Information processing device, information processing method, and program

Abstract

To make an appropriate proposal to prevent frailty on the basis of information on the condition of a subject.SOLUTION: An information processing device includes a detection device for detecting a body condition of a subject. The information processing device estimates a physical frailty level of the subject on the basis of an output of the detection device. The information processing device estimates a psychological frailty level of the subject on the basis of the output of the detection device. The information processing device proposes a method for preventing frailty from the physical frailty level and the psychological frailty level.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present disclosure relates to techniques for maintaining the health of a subject. [Background technology]

[0002] Frailty is the Japanese translation of "frailty," and is a concept proposed by the Japan Geriatrics Society in 2014. Specifically, frailty is a condition between a healthy state and a state requiring nursing care, characterized by a decline in physical and cognitive function, and is composed of physical factors such as muscle weakness, mental and psychological factors such as dementia and depression, and social factors such as living alone and financial hardship.

[0003] Even if a subject is frail, there is a good chance that appropriate treatment and prevention will prevent the subject from progressing to a state requiring nursing care. Therefore, it is important to prevent frailty by maintaining a healthy state in at least one of the physical, psychological, and social elements that make up frailty.

[0004] Conventionally, frailty prevention has involved checking the condition of a subject through a questionnaire and suggesting diet, exercise, social participation, etc. to the subject based on the questionnaire results. Patent Document 1 describes a health behavior suggestion system that encourages healthy behavior to prevent frailty based on the subject's voice and movements. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] International Publication No. 2022 / 224621 Summary of the Invention [Problem to be solved by the invention]

[0006] One of the purposes of this disclosure is to provide appropriate suggestions for preventing frailty based on information about the subject's condition. [Means for solving the problem]

[0007] In order to solve the above problem, in one aspect of the present disclosure, there is provided an information processing device comprising: A detection device for detecting a physical condition of a subject is provided, a physical frailty estimation means for estimating a degree of physical frailty of the subject based on an output of the detection device; a psychological frailty estimation means for estimating a degree of psychological frailty of the subject based on an output of the detection device; and a prevention suggestion means for suggesting a method for preventing frailty based on the subject's degree of physical frailty and degree of psychological frailty.

[0008] According to another aspect of the present disclosure, an information processing method executed by an information processing device including a detection device for detecting a physical state of a subject includes: Estimating the subject's degree of physical frailty based on the output of the detection device; Estimating the degree of psychological frailty of the subject based on the output of the detection device; A method for preventing frailty is proposed based on the subject's degree of physical frailty and degree of psychological frailty.

[0009] In yet another aspect of the present disclosure, a computer includes a detection device configured to detect a physical condition of a subject, The program is Estimating the subject's degree of physical frailty based on the output of the detection device; Estimating the degree of psychological frailty of the subject based on the output of the detection device; The computer is caused to execute a process of proposing a method for preventing frailty based on the subject's degree of physical frailty and degree of psychological frailty. [Effects of the Invention]

[0010] According to the present disclosure, appropriate suggestions for preventing frailty can be made based on information regarding the subject's condition. [Brief explanation of the drawings]

[0011] [Figure 1] 1 shows an example of a schematic configuration of a frailty prevention system. [Figure 2] 2 shows an example of the hardware configuration of a server and a user terminal. [Figure 3] FIG. 2 is a block diagram illustrating an example of a functional configuration of a server. [Figure 4] This is a proposed example of a method for preventing frailty. [Figure 5] 10 is a flowchart of a frailty prevention process. DETAILED DESCRIPTION OF THE INVENTION

[0012] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. [Embodiment] (composition) 1 shows an example of a schematic configuration of a frailty prevention system 100 to which an information processing device according to the present disclosure is applied. The frailty prevention system 100 is a system that can make appropriate suggestions for preventing frailty based on information about the condition of a subject.

[0013] Here, frailty is a state between a healthy state and a state requiring nursing care, in which there is a decline in physical and cognitive function, and is composed of physical frailty such as muscle weakness, psychological frailty such as dementia and depression, and social frailty such as living alone or financial hardship.

[0014] In the frailty prevention system 100, a server 1 and a user terminal 2 are communicatively connected via a network 5 such as the Internet. The user terminal 2 is a smartphone, tablet, PC, or the like used by a user (hereinafter also referred to as the "subject") who is concerned about frailty, and captures an image of the subject's face and transmits the image to the server 1. For example, the subject may be an elderly person who is concerned about their health or social status. The user terminal 2 is communicatively connected to a dedicated insole 3 worn by the subject via short-range wireless communication, a predetermined network, or the like, and acquires the subject's walking data from the dedicated insole 3 and transmits it to the server 1.

[0015] The server 1 is an information processing device that processes, stores, and transmits / receives various data, and estimates the subject's degree of psychological frailty and physical frailty from the subject's facial image and walking data. The server 1 also proposes methods for preventing frailty based on the estimated degrees of psychological frailty and physical frailty. Methods for preventing frailty include appropriate activities for maintaining health, such as diet, exercise, and social participation, tailored to the condition of each subject.

[0016] In the present disclosure, the server 1 acquires the facial image of the subject from the user terminal 2 via the network 5, but this is not limited thereto. For example, the facial image may be acquired without going through the network 5 by using an external storage such as a USB (Universal Serial Bus) memory, and the method by which the server 1 acquires the facial image can be set arbitrarily. Furthermore, it is desirable that the facial image is an image of the subject in a state of conversation. In this case, the person interacting with the subject is not limited to a medical professional, but may be, for example, a family member.

[0017] 2(a) is a block diagram showing an example of the hardware configuration of the server 1. As shown in the figure, the server 1 includes an interface 11, a processor 12, a memory 13, a recording medium 14, a display unit 15, and an input unit 16.

[0018] The interface 11 exchanges data with the user terminal 2. The interface 11 is used when receiving facial images and walking data of the subject from the user terminal 2. The interface 11 is also used when the server 1 exchanges data with a predetermined device connected by wire or wirelessly.

[0019] The processor 12 is a computer such as a CPU (Central Processing Unit), and executes a prepared program to control the entire server 1. The processor 12 may be a CPU, a GPU (Graphics Processing Unit), a DSP (Digital Signal Processor), an MPU (Micro Processing Unit), an FPU (Floating Point number Processing Unit), a PPU (Physics Processing Unit), a TPU (Tensor Processing Unit), a quantum processor, a microcontroller, or a combination thereof.

[0020] The memory 13 is composed of a ROM (Read Only Memory), a RAM (Random Access Memory), etc. The memory 13 stores programs executed by the processor 12. The memory 13 is also used as a working memory while the processor 12 is executing various processes.

[0021] The recording medium 14 is a non-volatile, non-temporary recording medium such as a disk-shaped recording medium or semiconductor memory, and is configured to be detachable from the server 1. The recording medium 14 records various programs to be executed by the processor 12. When the server 1 executes the frailty prevention process, the programs recorded on the recording medium 14 are loaded into the memory 13 and executed by the processor 12.

[0022] The display unit 15 displays a predetermined image on, for example, an LCD (Liquid Crystal Display), etc. The input unit 16 includes a keyboard, a mouse, a touch panel, etc., and is used by an operator who manages the server 1.

[0023] 2(b) is a block diagram showing an example of the hardware configuration of the user terminal 2. As shown in the figure, the user terminal 2 includes an interface 21, a processor 22, a memory 23, a recording medium 24, a display unit 25, an input unit 26, and an imaging unit 27.

[0024] The interface 21 exchanges data with the server 1 via the network 5. The interface 21 is used to send facial images and walking data of the subject to the server 1, and to receive appropriate suggestions from the server 1 according to the subject's level of frailty.

[0025] The processor 22 is a computer such as a CPU, and executes a prepared program to control the entire user terminal 2. The processor 22 may be a CPU, a GPU, a DSP, an MPU, an FPU, a PPU, a TPU, a quantum processor, a microcontroller, or a combination thereof.

[0026] The memory 23 is composed of a ROM, a RAM, etc. The memory 23 stores programs executed by the processor 22. The memory 23 is also used as a working memory while the processor 22 is executing various processes.

[0027] The recording medium 24 is a non-volatile, non-transitory recording medium such as a disk-shaped recording medium or semiconductor memory, and is configured to be detachable from the user terminal 2. The recording medium 24 records various programs executed by the processor 22. The display unit 25 is, for example, an LCD, and displays predetermined images. The input unit 26 is, for example, a touch panel, and is used when the user performs predetermined operations. The imaging unit 27 is equipped with a camera and acquires captured still image data and video data.

[0028] 3 is a block diagram showing an example of the functional configuration of the server 1. Functionally, the server 1 includes a physical frailty estimation unit 41, a psychological frailty estimation unit 42, a prevention suggestion unit 43, and an output unit 44. The physical frailty estimation unit 41, the psychological frailty estimation unit 42, the prevention suggestion unit 43, and the output unit 44 are realized by the processor 12 executing a program.

[0029] The physical frailty estimation unit 41 estimates the subject's level of physical frailty. Physical frailty is a state in which mobility and motor functions are impaired due to malnutrition and muscle weakness. The level of physical frailty is the degree of impairment of mobility and motor functions, and is expressed in three levels from 0 to 2 in this embodiment. For example, level 0 is a healthy state with no physical frailty. The higher the level number, the higher the level of physical frailty, with level 1 being a state just short of frailty, known as pre-frailty, and level 2 being a state with physical functional impairment just short of requiring care.

[0030] Specifically, the dedicated insole 3 is an insole that is attached to the shoes of the subject and has a sensor embedded therein. The sensor consists of an IMU (Inertial Measurement Unit), an MPU (Microprocessor), a BLE (Bluetooth Low Energy) module, and a battery.

[0031] The user terminal 2 stores a dedicated app compatible with the dedicated insole 3 in an executable state. The subject registers physical information such as gender, date of birth, height, and weight on the dedicated app by performing a predetermined operation using the user terminal 2. The dedicated app also acquires walking data measured by a sensor in the dedicated insole 3 at predetermined times and transmits it to the server 1 together with the subject's physical information.

[0032] The physical frailty estimation unit 41 calculates gait characteristics such as walking speed and stride length of the subject, and estimated physical abilities such as lower limb muscle strength and balance ability, by analyzing the walking data and physical information acquired from the user terminal 2. Next, the physical frailty estimation unit 41 estimates a disease risk score based on the physical information and the calculated gait characteristics and estimated physical abilities. Next, the physical frailty estimation unit 41 normalizes the estimated disease risk score and classifies it into three levels, from 0 to 2, to estimate the subject's degree of physical frailty.

[0033] The technology for estimating the degree of physical frailty based on walking data detected by a dedicated insole 3 worn by the subject is described, for example, in "PCT / JP2023 / 023043," which has the same patent applicant as the present application, and the description of the specification of this application is incorporated herein.

[0034] The psychological frailty estimation unit 42 estimates the degree of psychological frailty of the subject. Psychological frailty is a state in which cognitive function declines due to aging, depression, or the like. The degree of psychological frailty is the degree of cognitive decline, and in this embodiment, is expressed in three levels from 0 to 2. For example, level 0 is a healthy state with no psychological frailty. The higher the level number, the higher the degree of psychological frailty.

[0035] Specifically, the user terminal 2 acquires a facial image of the subject during a conversation and transmits it to the server 1. If the subject in the facial image is awake and the image has a predetermined length, the psychological frailty estimation unit 42 estimates the cognitive function of the subject based on the facial image. The psychological frailty estimation unit 42 calculates a feature amount related to the degree of eye opening of the subject from the facial image, estimates the cognitive function based on the eye closure rate and eyelid movement speed obtained from the feature amount, and outputs one of "cognitively normal," "mild cognitive impairment," and "dementia" as the estimation result. If "cognitively normal" is output as the estimation result, the psychological frailty estimation unit 42 estimates the degree of psychological frailty as level 0, if "mild cognitive impairment" is output as the estimation result, the psychological frailty degree as level 1, and if "dementia" is output as the estimation result, the psychological frailty degree as level 2.

[0036] The psychological frailty degree estimation unit 42 may output, as the estimation result, not only "cognitively normal," "mild cognitive impairment," or "dementia," but also a score equivalent to the Mini-Mental State Examination (MMSE), which is one of the assessments of cognitive function. In this case, the psychological frailty degree estimation unit 42 may estimate the degree of psychological frailty of the subject by normalizing the output MMSE score equivalent and dividing it into three levels from 0 to 2.

[0037] The technology for estimating the degree of psychological frailty based on facial images of a subject is described, for example, in "PCT / JP2023 / 041209," which has the same patent applicant as the present application, and the description of the specification of this application is incorporated herein by reference.

[0038] The prevention suggestion unit 43 suggests an optimal frailty prevention method for a subject based on the subject's level of physical frailty and level of psychological frailty. Fig. 4 shows an example of a proposed frailty prevention method.

[0039] Specifically, in a first method for proposing a frailty prevention method, the prevention suggestion unit 43 first determines whether the subject's risk of physical frailty and psychological frailty is equal to or greater than a threshold. In this embodiment, the threshold is set to "Level 1." Therefore, the prevention suggestion unit 43 determines that there is a risk of physical frailty if the level of the physical frailty degree is 1 or 2, and determines that there is no risk of physical frailty if the level of the physical frailty degree is 0. Furthermore, the prevention suggestion unit 43 determines that there is a risk of psychological frailty if the level of the psychological frailty degree is 1 or 2, and determines that there is no risk of psychological frailty if the level of the psychological frailty degree is 0.

[0040] Next, the prevention suggestion unit 43 proposes a frailty prevention method, as shown in Figure 4(a), depending on whether or not the subject is at risk for physical frailty and whether or not they are at risk for psychological frailty. For example, if there is no risk of physical frailty but only a risk of psychological frailty, the prevention suggestion unit 43 suggests watching videos or other activities as a way to change mood. The prevention suggestion unit 43 also suggests promoting communication based on videos. In this way, providing opportunities for communication and promoting social frailty prevention, such as isolation and eating alone, can improve the subject's quality of life (QOL). This allows for comprehensive frailty prevention. Furthermore, exercising to prevent physical frailty and watching videos to prevent psychological frailty require the subject's own will, and it is often difficult to act on or continue these activities. On the other hand, social frailty prevention, which stimulates communication and prevents loneliness, is effective because it allows third-party intervention and can be prevented without the subject's own will.

[0041] If there is only a risk of physical frailty but no risk of psychological frailty, the prevention suggestion unit 43 suggests exercise by moving to an external facility to increase muscle strength. The prevention suggestion unit 43 also suggests promoting communication by moving to an external facility.

[0042] If there is no risk of either physical frailty or psychological frailty, the prevention suggestion unit 43 suggests general diet and exercise to maintain health. On the other hand, if there is a risk of both physical frailty and psychological frailty, the subject is at very high risk of needing nursing care, so the prevention suggestion unit 43 suggests contacting medical institutions, facilities, and family members. The prevention suggestion unit 43 also suggests promoting communication through third-party intervention. Here, third-party intervention is not limited to communication with humans, but also includes, for example, conversation with a conversational AI (artificial intelligence) capable of voice recognition.

[0043] In another method for proposing a frailty prevention method, the prevention proposing unit 43 first determines whether the subject is at higher risk of physical frailty or psychological frailty. In this embodiment, the prevention proposing unit 43 compares the numerical values ​​indicating the levels of physical frailty and psychological frailty, and determines that the higher the numerical value, the higher the risk.

[0044] Next, the prevention suggestion unit 43 proposes a frailty prevention method as shown in FIG. 4(b) depending on which of the subject's physical frailty or psychological frailty is at higher risk. For example, if psychological frailty is at higher risk than physical frailty, the prevention suggestion unit 43 suggests watching videos or the like as a way to change one's mood. The prevention suggestion unit 43 also suggests promoting communication based on the videos. In this way, the prevention suggestion unit 43 proposes a method to improve which of the subject's physical frailty or psychological frailty is at higher risk, and social frailty.

[0045] When the degree of physical frailty is higher than the degree of psychological frailty, the prevention suggestion unit 43 suggests exercise by moving to an external facility to increase muscle strength. The prevention suggestion unit 43 also suggests promoting communication by moving to an external facility.

[0046] If the physical frailty level and psychological frailty level are both at the same level of 0, the prevention suggestion unit 43 suggests general diet and exercise to maintain health, as the risk of both is low. On the other hand, if the physical frailty level and psychological frailty level are both at the same level of 1 or 2, the subject is at high risk of becoming dependent on care, so the prevention suggestion unit 43 suggests contacting medical institutions, facilities, and family. The prevention suggestion unit 43 also suggests promoting communication through third-party intervention.

[0047] Note that the present disclosure is not limited to the suggestions shown in Fig. 4, and it is possible to suggest, for example, an effective diet as a method for preventing physical frailty, or a cognitive function test as a method for preventing psychological frailty. In other words, the suggestion content can be set arbitrarily.

[0048] In addition, since social frailty can be estimated from the amount of conversation a subject has, the prevention suggestion unit 43 may determine the risk by estimating the degree of social frailty of the subject in advance based on the amount of conversation with the interactive AI, and may suggest promoting communication based on the assessment results.

[0049] The output unit 44 outputs the proposal made by the prevention proposal unit 43. Specifically, the output unit 44 displays or outputs as sound the proposal made by the prevention proposal unit 43 by transmitting the proposal as data to the user terminal 2. This makes it possible to propose an appropriate frailty prevention method suited to the individual situation of the subject based on the subject's degree of physical frailty and degree of psychological frailty.

[0050] Furthermore, in the above configuration, the physical frailty estimation unit 41, the psychological frailty estimation unit 42, and the prevention suggestion unit 43 of the server 1 are examples of the physical frailty estimation means, the psychological frailty estimation means, and the prevention suggestion means of the present disclosure, respectively.

[0051] (Frailty prevention treatment) Next, a description will be given of the frailty prevention processing by the server 1. Fig. 5 is a flowchart of the frailty prevention processing by the server 1. This processing is realized by the processor 12 shown in Fig. 2 executing a program prepared in advance.

[0052] First, the server 1 acquires walking data of the subject from the dedicated insole 3 via the user terminal 2 (step S101). Next, the server 1 estimates the subject's level of physical frailty based on the walking data (step S102). The server 1 also acquires a facial image of the subject during a conversation from the user terminal 2 (step S103). Next, the server 1 estimates the subject's level of psychological frailty based on the facial image (step S104).

[0053] The server 1 proposes an optimal frailty prevention method for the subject based on the subject's degree of physical frailty and degree of psychological frailty (step S106). Next, the server 1 outputs the proposed frailty prevention method (step S106). Specifically, the server 1 transmits the proposed frailty prevention method as data to the user terminal 2, thereby notifying the subject of an appropriate frailty prevention method according to his or her situation by displaying or outputting audio. In this way, the server 1 completes the frailty prevention process.

[0054] The frailty prevention system 100 can notify the subject of an appropriate frailty prevention method suited to the subject's current situation using data that can be acquired on a daily basis, without placing a burden on the subject, thereby maintaining the subject's health and preventing frailty.

[0055] In this embodiment, the server 1 notifies the subject of the proposed frailty prevention method by outputting it to the user terminal 2, but the present disclosure is not limited to this, and the degree of physical frailty and the degree of psychological frailty may be output and notified together with the frailty prevention method. In this case, the server may notify the degree of physical frailty and the degree of psychological frailty as a level, or as the presence or absence of risk.

[0056] Furthermore, in the present embodiment, the frailty prevention method proposed to the subject is output to the user terminal 2 used by the subject, but the present disclosure is not limited to this, and for example, the server 1 may store in advance the IDs and email addresses of devices used by the subject's family, facilities such as a nursing home where the subject lives, the subject's regular medical institution, etc., and output the frailty prevention method to these terminals to notify those related to the subject. In this case, the server 1 may notify those related to the subject by outputting one or more of the frailty prevention method, the subject's degree of physical frailty, and the subject's degree of psychological frailty to these terminals.

[0057] [First Modification] In this embodiment, the physical frailty estimation unit 41 estimates the level of physical frailty based on walking data acquired from the dedicated insole 3. However, the present disclosure is not limited to this. The physical frailty state may be estimated based on data detected using a detection device that detects the subject's physical condition. The detection device may also include a camera mounted on a smartphone or other device that can capture images of the subject's body. For example, the physical frailty estimation unit 41 may estimate the level of physical frailty based on data such as the number of steps and heart rate acquired from a sensor worn by the subject, such as a pedometer or smartwatch. Furthermore, data on grip strength, which tends to be proportional to the muscle mass of the entire body, may be acquired and the level of physical frailty may be estimated based on the grip strength.

[0058] The physical frailty estimation unit 41 may also estimate the degree of physical frailty based on a facial image of the subject. In this case, the physical frailty estimation unit 41 extracts facial features from the facial image and detects facial muscle movements by analyzing the features. The physical frailty estimation unit 41 estimates the degree of physical frailty based on the facial muscle movements.

[0059] Furthermore, the physical frailty estimation unit 41 may combine a plurality of methods, such as facial images and walking data, to estimate the degree of physical frailty more precisely.

[0060] Furthermore, although the degree of physical frailty is categorized into three levels, from 0 to 2, the present disclosure is not limited to this and the levels can be set arbitrarily. Furthermore, instead of dividing into levels, for example, a disease risk score or a numerical value of grip strength may be applied as the degree of frailty.

[0061] [Second Modification] In this embodiment, the psychological frailty estimation unit 42 estimates the degree of psychological frailty based on a moving image of a face, but the present disclosure is not limited to this, and the degree of psychological frailty may also be estimated based on multiple consecutive still images taken of the subject.

[0062] Furthermore, the psychological frailty estimation unit 42 may estimate the degree of psychological frailty not only based on facial images but also, for example, based on walking data acquired from the dedicated insoles 3 or scores on a spatial awareness test in a neuropsychological test. When making an estimation based on walking data, the psychological frailty estimation unit 42 analyzes the walking data of the subject to detect differences between left and right sides, such as the frequency of hitting one's foot or the tendency to hit the little toe on only one side, and estimates the spatial awareness. Since cognitive function tends to be proportional to spatial awareness, the psychological frailty estimation unit 42 estimates the degree of psychological frailty based on the spatial awareness estimated from the walking data and the scores on the spatial awareness test.

[0063] Furthermore, the psychological frailty estimation unit 42 may combine a plurality of methods, such as facial images and walking data, to estimate the degree of psychological frailty more precisely.

[0064] Furthermore, although the degree of psychological frailty is rated at three levels, from 0 to 2, the present disclosure is not limited to this and the levels can be set arbitrarily. Furthermore, instead of dividing into levels, for example, a numerical value equivalent to the score on a spatial awareness test or the MMSE score may be used as the degree of frailty.

[0065] [Third Modification] The degree of physical frailty may be estimated using a physical frailty estimation model, which is a machine learning model. For example, the physical frailty estimation unit 41 may construct a physical frailty estimation model that receives gait data as input and outputs an optimized degree of physical frailty. Training data is used to construct (generate) the physical frailty estimation model. The training data is data that associates input data input in training the physical frailty estimation model with correct answer data corresponding to the input data. The input data is various gait data, and the correct answer data is the degree of physical frailty. The physical frailty estimation unit 41 trains the physical frailty estimation model to output the degree of physical frailty based on the gait data input as input data. An example of a machine learning method is a model using a neural network. According to this, the physical frailty estimation unit 41 can use the degree of physical frailty output by the physical frailty model as the estimation result.

[0066] [Fourth Modification] The degree of psychological frailty may be estimated using a psychological frailty estimation model, which is a machine learning model. For example, the psychological frailty estimation unit 42 may construct a psychological frailty estimation model that, when a facial image is input, outputs an optimized degree of psychological frailty. Training data is used to construct (generate) the psychological frailty estimation model. The training data is data that associates input data input in training the psychological frailty estimation model with correct answer data corresponding to the input data. The input data is various facial images, and the correct answer data is the degree of psychological frailty. The psychological frailty estimation unit 42 trains the psychological frailty estimation model to output the degree of psychological frailty based on the facial image input as input data. An example of a machine learning method is a model using a neural network. According to this, the psychological frailty estimation unit 42 can use the degree of psychological frailty output by the psychological frailty model as the estimation result.

[0067] [Fifth Modification] In the above embodiment, the subject uses the user terminal 2, but the present disclosure is not limited to this, and the subject may use a user terminal having the functions of the server 1. In this case, the user terminal executes the frailty prevention processing that was previously performed by the server 1, and can estimate the subject's physical frailty, estimate psychological frailty, and make and output frailty prevention suggestions. In other words, the subject's physical frailty, psychological frailty, and frailty prevention suggestions and output can all be performed by the user terminal alone.

[0068] In addition, some or all of the above-described embodiments (including modified examples, the same applies below) can be described as, but are not limited to, the following supplementary notes.

[0069] (Appendix 1) A detection device for detecting a physical condition of a subject is provided, a physical frailty estimation means for estimating a degree of physical frailty of the subject based on an output of the detection device; a psychological frailty estimation means for estimating a degree of psychological frailty of the subject based on an output of the detection device; a prevention suggestion means for suggesting a method for preventing frailty based on the subject's physical frailty level and psychological frailty level; An information processing device comprising:

[0070] (Appendix 2) 2. The information processing device according to claim 1, wherein the detection device is a sensor attached to the body of the subject.

[0071] (Appendix 3) the detection device is an insole sensor that outputs gait data related to the subject's gait; 3. The information processing device according to claim 2, wherein the physical frailty estimation means estimates a degree of physical frailty of the subject based on the walking data.

[0072] (Appendix 4) the detection device is an imaging device that captures an image of the subject's body and outputs an image of the subject's body; The information processing device according to claim 1, wherein the psychological frailty estimation means estimates the degree of psychological frailty of the subject based on a facial image captured of the face of the subject.

[0073] (Appendix 5) 2. The information processing device according to claim 1, wherein the method for preventing frailty is a method for preventing social frailty.

[0074] (Appendix 6) the prevention suggestion means determines whether the subject's physical frailty level and psychological frailty level are equal to or greater than a threshold; The information processing device described in Appendix 1, wherein the method for preventing frailty improves physical frailty, which is a condition in which the degree of physical frailty is above a threshold and therefore the risk is high, psychological frailty, which is a condition in which the degree of psychological frailty is above a threshold and therefore the risk is high, and social frailty.

[0075] (Appendix 7) the prevention suggestion means compares the degree of physical frailty with the degree of psychological frailty and determines whether the risk of physical frailty or psychological frailty is higher; The information processing device according to claim 1, wherein the method for preventing frailty involves improving either the physical frailty or the psychological frailty, whichever is at higher risk, and social frailty.

[0076] (Appendix 8) The information processing device described in Appendix 3, wherein the physical frailty estimation means estimates the subject's degree of physical frailty using a machine learning model that is optimized and trained to output the degree of physical frailty in response to the input of the walking data.

[0077] (Appendix 9) An information processing method executed by an information processing device including a detection device for detecting a physical state of a subject, Estimating the subject's degree of physical frailty based on the output of the detection device; Estimating the degree of psychological frailty of the subject based on the output of the detection device; An information processing method that suggests a method for preventing frailty based on the subject's degree of physical frailty and psychological frailty.

[0078] (Appendix 10) The computer includes a detection device that detects a physical state of the subject; Estimating the subject's degree of physical frailty based on the output of the detection device; Estimating the degree of psychological frailty of the subject based on the output of the detection device; A program that causes the computer to execute a process of proposing a method for preventing frailty based on the subject's degree of physical frailty and degree of psychological frailty.

[0079] (Appendix 11) The information processing device described in Appendix 4, wherein the psychological frailty estimation means estimates the degree of psychological frailty of the subject using a machine learning model that is trained to output an optimized degree of psychological frailty in response to input of a facial image of the subject.

[0080] (Appendix 12) The information processing device described in Appendix 3, wherein the psychological frailty estimation means estimates the degree of psychological frailty of the subject by estimating spatial awareness based on the difference in frequency of the subject hitting their feet between the left and right sides from the walking data.

[0081] (Appendix 13) The information processing device according to claim 4, wherein the physical frailty estimation means estimates the degree of physical frailty of the subject by detecting facial muscle movements from a facial image of the subject.

[0082] (Appendix 14) the detection device is an imaging device that captures an image of the subject's body and outputs an image of the subject's body; the physical frailty estimation means estimates the degree of physical frailty based on gait data of the subject and a facial image obtained by capturing a face of the subject; The information processing device according to claim 3, wherein the psychological frailty estimation means estimates the degree of psychological frailty based on the walking data and the facial image.

[0083] (Appendix 15) The prevention suggestion means suggests one or more of exercise and diet when the risk of physical frailty is high, The prevention suggestion means suggests one or more of watching a video and a cognitive function test when the risk of psychological frailty is high; The information processing device according to claim 6, wherein the prevention suggestion means suggests contacting one or more of a medical institution, a facility, and a family member if there is a high risk of both physical frailty and psychological frailty.

[0084] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above embodiments. Various modifications that would be understood by a person skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. In other words, the present disclosure naturally includes various modifications and alterations that would be possible for a person skilled in the art in accordance with the entire disclosure, including the claims, and the technical ideas. [Explanation of symbols]

[0085] 1 server 2. User terminal 11, 21 Interface 12, 22 processors 13, 23 memory 14, 24 Recording media 15, 25 Display section 16, 26 Input section 27 Imaging unit 41 Physical Frailty Estimation Department 42 Psychological Frailty Estimation Department 43 Prevention Proposal Department 44 Output section 100 Frailty Prevention System

Claims

1. A detection device for detecting a physical condition of a subject is provided, a physical frailty estimation means for estimating a degree of physical frailty of the subject based on an output of the detection device; a psychological frailty estimation means for estimating a degree of psychological frailty of the subject based on an output of the detection device; a prevention suggestion means for suggesting a method for preventing frailty based on the subject's physical frailty level and psychological frailty level; An information processing device comprising:

2. The information processing apparatus according to claim 1 , wherein the detection device is a sensor attached to the body of the subject.

3. the detection device is an insole sensor that outputs gait data related to the subject's gait; The information processing device according to claim 2 , wherein the physical frailty estimation means estimates a degree of physical frailty of the subject based on the walking data.

4. the detection device is an imaging device that captures an image of the subject's body and outputs an image of the subject's body; The information processing device according to claim 1 , wherein the psychological frailty estimation means estimates the degree of psychological frailty of the subject based on a facial image obtained by capturing a face of the subject.

5. The information processing device according to claim 1 , wherein the method for preventing frailty is a method for preventing social frailty.

6. the prevention suggestion means determines whether the subject's physical frailty level and psychological frailty level are equal to or greater than a threshold; The information processing device according to claim 1, wherein the method for preventing frailty improves physical frailty, which is a condition in which the degree of physical frailty is above a threshold and thus the risk is high, psychological frailty, which is a condition in which the degree of psychological frailty is above a threshold and thus the risk is high, and social frailty.

7. the prevention suggestion means compares the degree of physical frailty with the degree of psychological frailty and determines whether the risk of physical frailty or psychological frailty is higher; The information processing device according to claim 1 , wherein the method for preventing frailty is to improve either the physical frailty or the psychological frailty, whichever is at higher risk, and social frailty.

8. The information processing device according to claim 3 , wherein the physical frailty estimation means estimates the subject's degree of physical frailty using a machine learning model that is trained to output the optimized degree of physical frailty in response to the input of the walking data.

9. An information processing method executed by an information processing device including a detection device for detecting a physical state of a subject, Estimating the subject's degree of physical frailty based on the output of the detection device; Estimating the degree of psychological frailty of the subject based on the output of the detection device; An information processing method that suggests a method for preventing frailty based on the subject's degree of physical frailty and psychological frailty.

10. The computer includes a detection device that detects a physical state of the subject; Estimating the subject's degree of physical frailty based on the output of the detection device; Estimating the degree of psychological frailty of the subject based on the output of the detection device; A program that causes the computer to execute a process of proposing a method for preventing frailty based on the subject's degree of physical frailty and degree of psychological frailty.

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