Physical-characteristic estimation support program, physical-characteristic estimation support device, physical-characteristic estimation support method, and recording medium
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- UGOKINO CLINIC CORP
- Filing Date
- 2026-02-02
- Publication Date
- 2026-08-06
Smart Images
Figure JP2026003675_06082026_PF_FP_ABST
Abstract
Description
Body characteristic estimation support program, body characteristic estimation support device, body characteristic estimation support method, and recording medium
[0001] The present disclosure relates to a body characteristic estimation support program, a body characteristic estimation support device, a body characteristic estimation support method, and a recording medium.
[0002] In recent years, with the progress of the declining birthrate and aging population, the number of people suffering from low back pain and knee pain has been increasing. Therefore, in order to prevent low back pain and the like, based on the weight of an object, the height and weight of a wearer, and the trunk angle of the wearer, the intervertebral disc compression force of the wearer is continuously estimated, and while measuring the elapsed time for each section according to the load level of the intervertebral disc compression force in a time series, a lumbar load evaluation device that predicts the occurrence risk of the wearer's low back pain symptoms during the working time of a heavy muscle operation for handling an object is known (Patent Document 1).
[0003] Japanese Patent Application Laid-Open No. 2021-037059
[0004] However, the technique of Patent Document 1 has problems that a special wearable motion assistance device is required to estimate the onset risk of low back pain, so the hurdle for inspection is high, and it cannot be used for estimation other than the incidence rate of low back pain.
[0005] Therefore, an object of the present disclosure is to provide a body characteristic estimation support program, a body characteristic estimation support device, a body characteristic estimation support method, and a recording medium that can easily estimate various body characteristics of an individual.
[0006] In order to achieve the above object, the body characteristic estimation support program of the present disclosure includes a posture analysis information acquisition procedure, a posture analysis procedure, a body characteristic estimation procedure, and an output procedure. The posture analysis information acquisition procedure acquires posture analysis information of a subject. The posture analysis information includes plantar pressure waveform data. The plantar pressure waveform data is information on the change in pressure on the sole of the foot when the subject is in a predetermined state for a predetermined time. The posture analysis procedure extracts the posture feature amount of the subject based on the posture analysis information. The body characteristic estimation procedure estimates the body characteristics of the subject based on the posture feature amount. The output procedure outputs the body characteristics of the subject. It is a body characteristic estimation support program for causing a computer to execute each procedure.
[0007] The physical characteristics estimation support device of this disclosure includes a posture analysis information acquisition unit, a posture analysis unit, a physical characteristics estimation unit, and an output unit, wherein the posture analysis information acquisition unit acquires posture analysis information of a subject, the posture analysis information includes foot pressure waveform data, the foot pressure waveform data is information on the change in pressure on the soles of the feet when the subject assumes a predetermined state for a predetermined period of time, the posture analysis unit extracts posture features of the subject based on the posture analysis information, the physical characteristics estimation unit estimates the physical characteristics of the subject based on the posture features, and the output unit outputs the physical characteristics of the subject.
[0008] The physical characteristics estimation support method of this disclosure includes a posture analysis information acquisition step, a posture analysis step, a physical characteristics estimation step, and an output step, wherein each step is performed by a computer, the posture analysis information acquisition step involves acquiring posture analysis information of a subject, the posture analysis information includes foot pressure waveform data, the foot pressure waveform data is information on the change in pressure on the soles of the feet when the subject is in a predetermined state for a predetermined period of time, the posture analysis step extracts posture features of the subject based on the posture analysis information, the physical characteristics estimation step estimates the physical characteristics of the subject based on the posture features, and the output step outputs the physical characteristics of the subject.
[0009] The recording medium of this disclosure is a computer-readable recording medium on which the physical characteristics estimation support program of this disclosure is recorded.
[0010] According to this disclosure, various physical characteristics of an individual can be easily estimated.
[0011] Figure 1 is a block diagram showing the configuration of an example of the physical characteristics estimation support device of this disclosure. Figure 2 is a block diagram showing an example of the hardware configuration of the physical characteristics estimation support device of this disclosure. Figure 3 is a flowchart showing an example of the procedure by the physical characteristics estimation support program of this disclosure. Figure 4 is a schematic diagram showing an example of the foot pressure measurement locations of a subject in this disclosure.
[0012] The embodiments of this disclosure will be described below with reference to the drawings. This disclosure is not limited to the embodiments described below. In the following drawings, the same parts are denoted by the same reference numerals. Furthermore, unless otherwise specified, the descriptions of each embodiment can be used interchangeably with those of the other, and unless otherwise specified, the configurations of each embodiment can be combined. In this disclosure, each drawing may correspond to one or more embodiments.
[0013] [Embodiment 1] The physical characteristics estimation support program of this disclosure is a program that causes a computer to execute a procedure for acquiring information for posture analysis, a posture analysis procedure, a physical characteristics estimation procedure, and an output procedure. The physical characteristics estimation support program of this disclosure can also be described as a program that causes a computer to function as the procedure for acquiring information for posture analysis, a posture analysis procedure, a physical characteristics estimation procedure, and an output procedure. Furthermore, the physical characteristics estimation support program of this disclosure can also be described as a program that causes a computer to execute each step of the physical characteristics estimation support method described later.
[0014] The posture analysis information acquisition procedure acquires posture analysis information of a subject, the posture analysis information includes foot pressure waveform data, the foot pressure waveform data is information on the change in pressure on the soles of the feet when the subject is in a predetermined state for a predetermined period of time, the posture analysis procedure extracts posture features of the subject based on the posture analysis information, the physical characteristics estimation procedure estimates the physical characteristics of the subject based on the posture features, and the output procedure outputs the physical characteristics of the subject.
[0015] Each of the aforementioned steps can be reinterpreted, for example, by substituting "step" with "process." Furthermore, the physical characteristic estimation support program of this disclosure may be recorded on, for example, a computer-readable recording medium. The recording medium is, for example, a non-transitory computer-readable storage medium. The recording medium is not particularly limited and includes, for example, random access memory (RAM), read-only memory (ROM), hard disk (HD), flash memory (e.g., SSD (Solid State Drive), USB flash memory, SD / SDHC card, etc.), optical disc (e.g., CD-R / CD-RW, DVD-R / DVD-RW, BD-R / BD-RE, etc.), magneto-optical disk (MO), floppy disk (FD), etc. Furthermore, the physical characteristic estimation support program of this disclosure (for example, also referred to as a programming product or program product) may be delivered, for example, from an external computer. The aforementioned "distribution" may be, for example, distribution via a communication network or distribution via a wired connected device. The physical characteristics estimation support program of this disclosure may be installed and executed on the distributed device, or it may be executed without being installed. An information processing device capable of executing the physical characteristics estimation support program of this disclosure can be, for example, the physical characteristics estimation support device of this disclosure.
[0016] Next, the configuration of an example of the physical characteristic estimation support device of this disclosure will be described with reference to Figure 1. Figure 1 is a block diagram showing an example of the configuration of the physical characteristic estimation support device 10 of this disclosure (hereinafter also referred to as "the device 10"). As shown in Figure 1, the device 10 includes a posture analysis information acquisition unit 11, a posture analysis unit 12, a physical characteristic estimation unit 13, and an output unit 14. The device 10 may also include, for example, an input unit, an output unit, a display unit, and / or a storage unit, although these are not shown. The posture analysis information acquisition unit 11, the posture analysis unit 12, the physical characteristic estimation unit 13, and the output unit 14 can each execute, for example, the posture analysis information acquisition procedure, the posture analysis procedure, the physical characteristic estimation procedure, and the output procedure in the physical characteristic estimation support program of this disclosure.
[0017] The device 10 may be, for example, a single device including the aforementioned parts, or it may be a device in which each of the aforementioned parts can be connected via a communication network. Furthermore, the device 10 can be connected to an external device described later via the communication network. The communication network is not particularly limited and can use a known network, for example, it may be wired or wireless. Examples of the communication network include the Internet, WWW (World Wide Web), telephone line, LAN (Local Area Network), SAN (Storage Area Network), DTN (Delay Tolerant Networking), LPWA (Low Power Wide Area), L5G (Local 5G), etc. Examples of wireless communication include Wi-Fi®, Bluetooth®, Local 5G, LPWA, etc. The aforementioned wireless communication may be in the form of direct communication between devices (Ad Hoc communication), infrastructure communication, indirect communication via an access point, etc. The device 10 may, for example, be incorporated into a server as a system. Alternatively, the device 10 may be, for example, a personal computer (PC, e.g., desktop or notebook), smartphone, tablet terminal, etc., on which the program disclosed herein is installed. The device 10 may also be in the form of cloud computing or edge computing, for example, in which at least one of the aforementioned parts is on a server and the other aforementioned parts are on a terminal. When the device 10 is composed of multiple devices, the device 10 may also be called, for example, a physical characteristic estimation support system.
[0018] Figure 2 illustrates a block diagram of the hardware configuration of the device 10. The device 10 includes, for example, a central processing unit (CPU, GPU, etc.) 101, memory 102, bus 103, storage device 104, input device 105, output device 106, communication device 107, etc. Each part of the device 10 is interconnected via the bus 103 through its respective interface (I / F).
[0019] The central processing unit 101 operates in coordination with other components via controllers (system controller, I / O controller, etc.) and is responsible for the overall control of the device 10. In the device 10, the central processing unit 101 executes, for example, the program of this disclosure (the body characteristic estimation support program) and other programs, and also reads and writes various types of information. Specifically, for example, the central processing unit 101 functions as a posture analysis information acquisition unit 11, a posture analysis unit 12, and a body characteristic estimation unit 13. The device 10 may also include other computing devices such as a CPU (Central Processing Unit), GPU (Graphics Processing Unit), APU (Accelerated Processing Unit), or a combination thereof.
[0020] Bus 103 can also be connected to external devices, for example. Examples of such external devices include external storage devices (external databases, etc.), printers, external input devices, external display devices, and external imaging devices. The device 10 can be connected to an external network (the aforementioned communication network) via a communication device 107 connected to bus 103, for example, and can also be connected to other devices via the external network.
[0021] Memory 102 may be, for example, main memory. When the central processing unit 101 performs processing, memory 102 reads various operational programs, such as the program of this disclosure, stored in the storage device 104 (described later), and the central processing unit 101 receives data from memory 102 and executes the program. The main memory may be, for example, RAM (random access memory). Alternatively, memory 102 may be, for example, ROM (read-only memory).
[0022] The storage device 104 is also called an auxiliary storage device, for example, in relation to the main memory (primary memory). As described above, the storage device 104 stores an operating program including the program of this disclosure. The storage device 104 may be, for example, a combination of a recording medium and a drive for reading and writing to the recording medium. The recording medium is not particularly limited and may be internal or external, for example, an HD (hard disk), CD-ROM, CD-R, CD-RW, MO, DVD, flash memory, memory card, etc. The storage device 104 may be, for example, a hard disk drive (HDD) in which the recording medium and the drive are integrated, or a solid state drive (SSD). If the device 10 includes the storage unit, for example, the storage device 104 functions as the storage unit. The storage unit can store, for example, user information of the device (name, identification number, attribute information (gender, age, affiliated organization, address, contact information, hobbies, preferences, etc.), biometric information, etc.), foot pressure waveform data described later, analysis information, characteristic estimation information, etc.
[0023] In this device 10, the memory 102 and storage device 104 can also store various types of information, such as log information, information obtained from an external database (not shown) or external devices, information generated by this device 10, and information used by this device 10 when executing processing. In this case, the memory 102 and storage device 104 may store, for example, the user information of this device as described above. At least some of the information may be stored on an external server other than the memory 102 and storage device 104, or it may be stored in a distributed manner across multiple terminals using blockchain technology or the like.
[0024] The device 10 further includes, for example, an input device 105 and an output device 106. The input device 105 may include, for example, a pointing device such as a touch panel, trackpad, or mouse; a keyboard; imaging means such as a camera or scanner; a card reader such as an IC card reader or magnetic card reader; an audio input means such as a microphone; and so on. The output device 106 may include, for example, a display device such as an LED display or liquid crystal display; an audio output device such as a speaker; a printer; and so on. In this embodiment 1, the input device 105 and the output device 106 are configured separately, but the input device 105 and the output device 106 may be configured as an integrated unit, such as a touch panel display.
[0025] An example of processing performed by the physical characteristics estimation support program of this disclosure will be explained in more detail using Figure 3. Figure 3 is a flowchart showing an example of each step of the physical characteristics estimation support program of this disclosure.
[0026] The posture analysis information acquisition unit 11 acquires posture analysis information of the subject (S1, posture analysis information acquisition procedure). The posture analysis information includes foot pressure waveform data. The foot pressure waveform data is information on the change in pressure on the soles of the feet when the subject maintains a predetermined state for a predetermined period of time. The predetermined period is not particularly limited and can be set to any time. Specific examples of the predetermined period include any specified time, or the time it takes for the subject to complete a predetermined movement described later. The measurement points for the pressure on the soles of the feet (also called foot pressure) are not particularly limited and can be any point on the soles of the subject's feet, and may be one point or multiple points. If there are multiple locations for measuring foot pressure, for example, as shown in Figure 4, the subject may be divided into areas such as the forefoot, hindfoot, lateral side, and medial side, or the foot pressure of the hallux 2A, ball of the hallux 2B, middle forefoot 2C, lateral forefoot 2D, heel 2E, lateral heel 2F, and arch 2G may be measured. As a specific example, it is preferable that the posture analysis information acquisition unit 11 measures the pressure of the hallux 2A, medial forefoot (ball of the hallux 2B), lateral forefoot (ball of the little toe 2D), medial midfoot, lateral midfoot, medial hindfoot, and lateral hindfoot. The posture analysis information acquisition unit 11 may, for example, acquire the posture analysis information from a foot pressure measuring device that measures the foot pressure waveform data, or it may acquire the posture analysis information by collecting the subject's foot pressure over time measured by a pressure sensor connected via the bus 103. The foot pressure measuring device can be, for example, any known foot pressure measuring device as appropriate. The posture analysis information acquisition unit 11 may, for example, record the acquired posture analysis information.
[0027] The posture analysis information acquisition unit 11 can acquire, for example, at least one of the following as foot pressure waveform data: standing foot pressure waveform data in a standing posture state and exercise foot pressure waveform data in a predetermined exercise state. The standing posture state is, for example, a state in which the subject is standing naturally. The predetermined exercise state includes, for example, at least one selected from the group consisting of squats, walking, stepping in place, bending forward, and raising and lowering the heels. The predetermined exercise state is not limited to the examples given above and may be any movement. The arbitrary movement may be, for example, a predetermined training movement. The squat movement is not particularly limited and may be any squat movement, but for example, it may be a movement in which the subject repeatedly moves from a standing position to a state in which they squat as low as possible with their arms hanging down, and then back to a standing position. The walking movement is, for example, a state in which the subject is walking naturally. The stepping movement is, for example, a state in which the subject is naturally stepping in place while standing. In the stepping movement, it is preferable that the subject raises their thighs as high as possible. A forward bending motion is, for example, a motion in which the subject bends their upper body forward from a standing position while keeping their arms down. A heel raising and lowering motion is, for example, a motion in which the subject raises and lowers their heels from a standing position while keeping their toes on the ground. In the heel raising and lowering motion, for example, the left and right heels may be raised and lowered simultaneously or alternately, but it is preferable to raise and lower them simultaneously. The posture analysis information acquisition unit 11 can acquire, for example, at least one selected from the group consisting of standing foot pressure waveform data in a standing posture, squat foot pressure waveform data during a squat motion, walking foot pressure waveform data during a walking motion, stepping foot pressure waveform data during a stepping motion, forward bending foot pressure waveform data during a forward bending motion, and heel raising and lowering foot pressure waveform data during a heel raising and lowering motion.
[0028] The posture analysis information acquisition unit 11 may acquire posture analysis information, including, for example, posture analysis images of the subject. The posture analysis images may include, but are not limited to, standing posture images taken when the subject assumes the aforementioned standing posture, or movement posture images taken when the subject assumes the predetermined movement state. The posture analysis images may be, for example, a video or a still image. The posture analysis information acquisition unit 11 may record the acquired posture analysis images.
[0029] The posture analysis unit 12 extracts posture features of the subject based on the posture analysis information (S2, posture analysis procedure). The posture features are, for example, indicators for estimating the subject's physical characteristics obtained from the posture analysis information. The posture analysis unit 12 may, for example, extract the posture features for each state of the subject (the aforementioned standing state, a predetermined movement state). Specifically, the posture analysis unit 12 can, for example, extract posture features such as the weight balance of the subject's soles, the foot pressure center of gravity trajectory, and the pressure change rate based on the posture analysis information. The weight balance is, for example, information on the ratio of pressure at each measurement site of the subject's foot pressure. The foot pressure center of gravity trajectory is, for example, information on the trajectory connecting the parts of the subject's soles with the highest foot pressure in chronological order. The pressure change rate is, for example, information on the rate at which the subject's foot pressure changes.
[0030] Furthermore, if a posture analysis image is acquired as posture analysis information, the posture analysis unit 12 may further extract posture features based on the posture analysis image, for example. Examples of posture features based on the posture analysis image include joint angles, body center of gravity position, trunk inclination angle, and so on.
[0031] The physical characteristics estimation unit 13 estimates the physical characteristics of the subject based on the posture features (S3, physical characteristics estimation procedure). Specifically, the physical characteristics estimation unit 13 can estimate the physical characteristics of the subject by comparing the posture features of the subject with reference feature information. The reference feature information is information in which conditions for posture features are linked to each type of physical characteristic. The physical characteristics estimation unit 13 determines, for example, whether the posture features of the subject conform to the conditions for posture features defined in the reference feature information and linked to physical characteristics. If the posture features of the subject conform to the conditions, it can be estimated that the subject has the physical characteristics linked to those conditions. The physical characteristics are, for example, information indicating the physical features of the subject. The physical characteristics may be, for example, an evaluation of whether the subject's body is normal or abnormal, or an evaluation of more specific features. Also, the physical characteristics may be, for example, information indicating the current physical features of the subject, or information indicating the future physical features of the subject. Specific examples of physical characteristics include, for instance, information indicating whether the subject's body is healthy (normal) or abnormal, and information indicating predetermined features such as lordosis, lumbar kyphosis, knee-in, and knee-out.
[0032] Tables 1 to 6 below show specific examples of standard feature information, but this disclosure is not limited to these examples.
[0033]
[0034]
[0035]
[0036]
[0037]
[0038]
[0039] Further, the body characteristic estimation unit 13 may, for example, input the posture analysis information into the body characteristic estimation model to estimate the body characteristics of the subject. In this case, the body characteristic estimation model is a model learned to output an estimation result of the body characteristics of the subject when the posture feature amount of the subject is input by machine learning using the body characteristics as correct labels for the posture feature amounts.
[0040] The body characteristic estimation model may be, for example, stored in advance in the memory 102 and the storage device 104, or may be acquired from the outside via a communication network.
[0041] The body characteristic estimation model can be generated, for example, by machine learning using a set of the posture feature amount of the subject and the body characteristics of the subject as teacher data (learning information). For the machine learning, for example, a known machine learning method can be adopted. As a specific example, the statistical models adopted in the machine learning include, for example, simple linear regression model, Ridge regression, Lasso regression, Elastic Net regression, LightGBM (Light Gradient Boosting Machine), Logistic regression, general additive model, random forest regression, rule fit regression, gradient boosting tree, extra tree, support vector regression, Gaussian process regression, regression by k-nearest neighbor method, kernel ridge regression, neural network, etc. Note that the body characteristic estimation model may be, for example, a pre-generated learned model. Further, the learned model may be a learned model (derived model) re-learned using the teacher data and a previously generated learned model. Furthermore, the learned model may be a learned model obtained by transfer learning using a learned model generated using the teacher data, or may be a learned model generated by compressing the model of the learned model generated using the teacher data.
[0042] The physical characteristic estimation model may be a network including, for example, an input layer that inputs the posture features of a subject, an output layer that outputs the estimation results of the physical characteristics, and at least one intermediate layer provided between the input layer and the output layer. In this case, the physical characteristic estimation model may be a program module that is part of artificial intelligence software. Examples of the multilayer network include neural networks. Examples of the neural network include convolutional neural networks (CNNs), but are not limited to CNNs. Other neural networks, SVMs (Support Vector Machines), Bayesian networks, regression trees, and other learning algorithms may be used to construct trained models.
[0043] The output unit 14 then outputs the physical characteristics of the subject (S4, output step). The output unit 14 may output the physical characteristics to the output device 106 of the device 10 (for example, a display), or to an external device outside the device 10. The output unit 14 may output the physical characteristics as numerical data, as text data, or as image data. Specifically, the output unit 14 can output text indicating whether the subject's physical characteristics are healthy (normal) or abnormal, and if abnormal, text indicating the nature of the abnormality (for example, information indicating predetermined features such as lordosis, lumbar kyphosis, knee-in, knee-out). Furthermore, when outputting the physical characteristics as numerical data, the output unit 14 may output posture feature quantities for each posture as the physical characteristics. The posture feature quantities are, for example, as described above.
[0044] The output unit 14 may, for example, further generate and output image information reflecting the physical characteristics. The image information is not particularly limited and may be, for example, an avatar image. The avatar image is information of an image for displaying a virtual posture of a target person who is the user, and may be an image of a character. Generally, even if there is an abnormality in a person's body balance, it is difficult to recognize the abnormality. In the present disclosure, by outputting the image information (particularly, the avatar image) reflecting the physical characteristics of the target person by the output unit 14, the target person who is the user can visually understand, for example, the dissociation between the body balance assumed by the user and the actual body balance. Further, the output unit 14 may, for example, reflect the posture estimated from the input foot pressure on the avatar image.
[0045] As a usage example, when the present device 10 has such a mode, for example, a game or the like that controls the movement of an avatar image can be realized by using the foot pressure waveform data of the user as an input.
[0046] The output unit 14 may, for example, output action instruction information for instructing an action for improving the physical characteristics of the target person based on the physical characteristics. Examples of the action instruction information include information for training for improving physical characteristics. The action instruction information may be recorded, for example, in the storage unit of the present device 10 in association with each piece of information for each type of the physical characteristics. Thereby, the output unit 14 can output the action instruction information associated with the physical characteristics of the target person.
[0047] The output unit 14 may, for example, further output action instruction information for instructing to take the predetermined state after outputting the action instruction information. In this case, further, the posture analysis information acquisition unit 11 of the present device 10 may, for example, acquire the posture analysis information of the target person in the predetermined state instructed by the action instruction information, the posture analysis unit 12 may extract the posture feature amount of the target person based on the foot pressure waveform data, and the physical characteristic estimation unit 13 may estimate the physical characteristics of the target person based on the posture feature amount.
[0048] The physical characteristic estimation support method of this disclosure is a method implemented by, for example, replacing each "procedure" in the physical characteristic estimation support program of this disclosure with a "process." The physical characteristic estimation support method of this disclosure can be implemented, for example, using the physical characteristic estimation support device 10 of this disclosure shown in Figure 1 or Figure 2. However, the physical characteristic estimation support method of this disclosure is not limited to, for example, a method using the physical characteristic estimation support device 10. The physical characteristic estimation support method of this disclosure can, for example, utilize the descriptions in the physical characteristic estimation support program and physical characteristic estimation support device of this disclosure.
[0049] The physical characteristics estimation support program of this disclosure can, for example, acquire information for the subject's posture analysis using a posture analysis information acquisition procedure, extract posture features of the subject based on the posture analysis information using a posture analysis procedure, estimate the subject's physical characteristics based on the posture features using a physical characteristics estimation procedure, and output the subject's physical characteristics using an output procedure. For this reason, according to the physical characteristics estimation support program of this disclosure, for example, the subject's physical characteristics can be estimated simply by measuring the subject's foot pressure.
[0050] Although the present disclosure has been described above with reference to embodiments, the present disclosure is not limited to the embodiments described above. Various modifications to the structure and details of the present disclosure are possible, as can be understood by those skilled in the art within the scope of the present disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate.
[0051] This application claims priority based on Japanese Patent Application No. 2025-015863, filed on 3 February 2025, and incorporates all of its disclosures herein.
[0052] <Note> Some or all of the above embodiments may be described as follows, but are not limited to the following. (Note 1) A body characteristic estimation support program for causing a computer to execute each of the following procedures, including a procedure for acquiring information for posture analysis, a procedure for posture analysis, a procedure for estimating physical characteristics, and an output procedure, wherein the procedure for acquiring information for posture analysis acquires information for posture analysis of a subject, the posture analysis information includes foot pressure waveform data, the foot pressure waveform data is information on the change in pressure on the soles of the feet when the subject is in a predetermined state for a predetermined time, the posture analysis procedure extracts posture features of the subject based on the posture analysis information, the body characteristic estimation procedure estimates the physical characteristics of the subject based on the posture features, and the output procedure outputs the physical characteristics of the subject. (Note 2) The body characteristic estimation support program according to Note 1, wherein the procedure for acquiring information for posture analysis acquires at least one of standing foot pressure waveform data in a standing posture state and exercise foot pressure waveform data in a predetermined exercise state as the foot pressure waveform data. (Note 3) The physical characteristic estimation support program according to Note 2, wherein the predetermined exercise state includes at least one selected from the group consisting of squats, walking, stepping, bending forward, and raising and lowering the heels. (Note 4) The physical characteristic estimation support program according to any one of Notes 1 to 3, wherein the posture analysis information acquisition procedure acquires the posture analysis information including a posture analysis image of the subject, and the posture analysis procedure further extracts posture features based on the posture analysis image. (Note 5) The physical characteristic estimation support program according to any one of Notes 1 to 4, wherein the physical characteristic estimation procedure estimates the physical characteristics of the subject by comparing the posture features with reference feature information. (Note 6) The physical characteristic estimation support program according to any one of Notes 1 to 5, wherein the output procedure outputs action instruction information that instructs actions to improve the physical characteristics of the subject based on the physical characteristics.(Note 7) The output procedure further outputs action instruction information instructing the subject to assume the predetermined state after outputting the action instruction information; the posture analysis information acquisition procedure acquires posture analysis information of the subject in the predetermined state instructed by the action instruction information; the posture analysis procedure extracts posture features of the subject based on the foot pressure waveform data; and the body characteristics estimation procedure estimates the body characteristics of the subject based on the posture features, as described in Note 6, for the body characteristics estimation support program. (Note 8) A body characteristic estimation support device comprising: a posture analysis information acquisition unit, a posture analysis unit, a body characteristic estimation unit, and an output unit, wherein the posture analysis information acquisition unit acquires posture analysis information of a subject, the posture analysis information includes foot pressure waveform data, the foot pressure waveform data is information on the change in pressure on the soles of the feet when the subject is in a predetermined state for a predetermined time, the posture analysis unit extracts posture features of the subject based on the posture analysis information, the body characteristic estimation unit estimates the body characteristics of the subject based on the posture features, and the output unit outputs the body characteristics of the subject. (Note 9) The body characteristic estimation support device according to Note 8, wherein the posture analysis information acquisition unit acquires at least one of standing foot pressure waveform data in a standing posture state and exercise foot pressure waveform data in a predetermined exercise state as the foot pressure waveform data. (Note 10) The physical characteristic estimation support device according to Note 9, wherein the predetermined exercise state includes at least one selected from the group consisting of squats, walking, stepping, bending forward, and raising and lowering the heels. (Note 11) The physical characteristic estimation support device according to any one of Notes 8 to 10, wherein the posture analysis information acquisition unit acquires the posture analysis information including a posture analysis image of the subject, and the posture analysis unit further extracts posture features based on the posture analysis image. (Note 12) The physical characteristic estimation support device according to any one of Notes 8 to 11, wherein the physical characteristic estimation unit estimates the physical characteristics of the subject by comparing the posture features with reference feature information. (Note 13) The physical characteristic estimation support device according to any one of Notes 8 to 12, wherein the output unit outputs action instruction information that instructs actions to improve the physical characteristics of the subject based on the physical characteristics.(Note 14) The physical characteristics estimation support device according to Note 13, wherein the output unit outputs further action instruction information after outputting the action instruction information, the posture analysis information acquisition unit acquires posture analysis information of the subject in the predetermined state instructed by the action instruction information, the posture analysis unit extracts the posture features of the subject based on the foot pressure waveform data, and the physical characteristics estimation unit estimates the physical characteristics of the subject based on the posture features. (Note 15) A method for supporting the estimation of physical characteristics, comprising a step for acquiring information for posture analysis, a step for posture analysis, a step for estimating physical characteristics, and an output step, wherein the step for acquiring information for posture analysis acquires information for posture analysis of a subject, the posture analysis information includes foot pressure waveform data, the foot pressure waveform data is information on the change in pressure on the soles of the feet when the subject is in a predetermined state for a predetermined period of time, the posture analysis step extracts posture features of the subject based on the posture analysis information, the physical characteristics estimation step estimates the physical characteristics of the subject based on the posture features, and the output step outputs the physical characteristics of the subject, each step of which is performed by a computer. (Note 16) The method for supporting the estimation of physical characteristics according to Note 15, wherein the step for acquiring information for posture analysis acquires at least one of standing foot pressure waveform data in a standing posture state and exercise foot pressure waveform data in a predetermined exercise state as the foot pressure waveform data. (Note 17) The method for estimating physical characteristics according to Note 16, wherein the predetermined exercise state includes at least one selected from the group consisting of squats, walking, stepping in place, bending forward, and raising and lowering the heels. (Note 18) The method for estimating physical characteristics according to any one of Notes 15 to 17, wherein the posture analysis information acquisition step acquires posture analysis information including a posture analysis image of the subject, and the posture analysis step further extracts posture features based on the posture analysis image. (Note 19) The method for estimating physical characteristics according to any one of Notes 15 to 18, wherein the physical characteristics estimation step estimates the physical characteristics of the subject by comparing the posture features with reference feature information.(Note 20) The method for estimating physical characteristics according to any one of Notes 15 to 19, wherein the output step outputs action instruction information that instructs the subject to take action to improve the subject's physical characteristics based on the physical characteristics. (Note 21) The method for estimating physical characteristics according to Note 20, wherein the output step further outputs action instruction information that instructs the subject to assume a predetermined state after outputting the action instruction information, the posture analysis information acquisition step acquires posture analysis information of the subject in the predetermined state instructed by the action instruction information, the posture analysis step extracts posture features of the subject based on the foot pressure waveform data, and the physical characteristics estimation step estimates the subject's physical characteristics based on the posture features. (Note 22) A computer-readable recording medium that records a body characteristics estimation support program for causing a computer to execute each of the following procedures: (Note 23) The recording medium according to Note 22, wherein the posture analysis information acquisition procedure acquires posture analysis information of a subject, the posture analysis information includes foot pressure waveform data, the foot pressure waveform data is information on the change in pressure on the soles of the feet when the subject is in a predetermined state for a predetermined period of time, the posture analysis procedure extracts posture features of the subject based on the posture analysis information, the body characteristics estimation procedure estimates the body characteristics of the subject based on the posture features, and the output procedure outputs the body characteristics of the subject. (Note 24) The recording medium according to Note 23, wherein the predetermined exercise state includes at least one selected from the group consisting of squats, walking, stepping, bending forward, and raising and lowering the heels. (Note 25) The recording medium according to any one of Notes 22 to 24, wherein the posture analysis information acquisition procedure acquires the posture analysis information including a posture analysis image of the subject, and the posture analysis procedure further extracts posture features based on the posture analysis image.(Note 26) The recording medium according to any one of Notes 22 to 25, wherein the physical characteristics estimation procedure estimates the physical characteristics of the subject by comparing the posture features with reference feature information. (Note 27) The recording medium according to any one of Notes 22 to 26, wherein the output procedure outputs action instruction information that instructs the subject to take action to improve the physical characteristics of the subject based on the physical characteristics. (Note 28) The recording medium according to Note 27, wherein after outputting the action instruction information, the output procedure further outputs action instruction information that instructs the subject to assume a predetermined state, the posture analysis information acquisition procedure acquires posture analysis information of the subject in the predetermined state instructed by the action instruction information, the posture analysis procedure extracts the posture features of the subject based on the foot pressure waveform data, and the physical characteristics estimation procedure estimates the physical characteristics of the subject based on the posture features.
[0053] According to this disclosure, physical characteristics can be easily estimated. For this reason, this disclosure can be suitably used in the medical field, welfare field, and other fields.
[0054] 10 Body characteristic estimation support device 11 Information acquisition unit for posture analysis 12 Posture analysis unit 13 Body characteristic estimation unit 14 Output unit 101 Central processing unit 102 Memory 103 Bus 104 Storage device 105 Input device 106 Output device 107 Communication device
Claims
1. A body characteristics estimation support program that causes a computer to execute each of the following procedures: a procedure for acquiring information for posture analysis, a procedure for posture analysis, a procedure for estimating physical characteristics, and an output procedure, wherein the procedure for acquiring information for posture analysis acquires information for the posture analysis of a subject, the posture analysis information includes foot pressure waveform data, the foot pressure waveform data is information on the change in pressure on the soles of the feet when the subject is in a predetermined state for a predetermined period of time, the posture analysis procedure extracts postural features of the subject based on the posture analysis information, the body characteristics estimation procedure estimates the physical characteristics of the subject based on the postural features, and the output procedure outputs the physical characteristics of the subject.
2. The physical characteristic estimation support program according to claim 1, wherein the procedure for acquiring information for posture analysis acquires at least one of standing foot pressure waveform data in a standing posture state and exercise foot pressure waveform data in a predetermined exercise state as foot pressure waveform data.
3. The physical characteristic estimation support program according to claim 2, wherein the predetermined exercise state includes at least one selected from the group consisting of squats, walking, marching in place, bending forward, and raising and lowering the heels.
4. The posture analysis information acquisition procedure acquires posture analysis information including a posture analysis image of the subject, and the posture analysis procedure further extracts posture features based on the posture analysis image, the body characteristic estimation support program according to any one of claims 1 to 3.
5. The physical characteristic estimation support program according to any one of claims 1 to 4, wherein the physical characteristic estimation procedure estimates the physical characteristics of the subject by comparing the posture characteristics with reference characteristic information.
6. The physical characteristics estimation support program according to any one of claims 1 to 5, wherein the output procedure outputs behavioral instruction information that instructs actions to improve the physical characteristics of the subject based on the physical characteristics.
7. The physical characteristic estimation support program according to claim 6, wherein the output procedure further outputs action instruction information instructing the subject to assume the predetermined state after outputting the action instruction information; the posture analysis information acquisition procedure acquires posture analysis information of the subject in the predetermined state instructed by the action instruction information; the posture analysis procedure extracts posture features of the subject based on the foot pressure waveform data; and the physical characteristic estimation procedure estimates the physical characteristics of the subject based on the posture features.
8. A body characteristic estimation support device comprising: a posture analysis information acquisition unit, a posture analysis unit, a body characteristic estimation unit, and an output unit, wherein the posture analysis information acquisition unit acquires posture analysis information of a subject, the posture analysis information includes foot pressure waveform data, the foot pressure waveform data is information on changes in pressure on the soles of the feet when the subject maintains a predetermined state for a predetermined period of time, the posture analysis unit extracts posture features of the subject based on the posture analysis information, the body characteristic estimation unit estimates the subject's body characteristics based on the posture features, and the output unit outputs the subject's body characteristics.
9. The body characteristic estimation support device according to claim 8, wherein the posture analysis information acquisition unit acquires at least one of standing foot pressure waveform data in a standing posture state and exercise foot pressure waveform data in a predetermined exercise state as foot pressure waveform data.
10. The physical characteristic estimation support device according to claim 9, wherein the predetermined exercise state includes at least one selected from the group consisting of squatting, walking, stepping, bending forward, and raising and lowering the heels.
11. The posture analysis information acquisition unit acquires posture analysis information including a posture analysis image of the subject, and the posture analysis unit further extracts posture features based on the posture analysis image, the body characteristic estimation support device according to any one of claims 8 to 10.
12. The physical characteristics estimation support device according to any one of claims 8 to 11, wherein the physical characteristics estimation unit estimates the physical characteristics of the subject by comparing the posture characteristics with reference characteristic information.
13. The physical characteristics estimation support device according to any one of claims 8 to 12, wherein the output unit outputs action instruction information that instructs actions to improve the physical characteristics of the subject based on the physical characteristics.
14. The physical characteristic estimation support device according to claim 13, wherein the output unit outputs further action instruction information after outputting the action instruction information, the posture analysis information acquisition unit acquires posture analysis information of the subject in the predetermined state instructed by the action instruction information, the posture analysis unit extracts the posture features of the subject based on the foot pressure waveform data, and the physical characteristic estimation unit estimates the physical characteristics of the subject based on the posture features.
15. A method for supporting the estimation of physical characteristics, comprising a step for acquiring information for posture analysis, a step for posture analysis, a step for estimating physical characteristics, and an output step, wherein the step for acquiring information for posture analysis acquires information for the posture analysis of a subject, the posture analysis information includes foot pressure waveform data, the foot pressure waveform data is information on the change in pressure on the soles of the feet when the subject is in a predetermined state for a predetermined period of time, the posture analysis step extracts posture features of the subject based on the posture analysis information, the physical characteristics estimation step estimates the physical characteristics of the subject based on the posture features, and the output step outputs the physical characteristics of the subject, each step of which is performed by a computer.
16. The method for estimating physical characteristics according to claim 15, wherein the step for acquiring information for posture analysis acquires at least one of standing foot pressure waveform data in a standing posture state and exercise foot pressure waveform data in a predetermined exercise state as foot pressure waveform data.
17. The method for estimating physical characteristics according to claim 16, wherein the predetermined exercise state includes at least one selected from the group consisting of squats, walking, stepping, bending forward, and raising and lowering the heels.
18. The method for estimating physical characteristics according to any one of claims 15 to 17, wherein the posture analysis information acquisition step acquires posture analysis information including a posture analysis image of the subject, and the posture analysis step further extracts posture features based on the posture analysis image.
19. The method for estimating physical characteristics according to any one of claims 15 to 18, wherein the physical characteristics estimation step estimates the physical characteristics of the subject by comparing the posture features with reference feature information.
20. The method for estimating physical characteristics according to any one of claims 15 to 19, wherein the output step outputs behavioral instruction information that instructs actions to improve the physical characteristics of the subject based on the physical characteristics.
21. The method for supporting the estimation of physical characteristics according to claim 20, wherein the output step further outputs action instruction information instructing the subject to assume the predetermined state after outputting the action instruction information, the posture analysis information acquisition step acquires posture analysis information of the subject in the predetermined state instructed by the action instruction information, the posture analysis step extracts posture features of the subject based on the foot pressure waveform data, and the physical characteristics estimation step estimates the physical characteristics of the subject based on the posture features.
22. A computer-readable recording medium that records a body characteristics estimation support program for causing a computer to execute each of the following procedures: a procedure for acquiring information for posture analysis, a procedure for posture analysis, a procedure for estimating physical characteristics, and an output procedure, wherein the procedure for acquiring information for posture analysis acquires information for posture analysis of a subject, the posture analysis information includes foot pressure waveform data, the foot pressure waveform data is information on changes in pressure on the soles of the feet when the subject is in a predetermined state for a predetermined period of time, the posture analysis procedure extracts posture features of the subject based on the posture analysis information, the body characteristics estimation procedure estimates the physical characteristics of the subject based on the posture features, and the output procedure outputs the physical characteristics of the subject.
23. The recording medium according to claim 22, wherein the procedure for acquiring information for posture analysis acquires at least one of the following as foot pressure waveform data: standing foot pressure waveform data in a standing posture state and exercise foot pressure waveform data in a predetermined exercise state.
24. The recording medium according to claim 23, wherein the predetermined exercise state includes at least one selected from the group consisting of squats, walking, marching in place, bending forward, and raising and lowering the heels.
25. The recording medium according to any one of claims 22 to 24, wherein the posture analysis information acquisition procedure acquires posture analysis information including a posture analysis image of the subject, and the posture analysis procedure further extracts posture features based on the posture analysis image.
26. The recording medium according to any one of claims 22 to 25, wherein the physical characteristics estimation procedure estimates the physical characteristics of the subject by comparing the posture characteristics with reference characteristic information.
27. The recording medium according to any one of claims 22 to 26, wherein the output procedure outputs behavioral instruction information that instructs actions to improve the physical characteristics of the subject based on the physical characteristics.
28. The recording medium according to claim 27, wherein the output procedure further outputs action instruction information instructing the subject to assume the predetermined state after outputting the action instruction information; the posture analysis information acquisition procedure acquires posture analysis information of the subject in the predetermined state instructed by the action instruction information; the posture analysis procedure extracts posture features of the subject based on the foot pressure waveform data; and the physical characteristics estimation procedure estimates the physical characteristics of the subject based on the posture features.