial position of the specific body part.

The potential sensor 207b is a detector that measures the potential at a specific body part of the subject 11 to which the sensor module 207 is attached, and outputs information indicating the measurement result, which is the potential of the specific body part. The potential sensor 207b is a measuring instrument that has multiple electrodes and measures the potential generated between the multiple electrodes using an electrometer. The potential information output by the potential sensor indicates the potential generated at a specific body part of the subject 11, and since the potential corresponds to the action potential of the muscle in the specific body part, the accuracy of the estimation of the posture of the subject 11 estimated from the action potential of the specific body part can be improved.

The fatigue estimation system in this modified example estimates the fatigue level of the subject 11 using the posture of the subject 11 estimated as described above. Note that the processing subsequent to the estimation of the posture of the subject 11 is similar to that in the above embodiment, and therefore will not be described here.

As described above, in the fatigue estimation system of this modified example, the information output device is a position sensor 207a that is attached to a specific body part of the subject 11 and outputs position information regarding the spatial position of the specific body part as information regarding the position of the body part of the subject 11, and the estimation device 100 estimates the posture of the subject 11 based on the position information output by the position sensor 207a.

This allows the fatigue level of the subject 11 to be estimated using the position information output by the position sensor 207a. In estimating the fatigue level of the subject 11, the posture of the subject 11 estimated from the output information is used. Specifically, the accumulation of fatigue due to maintaining a certain stationary posture is quantified as the fatigue level from the duration of time that the subject 11 remains in the stationary posture. In this way, in the fatigue estimation system, the fatigue level of the subject 11 is calculated based on the results of detection and measurement by the sensor module 207 and taking into account the duration of the stationary posture, so that the fatigue level of the subject 11 in the stationary posture can be estimated with less burden on the subject 11 and with higher accuracy.

In addition, in the above embodiment, the increasing function and the decreasing function are described as being linear first-order functions, but this is not limited thereto. The increasing function may be a curved function as long as the fatigue level increases over time. Furthermore, the decreasing function may be a curved function as long as the fatigue level decreases over time.

The estimation device described above estimates the subject's level of fatigue using estimated values of muscle load, joint load, and blood flow rate estimated from the subject's posture, but it is also possible to achieve a more accurate estimation of fatigue level by correcting the estimated values with values measured using a measuring device. Specifically, the estimation device obtains measurement values that correspond to the estimated values and are based on the measurement results of measuring the subject using a measuring device.

The detection device may be, for example, an electromyograph, a muscle hardness meter, a pressure gauge, or a near-infrared spectrometer, and may obtain measurements related to the load on the muscle, the load on the joint, and the blood flow rate by measurement. For example, an electromyograph may estimate the muscle movement corresponding to the potential measured by potential measurement. In other words, the estimated muscle movement may be obtained as the measurement value. The estimated muscle movement may be converted into the load on the muscle, and therefore the estimated muscle load may be corrected by the measurement value. The correction here may involve, for example, taking the average of the estimated value and the measurement value, selecting either the estimated value or the measurement value, or substituting the estimated value into the correlation function between the estimated value and the measurement value.

A muscle hardness meter can estimate muscle hardness based on the stress exerted when pressure is applied to the muscle. The estimated muscle hardness can be converted into the amount of load on the muscle, and can be used to correct the estimated value in the same way as above.

A pressure gauge can obtain measurements of the pressure being applied to parts of the subject's body. Such pressure parameters can be input into a musculoskeletal model. Inputting additional parameters such as pressure improves the estimation accuracy of the musculoskeletal model, allowing the estimated values estimated using the musculoskeletal model to be corrected with higher accuracy.

The near-infrared spectrometer can obtain a measurement value obtained by spectroscopically measuring the blood flow rate of the subject. As in the above embodiment, when the estimated value does not include the blood flow rate, the estimated value may be corrected by combining the blood flow rate measured by the infrared spectrometer. Even when the estimated value includes the blood flow rate, the measured blood flow rate may be used when the reliability of the estimated value of the blood flow rate is low.

In this way, by using measurement values corresponding to estimates obtained from a different aspect and making corrections to make the estimates more accurate, it is possible to make a more accurate estimate of the subject's level of fatigue.

In addition, a fatigue factor identification system that identifies the factors behind a subject's fatigue may be configured using the fatigue estimation system described in the above embodiment. Conventionally, with devices or systems that estimate the degree of fatigue as "degree of stiff shoulders" and "degree of lower back pain", etc., it has been difficult to identify the way muscles and joints are used that are the factors behind such "degree of stiff shoulders" and "degree of lower back pain" (i.e., the posture that is the factor). Therefore, by using the fatigue estimation system in the present disclosure, the above problem can be addressed.

That is, in the fatigue factor identification system of the present disclosure, a body part in which fatigue is likely to accumulate in a static posture taken by the subject (a body part with a large estimated amount of promoting various types of fatigue) is identified as a fatigue factor part. Furthermore, the fatigue factor identification system may simply identify a fatigue factor part in one static posture taken by the subject, or may identify a fatigue factor posture with the largest estimated amount of the fatigue factor part from among multiple static postures taken by the subject. In addition, a recommended posture to replace the identified fatigue factor posture may be presented, or a fatigue recovery operation using a recovery device may be performed on the fatigue factor part in the fatigue factor posture.

The fatigue factor identification system includes the fatigue estimation system described in the above embodiment and a storage device for storing information related to the estimated fatigue level. Such a storage device is realized, for example, using a semiconductor memory or the like, and each main storage unit constituting the fatigue estimation system may be used, or a new storage device may be provided that is communicatively connected to the estimation device.

The present disclosure may also be realized as a fatigue estimation method executed by a fatigue estimation system or an estimation device. The present disclosure may also be realized as a program for causing a computer to execute such a fatigue estimation method, or as a computer-readable non-transitory recording medium on which such a program is recorded.

In addition, this disclosure also includes forms obtained by applying various modifications to the embodiments that may occur to a person skilled in the art, or forms realized by arbitrarily combining the components and functions of each embodiment without departing from the spirit of this disclosure.

11 Subject 11a Rigid body link model 11b Musculoskeletal model 11c Non-visible part 11d Visible part 11l Back joint 11m Lumbar skeleton 11n Lumbar joint 11o Thigh skeleton 11x Angle 12 Chair 13 Desk (furniture)
13a Desk surface (top)
100 Estimation device 101 First acquisition unit (image acquisition unit)
102 Second acquisition unit 103 Third acquisition unit 104 Fourth acquisition unit 115 Fifth acquisition unit 116 Sixth acquisition unit 105 Posture estimation unit 106 First calculation unit 107 Second calculation unit 108 Fatigue estimation unit 109 Output unit 200 Fatigue estimation system 201 Imaging device 202 Timing device 203 Pressure sensor 204 Reception device 215 Storage device 216 Height sensor 205 Display device 206 Recovery device 207 Sensor module 207a Position sensor 207b Potential sensor

Claims (11)

A fatigue estimation system that estimates a degree of fatigue of a subject, a part of which is hidden as an invisible part by a fixture as seen from an imaging device, and that estimates a degree of fatigue that accumulates when the subject assumes a fixed, still posture ,
The imaging device captures an image including the subject and fixtures around the subject;
an image acquisition unit that acquires the image from the imaging device;
A detection unit that detects a top surface of a fixture around the subject included in the acquired image;
a posture estimation unit that estimates a posture of the subject, the posture estimation unit estimating a posture of a visible part of the subject that is not hidden when viewed from the imaging device based on the subject included in the image, detecting a horizontal plane based on the detected top surface, and estimating a direction in which a skeleton of the invisible part extends, the skeleton being capable of determining an angle formed with respect to the horizontal plane, thereby estimating the posture of the invisible part ;
A fatigue estimation system comprising: a fatigue estimation unit that estimates a fatigue level of the subject based on an estimated posture of the subject. the visible portion includes a hip joint of the subject;
the non-visible portion includes a femoral skeleton of the subject, the femoral skeleton being a skeleton extending from the hip joint;
The fatigue estimation system according to claim 1 , wherein the posture estimation unit estimates an extension direction of the thigh skeleton extending in a direction forming a predetermined angle with respect to the top surface from a position of the waist joint included in the estimated posture of the visible part. the visible portion includes a back joint of the subject;
the non-visible portion includes a lumbar joint of the subject connected to the back joint via a lumbar vertebral skeleton of the subject, which is a skeleton extending from the back joint, and a femoral skeleton of the subject, which is a skeleton extending from the lumbar joint;
The fatigue estimation system further comprises:
A length acquisition unit for acquiring a length of the lumbar vertebral skeleton;
A height acquisition unit for acquiring a height of the waist joint,
The posture estimation unit is
From the position of the back joint included in the estimated posture of the visible part, a position of the lumbar joint is estimated that is within a range of the length of the acquired lumbar skeleton and coincides with the height of the acquired lumbar joint;
The fatigue estimation system according to claim 1 , further comprising: estimating an extension direction of the thigh skeleton, the extension direction extending in a direction forming a predetermined angle with respect to the top surface, from the estimated position of the waist joint. The fatigue estimation system according to claim 2 , wherein when the subject is in a standing position, the predetermined angle is within a range of 80 degrees to 100 degrees. The fatigue estimation system according to claim 4 , wherein the predetermined angle is 90 degrees when the subject is in a standing position. The fatigue estimation system according to claim 2 , wherein when the subject is in a sitting position, the predetermined angle is within a range of −10 degrees to 10 degrees. The fatigue estimation system according to claim 6 , wherein the predetermined angle is 0 degrees when the subject is in a sitting position. The furniture around the subject is a desk used by the subject,
The fatigue estimation system according to claim 1 , wherein the top surface is a top surface of the desk. The fatigue estimation system according to claim 1 , wherein the non-visible part is hidden by furniture around the subject as viewed from the imaging device. An estimation device that estimates a degree of fatigue of a subject, a part of which is hidden as an invisible part by a fixture as seen from an imaging device, and that accumulates when the subject takes a fixed, still posture ,
An image acquisition unit that acquires an image including the subject and furniture around the subject from the imaging device;
A detection unit that detects a top surface of a fixture around the subject included in the acquired image;
a posture estimation unit that estimates a posture of the subject, the posture estimation unit estimating a posture of a visible part of the subject that is not hidden when viewed from the imaging device based on the subject included in the image, detecting a horizontal plane based on the detected top surface, and estimating a direction in which a skeleton of the invisible part extends, the skeleton being capable of determining an angle formed with respect to the horizontal plane, thereby estimating the posture of the invisible part ;
and a fatigue estimation unit that estimates the fatigue level of the subject based on the estimated posture of the subject. A fatigue estimation method executed by an estimation device that estimates a fatigue level of a subject, a part of which is hidden as an invisible part by a fixture as seen from an imaging device, and that accumulates when the subject assumes a fixed, still posture, comprising :
The estimation device comprises:
Acquire an image including the subject and furniture around the subject from the imaging device;
Detecting a top surface of the fixture included in the acquired image;
estimating a posture of a visible portion of the subject that is not hidden when viewed from the imaging device based on the subject included in the image;
detecting a horizontal plane based on the detected top surface, and estimating a direction in which a skeleton of the non-visible portion extends, the direction being capable of determining an angle with respect to the horizontal plane, thereby estimating a posture of the non-visible portion ;
The fatigue level of the subject is estimated based on the estimated posture of the subject.

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