Physical characteristic estimation support program, physical characteristic estimation support device, physical characteristic estimation support method, and recording medium

Abstract

We provide a body characteristic estimation support program that can easily estimate various physical characteristics of an individual. [Solution] The physical characteristics estimation support program of this disclosure includes a procedure for acquiring information for posture analysis, a posture analysis procedure, a physical characteristics estimation procedure, and an output procedure. The procedure for acquiring posture analysis information described above involves acquiring posture analysis information of the subject, The aforementioned posture analysis information includes foot pressure waveform data, The foot pressure waveform data is information about the change in pressure on the soles of the feet when the subject maintains a predetermined state for a predetermined period of time. The posture analysis procedure extracts the posture features of the subject based on the posture analysis information, The aforementioned physical characteristics estimation procedure estimates the physical characteristics of the subject based on the postural features, The output procedure outputs the physical characteristics of the subject.

Description

Technical Field

[0006] , , , ,

[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.

Background Art

[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. For this reason, in order to prevent low back pain and the like, based on the weight of the object, the height and weight of the wearer, and the trunk angle of the wearer, the intervertebral disc compression force of the wearer is continuously estimated, and the elapsed time is measured in time series for each category according to the load level, and a lumbar load evaluation device that predicts the risk of occurrence of low back pain symptoms in the wearer during the working time of the heavy muscle work of handling the object is known (Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, the technology of Patent Document 1 has the problem that a special wearable motion assistance device is required to estimate the risk of onset 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.

Means for Solving the Problems

[0006] To achieve the above object, the body characteristic estimation support program of the present disclosure is This includes procedures for acquiring information for posture analysis, posture analysis, body characteristic estimation, and output procedures. The procedure for acquiring posture analysis information described above involves acquiring posture analysis information of the subject, The aforementioned posture analysis information includes foot pressure waveform data, The foot pressure waveform data is information about the change in pressure on the soles of the feet when the subject maintains a predetermined state for a predetermined period of time. The posture analysis procedure extracts the posture features of the subject based on the posture analysis information, The aforementioned physical characteristics estimation procedure estimates the physical characteristics of the subject based on the postural features, The output procedure outputs the physical characteristics of the subject. This is a physical characteristics estimation support program that allows a computer to execute each step.

[0007] The physical characteristics estimation support device disclosed herein is It includes a posture analysis information acquisition unit, a posture analysis unit, a body characteristics estimation unit, and an output unit. The aforementioned posture analysis information acquisition unit acquires posture analysis information of the subject, The aforementioned posture analysis information includes foot pressure waveform data, The foot pressure waveform data is information about the change 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 the posture characteristics 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 characteristics, The output unit outputs the physical characteristics of the subject.

[0008] The method for supporting the estimation of physical characteristics in this disclosure is: This process includes a process for acquiring information for posture analysis, a posture analysis process, a body characteristics estimation process, and an output process. The aforementioned posture analysis information acquisition step acquires posture analysis information of the subject, The aforementioned posture analysis information includes foot pressure waveform data, The foot pressure waveform data is information about the change in pressure on the soles of the feet when the subject maintains a predetermined state for a predetermined period of time. The posture analysis step extracts the 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 characteristics, The output step outputs the physical characteristics of the subject. This method involves each step being performed by a computer.

[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. [Effects of the Invention]

[0010] According to this disclosure, various physical characteristics of an individual can be easily estimated. [Brief explanation of the drawing]

[0011] [Figure 1] Figure 1 is a block diagram showing the configuration of an example of the physical characteristics estimation support device of this disclosure. [Figure 2] 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] Figure 3 is a flowchart showing an example of the procedure using the physical characteristics estimation support program of this disclosure. [Figure 4] Figure 4 is a schematic diagram showing an example of the foot pressure measurement locations for a subject in this disclosure. [Modes for carrying out the invention]

[0012] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. The present disclosure is not limited to the following embodiments. In the following figures, the same parts are denoted by the same reference numerals. Also, unless otherwise specified, the descriptions of the respective embodiments can be mutually referred to, and the configurations of the respective embodiments can be combined unless otherwise specified. In the present disclosure, each drawing may apply to one or more embodiments.

[0013] [Embodiment 1] The body characteristic estimation support program of the present disclosure is a program for causing a computer to execute a posture analysis information acquisition procedure, a posture analysis procedure, and a body characteristic estimation procedure. The body characteristic estimation support program of the present disclosure can also be said to be a program for causing a computer to function as a posture analysis information acquisition procedure, a posture analysis procedure, and a body characteristic estimation procedure. Further, the body characteristic estimation support program of the present disclosure can also be said to be a program for causing a computer to execute each step of the body characteristic estimation support method described later, for example.

[0014] The posture analysis information acquisition procedure acquires posture analysis information of the 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 in a state where the subject takes a predetermined state for a predetermined time, The posture analysis procedure calculates a posture analysis score 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 analysis score.

[0015] Each of the aforementioned steps can be reinterpreted, for example, by substituting "step" with "process." The physical characteristics estimation support program of this disclosure may also 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. The physical characteristics estimation support program of this disclosure (for example, also called a programming product or program product) may also be delivered, for example, from an external computer. The "delivery" may be, for example, delivery via a communication network or delivery via a wired connected device. The physical characteristics estimation support program of this disclosure may be installed and executed on the delivered 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, and a physical characteristic estimation unit 13. 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, and the physical characteristic estimation unit 13 can each execute, for example, the posture analysis information acquisition procedure, the posture analysis procedure, and the physical characteristic estimation 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 lines, 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 (registered trademark), Bluetooth (registered trademark), Local 5G, LPWA, etc. The 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 be, for example, incorporated into a server as a system. Furthermore, the device 10 may be, for example, a personal computer (PC, e.g., desktop or notebook), smartphone, tablet terminal, etc., on which the program of this disclosure 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. If 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 described herein will be explained in more detail using Figure 3. Figure 3 is a flowchart showing an example of each step in the physical characteristics estimation support program described herein.

[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 to measure foot pressure, for example, as shown in Figure 4, the subject may be divided into areas such as the forefoot, hindfoot, outer side, and inner side, or the foot pressure of the big toe (2A), ball of the thumb (2B), middle forefoot (2C), hypothenar (2D), heel (2E), outside the heel (2F), and arch (2G) may be measured. Specifically, it is preferable that the posture analysis information acquisition unit 11 measures the pressure of the big toe (2A), inner forefoot (ball of the big toe (2B)), outer forefoot (ball of the little toe (2D)), inner midfoot, outer midfoot, inner hindfoot, and outer 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 measured over time 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 associated with 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 associated with 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 information indicating whether the subject's body is healthy (normal) or abnormal, and information indicating predetermined features such as lordosis, kyphosis, knee-in, and knee-out.

[0032] Tables 1-6 below show specific examples of standard feature information, but this disclosure is not limited to these examples.

[0033] [Table 1]

[0034] [Table 2]

[0035] [Table 3]

[0036] [Table 4]

[0037] [Table 5]

[0038] [Table 6]

[0039] Furthermore, the body characteristic estimation unit 13 may, for example, input the posture analysis information into the body characteristic estimation model to estimate the subject's body characteristics. In this case, the body characteristic estimation model is a model that has been trained by machine learning, using the body characteristics as the correct labels for the posture features, to output an estimation result of the subject's body characteristics when the subject's posture features are input.

[0040] The aforementioned physical characteristic estimation model may, for example, be stored in memory 102 and storage device 104 in advance, or it may be acquired from an external source via a communication network.

[0041] The aforementioned physical characteristic estimation model can be generated, for example, by machine learning using a pair of the subject's posture features and the subject's physical characteristics as training data (learning information). The aforementioned machine learning can employ, for example, a known machine learning method. Specific examples of statistical models that can be used in the machine learning include, for example, simple linear regression models, Ridge regression, Lasso regression, Elastic Net regression, LightGBM (Light Gradient Boosting Machine), Logistic regression, general additive models, random forest regression, rule-fit regression, gradient boosting trees, extra trees, support vector regression, Gaussian process regression, k-nearest neighbor regression, kernel ridge regression, neural networks, etc. The physical characteristic estimation model may, for example, be a pre-generated, trained model. Furthermore, the trained model may be a trained model (derived model) retrained using the training data and an already generated trained model. Additionally, the trained model may be a trained model obtained by transfer learning using a trained model generated with the training data, or a trained model generated by model compression of a trained model generated with the training data.

[0042] The physical characteristic estimation model may be a network that includes, for example, an input layer for inputting the subject's posture features, an output layer for outputting the estimation results of the physical characteristics, and at least one intermediate layer 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 pre-trained models constructed with other learning algorithms may also be used.

[0043] The output unit 14 then outputs the physical characteristics of the subject (S4, output process). 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, text data, or 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 that reflects the physical characteristics. The image information is not particularly limited and may, for example, be an avatar image. The avatar image is image information for displaying a hypothetical appearance of the user, and may be a character image. In general, it is difficult for people to recognize abnormalities even if there are abnormalities in their own body balance. In this disclosure, by outputting image information (in particular, an avatar image) that reflects the physical characteristics of the user, the user can, for example, visually understand the discrepancy between the body balance they assume and their actual body balance. The output unit 14 may also, for example, reflect the posture estimated from the input foot pressure in the avatar image.

[0045] As an example of its use, if the device 10 has this configuration, it can, for instance, be used to implement a game that controls the movement of an avatar image by taking the user's foot pressure data as input.

[0046] The output unit 14 may output, for example, action instruction information that instructs actions to improve the subject's physical characteristics based on those physical characteristics. The action instruction information may include, for example, information for training to improve physical characteristics. The action instruction information may be recorded in the storage unit of the device 10, with each piece of information linked to a specific type of physical characteristic. This allows the output unit 14 to output action instruction information linked to the subject's physical characteristics.

[0047] The output unit 14 may, for example, output further action instruction information after outputting the action instruction information, instructing the subject to assume the predetermined state. In this case, the posture analysis information acquisition unit 11 of the device 10 may, for example, acquire posture analysis information of the subject in the predetermined state instructed by the action instruction information, the posture analysis unit 12 may extract posture features of the subject based on the foot pressure waveform data, and the body characteristic estimation unit 13 may estimate the body characteristics of the subject based on the posture features.

[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] <Note> Some or all of the above embodiments may be described as follows, but are not limited to the following: (Note 1) This includes procedures for acquiring information for posture analysis, posture analysis, body characteristic estimation, and output procedures. The procedure for acquiring posture analysis information described above involves acquiring posture analysis information of the subject, The aforementioned posture analysis information includes foot pressure waveform data, The foot pressure waveform data is information about the change in pressure on the soles of the feet when the subject maintains a predetermined state for a predetermined period of time. The posture analysis procedure extracts the posture features of the subject based on the posture analysis information, The aforementioned physical characteristics estimation procedure estimates the physical characteristics of the subject based on the postural features, The output procedure outputs the physical characteristics of the subject. A program that assists in estimating physical characteristics to enable a computer to perform each step of the procedure. (Note 2) The posture analysis information acquisition procedure is a body characteristic estimation support program as described in Appendix 1, which acquires at least one of the foot pressure waveform data, namely standing foot pressure waveform data in a standing posture 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 described in Appendix 2, 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 4) The procedure for acquiring posture analysis information includes acquiring posture analysis information, including posture analysis images of the subject, The posture analysis procedure is a body characteristic estimation support program described in any of the appendices 1 to 3, which further extracts posture features based on the posture analysis images. (Note 5) The physical characteristic estimation procedure is a physical characteristic estimation support program described in any of the appendices 1 to 4, which estimates the physical characteristics of the subject by comparing the posture features with reference feature information. (Note 6) The output procedure is a physical characteristic estimation support program according to any one of the appendices 1 to 5, which outputs behavioral instruction information that instructs actions to improve the physical characteristics of the subject based on the physical characteristics. (Note 7) The output procedure, after outputting the action instruction information, further outputs action instruction information instructing the system to assume the predetermined state. The procedure for acquiring posture analysis information involves acquiring posture analysis information of a subject in a predetermined state as instructed by the action instruction information. The posture analysis procedure extracts the postural features of the subject based on the foot pressure waveform data, The physical characteristics estimation procedure is a physical characteristics estimation support program as described in Appendix 6, which estimates the physical characteristics of the subject based on the postural features. (Note 8) It includes a posture analysis information acquisition unit, a posture analysis unit, a body characteristics estimation unit, and an output unit. The aforementioned posture analysis information acquisition unit acquires posture analysis information of the subject, The aforementioned posture analysis information includes foot pressure waveform data, The foot pressure waveform data is information about the change 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 the posture characteristics 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 characteristics, The output unit outputs the physical characteristics of the subject. Physical characteristics estimation support device. (Note 9) The posture analysis information acquisition unit 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, as described in Appendix 8, for the body characteristic estimation support device. (Note 10) The physical characteristic estimation support device according to Appendix 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 posture analysis information acquisition unit acquires the posture analysis information, including the posture analysis image of the subject, The posture analysis unit further extracts posture features based on the posture analysis image, and is a body characteristic estimation support device according to any one of appendices 8 to 10. (Note 12) The physical characteristics estimation support device according to any one of the appendices 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. (Note 13) The physical characteristics estimation support device according to any one of appendices 8 to 12, wherein the output unit outputs behavioral instruction information that instructs actions to improve the physical characteristics of the subject based on the physical characteristics. (Note 14) After outputting the action instruction information, the output unit further outputs action instruction information instructing the system to assume the predetermined state. The posture analysis information acquisition unit acquires posture analysis information of a subject in a predetermined state as instructed by the action instruction information. The posture analysis unit extracts the postural features of the subject based on the foot pressure waveform data, The physical characteristics estimation unit estimates the physical characteristics of the subject based on the posture characteristics, as described in Appendix 13. (Note 15) This process includes a process for acquiring information for posture analysis, a posture analysis process, a body characteristics estimation process, and an output process. The aforementioned posture analysis information acquisition step acquires posture analysis information of the subject, The aforementioned posture analysis information includes foot pressure waveform data, The foot pressure waveform data is information about the change in pressure on the soles of the feet when the subject maintains a predetermined state for a predetermined period of time. The posture analysis step extracts the 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 characteristics, The output step outputs the physical characteristics of the subject. A method for supporting the estimation of physical characteristics, in which each step is performed by a computer. (Note 16) The method for estimating physical characteristics as described in Appendix 15, wherein the step for acquiring information for posture analysis acquires at least one of standing foot pressure waveform data in a standing posture and exercise foot pressure waveform data in a predetermined exercise state as foot pressure waveform data. (Note 17) The method for estimating physical characteristics as described in Appendix 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 posture analysis information acquisition step acquires the posture analysis information, including the posture analysis image of the subject, The posture analysis step further extracts posture features based on the posture analysis image, the method for estimating physical characteristics as described in any of appendices 15 to 17. (Note 19) The physical characteristic estimation step is a method for estimating physical characteristics according to any one of the appendices 15 to 18, wherein the physical characteristics estimation step estimates the physical characteristics of the subject by comparing the posture characteristics with reference characteristic information. (Note 20) The method for estimating physical characteristics according to any one of the appendices 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. (Note 21) The output step, after outputting the action instruction information, further outputs action instruction information instructing to take the predetermined state, The posture analysis information acquisition step acquires posture analysis information of a subject in a predetermined state as instructed by the action instruction information. The posture analysis step extracts the postural features of the subject based on the foot pressure waveform data, The physical characteristics estimation step is the physical characteristics estimation support method described in Appendix 20, which estimates the physical characteristics of the subject based on the posture characteristics. (Note 22) This includes procedures for acquiring information for posture analysis, posture analysis, body characteristic estimation, and output procedures. The procedure for acquiring posture analysis information described above involves acquiring posture analysis information of the subject, The aforementioned posture analysis information includes foot pressure waveform data, The foot pressure waveform data is information about the change in pressure on the soles of the feet when the subject maintains a predetermined state for a predetermined period of time. The posture analysis procedure extracts the posture features of the subject based on the posture analysis information, The aforementioned physical characteristics estimation procedure estimates the physical characteristics of the subject based on the postural features, The output procedure outputs the physical characteristics of the subject. A computer-readable recording medium containing a program that supports the estimation of physical characteristics, used to instruct a computer to perform each step of the procedure. (Note 23) The recording medium described in Appendix 22 is used to acquire information for posture analysis, wherein the recording medium 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. (Note 24) The recording medium according to Appendix 23, 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 25) The procedure for acquiring posture analysis information includes acquiring posture analysis information, including posture analysis images of the subject, The posture analysis procedure further extracts posture features based on the posture analysis image, using a recording medium as described in any of appendices 22 to 24. (Note 26) The recording medium described in any of Appendix 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 appendices 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. (Note 28) The output procedure, after outputting the action instruction information, further outputs action instruction information instructing the system to assume the predetermined state. The procedure for acquiring posture analysis information involves acquiring posture analysis information of a subject in a predetermined state as instructed by the action instruction information. The posture analysis procedure extracts the postural features of the subject based on the foot pressure waveform data, The recording medium described in Appendix 27 estimates the physical characteristics of the subject based on the postural features. [Industrial applicability]

[0052] 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. [Explanation of symbols]

[0053] 10 Physical characteristics estimation support device 11 Posture analysis information acquisition unit 12 Posture analysis section 13 Physical characteristics estimation section 14 Output section 101 Central Processing Unit 102 memory 103 Bus 104 Storage device 105 Input device 106 Output device 107 Communication devices

Claims

1. This includes procedures for acquiring information for posture analysis, posture analysis, body characteristic estimation, and output procedures. The procedure for acquiring posture analysis information described above involves acquiring posture analysis information of the subject, The aforementioned posture analysis information includes foot pressure waveform data, The foot pressure waveform data is information about the change in pressure on the soles of the feet when the subject maintains a predetermined state for a predetermined period of time. The posture analysis procedure extracts the posture features of the subject based on the posture analysis information, The aforementioned physical characteristics estimation procedure estimates the physical characteristics of the subject based on the postural features, The output procedure outputs the physical characteristics of the subject. A program that assists in estimating physical characteristics to enable a computer to perform each step of the procedure.

2. The body 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, stepping in place, bending forward, and raising and lowering the heels.

4. The procedure for acquiring posture analysis information includes acquiring posture analysis information, including posture analysis images of the subject, The posture analysis procedure further extracts posture features based on the posture analysis image, according to any one of claims 1 to 3, for the body characteristic estimation support program.

5. The physical characteristics estimation support program according to any one of claims 1 to 3, wherein the physical characteristics 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 3, 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 output procedure, after outputting the action instruction information, further outputs action instruction information instructing the system to assume the predetermined state. The procedure for acquiring posture analysis information involves acquiring posture analysis information of a subject in a predetermined state as instructed by the action instruction information. The posture analysis procedure extracts the postural features of the subject based on the foot pressure waveform data, The physical characteristics estimation support program according to claim 6, wherein the physical characteristics estimation procedure estimates the physical characteristics of the subject based on the postural characteristics.

8. It includes a posture analysis information acquisition unit, a posture analysis unit, a body characteristics estimation unit, and an output unit. The aforementioned posture analysis information acquisition unit acquires posture analysis information of the subject, The aforementioned posture analysis information includes foot pressure waveform data, The foot pressure waveform data is information about the change 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 the posture characteristics 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 characteristics, The output unit outputs the physical characteristics of the subject. Physical characteristics estimation support device.

9. This process includes a process for acquiring information for posture analysis, a posture analysis process, a body characteristics estimation process, and an output process. The aforementioned posture analysis information acquisition step acquires posture analysis information of the subject, The aforementioned posture analysis information includes foot pressure waveform data, The foot pressure waveform data is information about the change in pressure on the soles of the feet when the subject maintains a predetermined state for a predetermined period of time. The posture analysis step extracts the 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 characteristics, The output step outputs the physical characteristics of the subject. A method for supporting the estimation of physical characteristics, in which each step is performed by a computer.

10. This includes procedures for acquiring information for posture analysis, posture analysis, body characteristic estimation, and output procedures. The procedure for acquiring posture analysis information described above involves acquiring posture analysis information of the subject, The aforementioned posture analysis information includes foot pressure waveform data, The foot pressure waveform data is information about the change in pressure on the soles of the feet when the subject maintains a predetermined state for a predetermined period of time. The posture analysis procedure extracts the posture features of the subject based on the posture analysis information, The aforementioned physical characteristics estimation procedure estimates the physical characteristics of the subject based on the postural features, The output procedure outputs the physical characteristics of the subject. A computer-readable recording medium containing a program that supports the estimation of physical characteristics, used to instruct a computer to perform each step of the procedure.

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