Insole

Abstract

[Problem] To accurately acquire information about pressure applied to a sole. [Solution] An insole for evaluating the walking of a user, the insole comprising a sensor layer including a pressure-sensitive sensor, and at least one of an upper layer disposed more toward a foot than the sensor layer is, and a lower layer disposed more toward the sole than the sensor layer is. At least one of the upper layer and the lower layer has a convex structure at a position corresponding to the position where the pressure-sensitive sensor is disposed in the sensor layer.

Description

insole

[0001] The present invention relates to an insole.

[0002] Methods for obtaining data from the foot during movement are known.

[0003] For example, Patent Document 1 discloses an invention in which data on the pressure acting on the sole of the foot during movement is acquired from a sensor attached to the sole of a shoe.

[0004] Patent No. 6194041

[0005] However, the technology disclosed in Patent Document 1 places sensors in multiple locations, but does not take into account that the soles of the feet have many flat areas, and that when walking slowly, for example, sufficient pressure may not be applied to the sensors, causing the pressure to fall below the detection limit and preventing detection.

[0006] Therefore, an object of the present invention is to obtain information on the pressure acting on the soles of the feet with high accuracy.

[0007] In one aspect of the present invention, the insole is an insole that evaluates a user's walking, and comprises a sensor layer equipped with a pressure sensor, and at least either an upper layer arranged closer to the foot than the sensor layer, or a lower layer arranged closer to the sole than the sensor layer, and at least either the upper layer or the lower layer has a convex structure at a position corresponding to the position where the pressure sensor is arranged in the sensor layer.

[0008] According to the present invention, information on the pressure acting on the soles of the feet can be obtained with high accuracy.

[0009] FIG. 1 is a block diagram showing an evaluation system according to the present embodiment. FIG. 2 is a diagram showing an example of a sensor device 3 according to the present embodiment. FIG. 3 is another diagram showing an example of a sensor device 3 according to the present embodiment. FIG. 4 is another diagram showing an example of a sensor device 3 according to the present embodiment. FIG. 5 is a block diagram showing a hardware configuration of the sensor device 3 according to the present embodiment. FIG. 6 is a block diagram showing a functional configuration of the sensor device 3 according to the present embodiment. FIG. 7 is a diagram showing an example of sensing information according to the present embodiment. FIG. 8 is a block diagram showing a hardware configuration of a server device 1 according to the present embodiment. FIG. 9 is a block diagram showing a functional configuration of the server device 1 according to the present embodiment. FIG. 10 is a diagram showing an example of user information according to the present embodiment. FIG. 11 is a diagram showing an example of sensing information according to the present embodiment. FIG. 12 is a diagram showing an example of status information according to the present embodiment. FIG. 13 is a diagram showing an example of the operation of the evaluation system according to the present embodiment. FIG. 14 is an explanatory diagram of an auxiliary protrusion according to the present embodiment. FIG. 15 is another explanatory diagram of an auxiliary protrusion according to the present embodiment.

[0010] Hereinafter, embodiments of the present invention will be described with reference to the drawings. Note that the embodiments described below do not unduly limit the content of the present invention described in the claims. Furthermore, not all of the components shown in the embodiments are necessarily essential components of the present invention.

[0011] <Summary of the Invention> [Item 1] An insole for evaluating a user's gait, comprising: a sensor layer having a pressure sensor; and at least either an upper layer arranged closer to the foot than the sensor layer; or a lower layer arranged closer to the sole than the sensor layer; wherein at least one of the upper layer and the lower layer has a convex structure at a position corresponding to the position of the pressure sensor in the sensor layer. [Item 2] The insole according to Item 1, wherein the sensor layer comprises a plurality of the pressure sensors, and the convex structure is arranged at a position corresponding to at least one of the pressure sensors. [Item 3] The insole according to Item 1 or 2, wherein the convex structure is arranged on the sensor layer side of either the upper layer or the lower layer. [Item 4] The insole according to any one of Items 1 to 3, wherein the convex structure has a predetermined flexibility. [Item 5] The insole according to Item 2, wherein the convex structure is arranged at a position corresponding to the position of the pressure sensor that detects pressure in at least the lateral longitudinal arch portion.

[0012] 1 is a diagram showing an example of the overall configuration of an evaluation system according to one embodiment of the present invention. The evaluation system of this embodiment includes a server device 1, a user terminal 2, and a sensor device 3. The server device 1 is communicatively connected to the user terminal 2 via a communication network NW. The communication network NW is, for example, the Internet, and is constructed using a public telephone network, a mobile phone network, a wireless communication path, Ethernet (registered trademark), or the like. The sensor device 3 is connected to the user terminal 2 via short-range communication such as Bluetooth (registered trademark).

[0013] ==User Terminal 2== The user terminal 2 is a computer used by the user (or their supporter) who evaluates the state of the user during operation. For example, it is a smartphone, tablet computer, personal computer, etc. The user can access the server device 1 using, for example, an application or web browser running on the user terminal 2.

[0014] ==Sensor Device 3== The sensor device 3 is a computer attached to an insole used in the shoes worn by the user. In this embodiment, an example of an insole is described, but the sensor, etc. described later may be mounted in the sole of the shoe, or may be in the form of a device attached to the shoe or the foot, but is not limited to these.

[0015] FIG. 2 is a diagram showing an example of the configuration of the sensor device 3. Note that FIG. 2 shows the sensor device 3 for the left foot. The sensor device 3 for the right foot may have the same components as the sensor device 3 for the left foot and be configured symmetrically. In this embodiment, the sensor device 3 is an insole used in a shoe, which includes, for example, a computer, a sensor, and a battery. For example, the insole including the sensor device 3 includes a foot-contact layer (3001) that contacts the sole of the user's foot, a shock-absorbing layer (3002) having shock-absorbing properties, a sensor layer (3003) including a pressure-sensitive sensor included in the sensor 305, and an attachment layer 3004 having a gap for attaching a box 30051 formed by fastening the components 3005 and 3011 with screws or the like. Each layer may be waterproof or shock-absorbing. Although not specifically shown in the following drawings, the computer, sensor 305, battery, etc. of the sensor device 3 may be connected by wire. The foot contact layer 3001 and the shock absorbing layer 3002 may be configured as a single member that performs both functions.

[0016] Fig. 3 is a diagram showing an example of the configuration of the sensor device 3. Fig. 3 shows the sensor device 3 for the right foot, and is a side view of the sensor device 3 when viewed from the direction of the arch. The sensor device 3 in this embodiment has a box 30051 at the position of the arch, and it is sufficient that the box 30051 stores a computer, part of the sensor 305, a battery, etc.

[0017] The sensor 305 of this embodiment may be a pressure sensor, for example. The sensor device 3 may be, for example, a known piezo-resistive, capacitive, or optical sensor, but is not limited to these. Since this is a known method, the details of the principle will be omitted.

[0018] 4, the sensor device 3 may have multiple pressure sensors (shown by dotted lines) arranged over the entire surface of the sensor layer 3003, or may be arranged only in a portion such as the toe or heel. Also, multiple sizes of pressure sensors (e.g., A1 and A2) may be prepared, and the location of the pressure sensors may be changed depending on the characteristics of the sole of the foot.

[0019] The sensor device 3 is designed for users with the same foot size, but with individual differences in foot shape, such as differences in finger length and ball of the foot position. For this reason, larger pressure sensors may be placed around the fingers and ball of the foot, where individual differences in foot shape tend to be large, to make it easier to collect data regardless of individual differences. Furthermore, multiple small sensors may be placed in a small area where high-resolution pressure information is desired (such as the heel).

[0020] The sensor device 3 is configured by bonding together a foot contact layer 3001, an impact absorbing layer 3002, a sensor layer 3003, and an attachment layer 3004, and attaching a box 30051. When it is necessary to open the box 30051 for component maintenance or the like, the inside of the box 30051 can be accessed by opening a window provided in the component 3011 (part 30111 in FIG. 3, which is configured as an openable window that does not physically obstruct tools, etc., so that components inside the box 30051 can be repaired or replaced). Furthermore, the components 3006 and 3010 in FIG. 2 may be packings, which may provide waterproofing to the box.

[0021] The sensor device 3 may be configured not only by simply bonding the foot contact layer 3001, the shock absorbing layer 3002, the sensor layer 3003, and the mounting layer 3004, but also by forming a convex portion a few millimeters inward from the end of the mounting layer 3004, forming a concave portion in another layer at a position corresponding to the convex portion, and then fitting and bonding the convex portion and the concave portion together to prevent the layers from shifting during use. Note that the locations of the convex portion and the concave portion are not limited to the above-mentioned positions, and the layer on which the convex portion is formed is not limited to the mounting layer 3004. It is also possible to form a concave portion in the mounting layer 3004 and a convex portion in another layer.

[0022] At least either the shock absorbing layer 3002 or the mounting layer 3004 may have auxiliary convex portions (convex structures) at some or all of the positions corresponding to the positions where the sensors 305 are disposed on the sensor layer 3003. The auxiliary convex portions serve to assist in the transmission of sole pressure to the sensors 305. For example, as shown in an example in FIG. 14 , if a user has a sole structure that makes it difficult for pressure to be transmitted to the sensor 305 due to personal characteristics, if a specific part of the sole is very soft and makes it difficult for pressure to be transmitted to the sensor device 305, or if the user walks or moves in a way that makes it difficult for pressure to be transmitted to the sensor 305, the pressure applied to the sensor 305 may be small and below the detection limit, making it impossible to detect or accurately detect pressure (left side of FIG. 14 ). In these cases, the auxiliary convex portions (3013) assist in the transmission of sole pressure to the sensors 305, as shown in the right side of FIG. 14 .

[0023] The sensor 305 may have a concept of front and back, for example. In this case, the sensor 305 senses when pressure is applied to the front side, and does not sense when pressure is applied to the back side. When the sensor 305 is arranged with the front side facing upward (toward the sole of the foot), an auxiliary convex portion may be provided on the lower surface of the shock absorbing layer 3002. When the sensor 305 is arranged with the front side facing downward (toward the ground), an auxiliary convex portion may be provided on the upper surface of the mounting layer 3004.

[0024] The auxiliary protrusion may have a predetermined hardness and a predetermined flexibility. The auxiliary protrusion needs to have the hardness necessary to transmit pressure to the sensor 305. On the other hand, if the auxiliary protrusion has too high a hardness, the applied pressure may exceed the upper limit of detection of the sensor 305. For this reason, as shown in FIG. 15 , the auxiliary protrusion may have flexibility to the extent that it deforms to disperse pressure when a large pressure is applied (right side of FIG. 15 ). The auxiliary protrusion may be made of an elastomer such as rubber, urethane, or silicone.

[0025] In addition, the auxiliary convex portion may be arranged at a position on the shock absorbing layer 3002 or the mounting layer 3004 that corresponds to a position intended for sensing a relatively soft part of the sole, for example, the position of a sensor 305 (for example, at least one of the sensors 305 shown as A1 to A4 in Figure 4) arranged in the lateral longitudinal arch part of the sole.

[0026] Although the auxiliary convex portion has been described as at least a part of either the shock absorbing layer 3002 or the mounting layer 3004, it may be configured as an independent member between the shock absorbing layer 3002 and the sensor layer 3003, or between the sensor layer 3003 and the mounting layer 3004. In that case, it is configured so that its position does not change by being bonded or fixed to one or more of the shock absorbing layer 3002, the sensor layer 3003, and the mounting layer 3004.

[0027] FIG. 5 is a diagram illustrating an example of the hardware configuration of the sensor device 3. Note that the illustrated configuration is an example, and other configurations may also be used. The sensor device 3 includes a CPU 301, a memory 302, a storage device 303, a communication interface 304, a sensor 305, and an output device 306. The storage device 303 stores various data and programs, such as a hard disk drive, a solid-state drive, or a flash memory. The communication interface 104 is an interface for connecting to the user terminal 2, such as a short-range communication interface for Bluetooth (registered trademark) and BLE (Bluetooth Low Energy), a USB (Universal Serial Bus) connector for serial communication, or an RS232C connector. Note that the interface may also be an interface for connecting to a communication network NW, such as an adapter for connecting to Ethernet (registered trademark), a modem for connecting to a public telephone line network, or a wireless communication device for wireless communication, and may be connected to the user terminal 2 or the server device 1. The sensor 305 acquires data and is, for example, a pressure sensor and an IMU (6-axis sensor). The output device 106 outputs data and the device status and is, for example, a display, LED, speaker, vibrator, etc. The sensor device 3 may have a battery that shares power, and the battery may be charged by externally supplying power via a USB port or by contactless charging, but is not limited to these methods.

[0028] 6 is a functional block diagram of the sensor device 3. The sensor device 3 includes processing units, namely, a sensing unit 311, a communication unit 312, and a control unit 313, as well as a sensing information storage unit 331.

[0029] The sensing information storage unit 331 stores information acquired by the sensor 305. The sensing information includes information on pressure, acceleration, angular velocity, geomagnetism, and time, associated with a user ID, as shown in an example in Fig. 7. The information acquired by the sensor 305 is considered to be primary information.

[0030] The functions of each processing unit of the sensing unit 311, the communication unit 312, and the control unit 313 will be described below.

[0031] The sensing unit 311 acquires information about the user's feet using the sensor 305. The sensing unit 311 acquires data measuring the pressure on the soles of the feet using a pressure sensor included in the sensor 305, and the acceleration, angular velocity, and geomagnetism of the feet using an IMU, and stores the data in the sensing information storage unit 331. Note that in this embodiment, the term "foot" may include a foot wearing shoes, and for example, when it is stated that a foot is in contact with the ground, "foot" may be read as "shoe" to mean that the shoe is in contact with the ground.

[0032] The communication unit 312 transmits the sensing information acquired by the sensing unit 311 to the user terminal 2. In this embodiment, since the sensor device 3 and the user terminal 2 are connected via short-range communication such as Bluetooth (registered trademark), the communication unit 312 transmits the sensing information to the user terminal 2 through this environment. The transmission may be performed in real time, or may be performed when the control unit 313 receives an instruction to transmit the sensing information from the user terminal 2.

[0033] The control unit 313 performs various controls of the sensor device 3. The control unit 313 controls, for example, the power supply of the sensor device 3. The control unit 313 may acquire information from the sensor 305, for example, and turn on or off the power supply or functions when it determines that the sensor device 3 has reached a predetermined state. For example, the control unit 313 may turn off the power supply of the sensor device 3 when a shoe equipped with the sensor device 3 is turned upside down while the sensor device 3 is powered on and a predetermined time has elapsed. Furthermore, the control unit 313 may stop the functions of the sensing unit 311 and the communication unit 312 or turn off the power supply when the sensor device 3 has detected the user's foot movement and the foot movement stops for a predetermined time.

[0034] ==Server Device 1== The server device 1 may be, for example, a general-purpose computer such as a workstation or a personal computer, or may be logically realized by cloud computing. In this embodiment, for convenience of explanation, one server is illustrated as an example, but this is not limited to this and multiple servers may be used.

[0035] FIG. 8 is a diagram illustrating an example of the hardware configuration of the server device 1. Note that the illustrated configuration is an example, and other configurations may also be used. The server device 1 includes a CPU 101, a memory 102, a storage device 103, a communication interface 104, an input device 105, and an output device 106. The storage device 103 stores various data and programs, and is, for example, a hard disk drive, a solid-state drive, or a flash memory. The communication interface 104 is an interface for connecting to a communication network NW, and is, for example, an adapter for connecting to Ethernet (registered trademark), a modem for connecting to a public telephone network, a wireless communication device for wireless communication, a USB (Universal Serial Bus) connector or an RS232C connector for serial communication, etc. The input device 105 is, for example, a keyboard, a mouse, a touch panel, a button, a microphone, etc. for inputting data. The output device 106 is, for example, a display, a printer, a speaker, etc. for outputting data. Each functional unit of the server device 1 described below is realized by the CPU 101 reading a program stored in the storage device 103 into the memory 102 and executing it, and each storage unit of the server device 1 is realized as part of the storage area provided by the memory 102 and the storage device 103.

[0036] 9 is a functional block diagram of the server device 1. The server device 1 includes processing units, namely, a user information acquisition unit 111, a sensing information acquisition unit 112, an analysis unit 113, a state information acquisition unit 114, a model generation unit 115, an evaluation unit 116, and an evaluation presentation unit 117, and storage units, namely, a user information storage unit 131, a sensing information storage unit 132, a state information storage unit, and a model storage unit.

[0037] The user information storage unit 131 stores the user information acquired by the user information acquisition unit 111. As shown in an example in Fig. 10 , the user information includes, but is not limited to, information such as name, age, sex, height, and weight in association with a user ID.

[0038] The sensing information storage unit 132 acquires the sensing information acquired by the sensing information acquisition unit 112 and stores it in the sensing information storage unit 132. As shown in an example in Fig. 11 , the sensing information includes information such as pressure, acceleration, angular velocity, geomagnetism, and time, in association with a user ID.

[0039] The condition information storage unit 133 acquires information about the user's condition. As shown in Fig. 12 as an example, the condition information includes information such as disease state, physical condition, images of the user in motion, fatigue level, physical load, proficiency level, lower back pain state, dementia state, center of gravity position, frailty state, whether the user has stumbled or fallen, and progress and effects of rehabilitation.

[0040] The model information storage unit 134 stores the prediction model generated by the model generation unit described later.

[0041] The functions of each processing unit, namely, the user information acquisition unit 111, the sensing information acquisition unit 112, the analysis unit 113, the state information acquisition unit 114, the model generation unit 115, the evaluation unit 116, and the evaluation presentation unit 117, will be described below.

[0042] As an example, the user information acquisition unit 111 acquires basic information about the user from the user terminal 2 via the communication network NW and stores the information in the user information storage unit 131. The communication for sending and receiving may be either wired or wireless, and any communication protocol may be used as long as the communication between the two devices is possible.

[0043] As an example, the sensing information acquisition unit 112 acquires the sensing information acquired by the sensor device 3 from the user terminal 2 via the communication network NW, and stores the information in the sensing information storage unit 132. The communication in the transmission and reception may be either wired or wireless, and any communication protocol may be used as long as the communication between the devices can be performed.

[0044] The analysis unit 113 analyzes the state of the user's feet during movement based on the sensing information.

[0045] The analysis unit 113 analyzes the user's movements and foot characteristics during movements based on, for example, at least any of the primary information. The analysis includes, but is not limited to, the landing position, landing angle, landing load, contact angle, contact load transfer, plantar load, kick-off load, kick-off angle, COP (Center of Pressure), COB (Center of Balance), stride length, walking speed, cadence (number of steps in a given time, etc.), toe direction, foot lift height, number of steps, activity distance, pronation state and degree, supination state and degree, upright plantar load, activity time, and exercise amount. Note that the information on characteristics obtained as a result of the analysis of the primary information by the analysis unit 113 is referred to as secondary information.

[0046] The analysis unit 113 analyzes that the foot has landed when it detects, for example, from the value of a pressure sensor, that a load has been applied to the sole of the foot. For example, the analysis unit 113 may analyze the timing when the acceleration in the approximately vertical direction detected by an acceleration sensor becomes zero as the timing when the foot has landed. Based on the value of the pressure sensor at the timing when the foot has landed, the analysis unit 113 may analyze which part of the sole of the foot has landed (landing position). For example, the analysis unit 113 may analyze that the foot has landed on the heel if the value of the pressure sensor for the heel increases before the value of other parts. Furthermore, the analysis unit 113 may analyze the angle of the foot when it lands (landing angle) based on the value of an angular velocity sensor at the timing when the foot has landed. Furthermore, the analysis unit 113 may analyze, for example, from the value of the pressure sensor at the timing when the foot has landed, which part of the foot is under load (landing load).

[0047] In this embodiment, the period from when the foot lands on the ground, floor, etc. until the foot kicks off is expressed as the foot being in contact with the ground, floor, etc. The analysis unit 113 may, for example, analyze the load transfer at the time of contact by continuously extracting values ​​from multiple pressure sensors along a time axis while the foot is in contact. The analysis unit 113 may also analyze the angle of the foot during contact from values ​​from an angular velocity sensor, for example. The analysis unit 113 may, for example, analyze whether the foot is in a pronation state (inward pronation) and the degree of pronation, or whether the foot is in a supination state (outward pronation) and the degree of pronation from values ​​from multiple pressure sensors, angular velocity sensors, etc. during contact.

[0048] The analysis unit 113 may analyze the kicking position and the kicking load by, for example, analyzing the amount of load applied to which position on the sole of the foot when the foot kicks off and leaves the ground after contact. The angle of the foot when the foot kicks off and leaves the ground and the direction of the toes may also be analyzed from values ​​of an angular velocity sensor or the like.

[0049] For example, the analysis unit 113 may analyze the distance that the foot moves in the front-back, left-right, and vertical directions of the body from the time the foot kicks off until the foot lands, based on the value of an acceleration sensor (the distance can be determined by integrating the acceleration twice). Furthermore, the analysis unit 113 may analyze the movement speed of the foot in the front-back, left-right, and vertical directions of the body, based on the time data and the distance information, for example.

[0050] The analysis unit 113 may, for example, represent the location of the center of pressure (COP) of the foot during contact in coordinates based on the value of the pressure sensor. The analysis unit may acquire the COP when the user is moving, or may acquire the COP when the user is standing upright.

[0051] The analysis unit 113 may analyze, for example, the position of the center of balance (COB) of the body during movement. The analysis unit may analyze the relationship between the positions of both feet based on information about the accelerations of both feet, and further analyze the position of the COB based on information about the COP of each foot.

[0052] The analysis unit 113 may analyze, for example, the rotational state (yaw, roll, pitch) of the user's feet at a specific time point during a movement from values ​​acquired by an angular velocity sensor. The rotational state of the feet is referred to as the foot posture.

[0053] For example, the analysis unit 113 may analyze that the user is walking (or running) when a pattern in which a pressure sensor on one foot detects pressure and, after a predetermined time, a pressure sensor on another foot detects pressure is detected a predetermined number of times. The analysis unit 113 may analyze the number of steps based on the number of times the pattern occurs. The analysis unit 113 may also analyze the length of one step (stride) from the distance traveled by the foot from kicking off to landing, or may analyze the distance traveled by the user by adding up the lengths of each step. Furthermore, the analysis unit 113 may analyze the user's movement speed by dividing the distance by the time from the start to the end of the pattern. The analysis unit 113 may also analyze the cadence based on the number of times the pattern is detected within a predetermined time.

[0054] For example, the analysis unit 113 may analyze the time during which the sensor device 3 continues to detect any foot movement continuously or intermittently as the activity time. Furthermore, the analysis unit 113 may analyze the movement the user is making during the activity time as walking, running, or the like, by analyzing the pattern, and may analyze the amount of exercise of the user by multiplying the activity time by a predetermined coefficient corresponding to the movement.

[0055] The analysis unit 113 may present the secondary information to the user terminal 2. The analysis unit 113 may present the analyzed secondary information as values ​​or coordinates, or may superimpose a diagram showing a direction such as an arrow (the magnitude of the value may be expressed by changing the display method such as line thickness or color) on a schematic diagram of the whole or part of the human body including the feet if the analysis result is a direction, or a heat map or the like of the analysis results of the pressure sensor values, and further change them in time series and present them on the user terminal 2, but is not limited to these methods.

[0056] As an example, the status information acquisition unit 114 acquires basic information about the user from the user terminal 2 via the communication network NW and stores the information in the user information storage unit 131. The communication for sending and receiving the information may be wired or wireless, and any communication protocol may be used as long as the communication between the users can be performed. Note that the status information may be input to the server device 1 via the communication network NW by a third party who acquires information about the user's status, or the status information may be input directly to the server device 1 by a business operator who uses the server device 1 to conduct business.

[0057] The state information may be, for example, subjective information about the user's state obtained from the user, or objective information about the user's state.

[0058] The condition information may be, for example, a physical condition. The physical condition may be, for example, information on the state of cognitive function, the degree of progression of dementia, the state of frailty, the state of lower back pain, tripping, falling, etc., or may be, but is not limited to, the results of a cognitive function test or a subjective report of a state such as lower back pain that the condition information acquisition unit 114 presents to the user terminal 2, or information on the results of examinations, diagnoses, observations, and tests by medical professionals or the like that are acquired from an information terminal used by the medical professionals or the like.

[0059] The state information may be, for example, a degree of fatigue, and the state information acquiring unit 114 may acquire the state information by presenting to the user terminal 2 a form in which the user selects a level of subjective fatigue, or by presenting a psychological scale to the user terminal 2 and acquiring the degree of fatigue by analyzing the selection received from the user. Furthermore, the state information acquiring unit 114 may acquire, as the degree of fatigue, information on the results of physiological evaluations such as reaction time and awakening rhythm, or biochemical evaluations such as blood tests, acquired from the user terminal 2 or an information terminal used by a medical professional or the like who supports the user's rehabilitation, treatment, or the like, but is not limited to these.

[0060] The status information may be, for example, information obtained by a third party evaluating the user's actions. The evaluation may be, for example, but is not limited to, the state or degree of proficiency, progress, or improvement of the user's actions, obtained from an information terminal used by the third party.

[0061] The status information may be, for example, information on an image (including video) of the user while in motion. The image may be information acquired by Kinect (registered trademark), a motionless capture camera, or the like. The image information may also be information such as the position of the user's center of gravity output by analyzing the image. The image may be, for example, an image of the user carrying a heavy object, an image of the user providing care, an image of the user walking, or the like, but is not limited to these.

[0062] The status information may be, for example, information from a sensor worn by the user or attached to the body or clothing, such as, but not limited to, an acceleration sensor, an angular velocity sensor, a vibration meter, a pulse rate meter, a heart rate meter, etc.

[0063] The model generation unit 115 generates a prediction model that predicts the state of the user.

[0064] As an example, the model generation unit 115 generates a prediction model that predicts a user's state based on one or more types of primary information and state information. The model generation unit 115 uses one or more types of primary information and state information as training data, and generates a prediction model that uses one or more types of primary information of the user of the type used as the training data as input and the state information as output.

[0065] As an example, the model generation unit 115 generates a prediction model that predicts the user's state based on one or more types of secondary information and state information. The model generation unit 115 uses one or more types of secondary information and the state information as training data, and generates a prediction model that uses one or more types of secondary information of the user of the type used as the training data as input and the state information as output.

[0066] An example of a prediction model generated by the model generation unit 115 will be described below.

[0067] The model generation unit 115 generates a prediction model that predicts the degree of progression of dementia based on, for example, primary information or secondary information and information on the degree of progression of dementia. The model generation unit 115 uses, for example, one or more types of primary information or secondary information (e.g., one or more of toe direction, stride length, and foot lift height) and information on the degree of progression of dementia as training data, and generates a prediction model that uses, as input information, one or more types of primary information or secondary information of the user of the type used as the training data, and outputs the degree of progression of dementia.

[0068] The model generation unit 115 generates a prediction model that predicts a fatigue level based on, for example, primary information or secondary information and fatigue level information. The model generation unit 115 uses, for example, one or more types of primary information or secondary information and fatigue level information as training data, uses one or more types of primary information or secondary information of the user of the type used as the training data as input information, and generates a prediction model that outputs a fatigue level.

[0069] The model generation unit 115 generates a prediction model that predicts a state of frailty or a state of lower back pain based on, for example, primary information or secondary information and information on the state of frailty or the state of lower back pain, and the effects of a treatment such as rehabilitation. The model generation unit 115 uses, for example, one or more types of primary information or secondary information and information on the state of frailty or the state of lower back pain, and the effects of a treatment such as rehabilitation, as training data, and generates a prediction model that uses, as input information, one or more types of primary information or secondary information of the user of the type used as the training data, and outputs the state of frailty or the state of lower back pain, and the effects of a treatment such as rehabilitation.

[0070] The model generation unit 115 generates a prediction model that detects tripping or falling or predicts the risk of tripping or falling, based on, for example, primary information or secondary information and information about the state of tripping or falling. The model generation unit 115 generates a prediction model that detects tripping or falling or predicts the risk of tripping or falling, using, for example, training data, one or more types of primary information or secondary information (e.g., the ground contact angle) from a predetermined time before the tripping or falling. The model generation unit 115 generates a prediction model that detects tripping or falling or predicts the risk of tripping or falling, using, as input information, one or more types of primary information or secondary information about the user of the type used as training data.

[0071] The model generation unit 115 generates a prediction model that predicts proficiency based on, for example, primary information or secondary information and state-related information called proficiency. The model generation unit 115 generates a prediction model that uses, for example, one or more types of primary information or secondary information and proficiency information as training data, uses one or more types of primary information or secondary information of the user of the type used as the training data as input information, and outputs proficiency.

[0072] The model generation unit 115 generates a prediction model that predicts the position of the center of gravity based on, for example, primary information or secondary information and position information of the center of gravity estimated from an image of the user in motion. The model generation unit 115 uses, for example, one or more types of primary information or secondary information and the position information of the center of gravity as training data, uses one or more types of primary information or secondary information of the user of the type used as the training data as input information, and generates a prediction model that outputs the position of the center of gravity.

[0073] The model generation unit 115 generates a prediction model that predicts the load on the body or the center of gravity based on, for example, primary information or secondary information and information on the load on the body or information on the center of gravity analyzed from information from sensors attached to the body. The model generation unit 115 uses, for example, one or more types of primary information or secondary information and the information on the load on the body or the center of gravity as training data, and generates a prediction model that uses, as input information, one or more types of primary information or secondary information of the user of the type used as the training data, and outputs the load on the body or the center of gravity.

[0074] The model generation unit 115 generates a prediction model that determines whether or not a specific user is walking, based on, for example, primary information or secondary information of the specific user. The model generation unit 115 uses, for example, one or more types of primary information or secondary information of the specific user as training data, uses one or more types of primary information or secondary information of the user of the type used as the training data as input information, and generates a prediction model that outputs whether or not the specific user is walking.

[0075] As an example, the model generation unit 115 generates a prediction model that predicts a user's state based on one or more types of primary information or secondary information, state information, environmental information, and / or user information. The model generation unit 115 uses one or more types of primary information or secondary information, state information, environmental information, and / or user information as training data, and generates a prediction model that takes one or more types of primary information or secondary information, environmental information, and / or user information of the user used as the training data as input and outputs state information. The environmental information is information about the environment in which the user is operating, and may include, for example, road conditions (degree of gradient, presence or absence of pavement (asphalt, gravel, sand, etc.), during rainfall, after rainfall, during snowfall, after snowfall, etc.), and the like. Learning can be performed by adding environmental information to the example of the model generation method described above.

[0076] The evaluation unit 116 evaluates the state of the user.

[0077] The evaluation unit 116 evaluates the state of the user using the prediction model generated by the model generation unit 115. The evaluation unit 116 inputs one or more types of primary information or secondary information of the user, of the type used as training data, and environmental information and / or user information into the prediction model, and evaluates the state of the user based on the output state information.

[0078] The evaluation presenting unit 117 presents the evaluation of the user's condition made by the evaluation unit 116 to the user terminal 2. The evaluation presenting unit 117 may present advice information linked to the evaluation and stored in the server device 1 together with the evaluation to the user terminal 2. The advice information may be text information, audio information, image information, video information, or the like.

[0079] FIG. 13 is a diagram illustrating the operation of the evaluation system of this embodiment.

[0080] The sensor device 3 acquires sensing information from the sensor (3011). The sensor device 3 transmits the sensing information to the user terminal 2 (3012). The user terminal 2 acquires user information (2011). The user terminal 2 acquires the sensing information (2012). The user terminal 2 transmits the user information and sensing information to the server device 1 (2013). The server device 1 acquires the user information and sensing information (1011). The server device 1 analyzes the sensing information (1012). The user terminal 2 transmits state information to the server device 1 (2014). The server device 1 acquires the state information (1013). The server device 1 generates a prediction model that predicts the user's state based on some or all of the acquired information (1014). The sensor device 3 acquires sensing information to be used for evaluation (3013). The sensor device 3 acquires sensing information to be used for evaluation and transmits it to the user terminal 2 (3014). The user terminal 2 transmits the sensing information to be used for the evaluation to the server device 1 (2015). The server device 1 acquires the sensing information to be used for the evaluation (3015). The server device 1 performs the evaluation using the prediction model (1016). The server device 1 presents the evaluation results to the user terminal 2 (1017). The user terminal 2 acquires the evaluation results (2016).

[0081] Although the preferred embodiments of the present disclosure have been described in detail above with reference to the accompanying drawings, the technical scope of the present disclosure is not limited to such examples. It is clear that a person skilled in the art of the present disclosure can conceive of various modified or altered examples within the scope of the technical idea described in the claims, and it is understood that these also naturally fall within the technical scope of the present disclosure.

[0082] Other examples are given below.

[0083] The sensor device 3 may be in the form of a device that is attached to a shoe or the sole of a foot, rather than inside the insole, in which case the insole does not need to include the attachment layer 3004 for attaching the sensor device 3. In that case, the auxiliary protrusion may be provided on the shoe itself to which the insole is attached.

[0084] The sensor device 3 may not necessarily include the shock absorbing layer 3002. In that case, for example, the socks worn by the user may include auxiliary convex portions.

[0085] The auxiliary protrusions may be provided at least at some or all of the positions of either the shock absorbing layer 3002 or the mounting layer 3004 corresponding to the positions where the sensors 305 are disposed on the sensor layer 3003, but may also be provided at other positions. For example, the auxiliary protrusions may be provided so as to extend over multiple sensors 305.

[0086] When the sensor layer 3003 is formed from a material having a predetermined hardness, the position where the sensor 305 is arranged on the sensor layer 3003 or the surrounding area thereof may be formed from a material having a softer hardness than the other parts, rather than the auxiliary convex portion.

[0087] The devices described in this specification may be realized as a single device, or may be realized by a plurality of devices (e.g., cloud servers) some or all of which are connected via a network. For example, the CPU and storage device of the server device 1 may be realized by different servers connected to each other via a network.

[0088] The series of processes performed by the device described herein may be implemented using software, hardware, or a combination of software and hardware. A computer program for implementing each function of the server device 1 according to this embodiment may be created and installed on a PC or the like. A computer-readable recording medium storing such a computer program may also be provided. Examples of the recording medium include a magnetic disk, an optical disk, a magneto-optical disk, and a flash memory. The computer program may also be distributed, for example, via a network, without using a recording medium.

[0089] Additionally, the processes described herein do not necessarily have to be performed in the order described, some process steps may be performed in parallel, additional process steps may be employed, and some process steps may be omitted.

[0090] Furthermore, the effects described herein are merely descriptive or exemplary and are not limiting. In other words, the technology according to the present disclosure may achieve other effects that will be apparent to those skilled in the art from the description of this specification, in addition to or in place of the above-described effects.

[0091] 1 Server device 2 User terminal 3 Sensor device NW Network 101 Processor 102 Memory 103 Storage device 104 Communication interface 105 Input device 106 Output device 111 User information acquisition unit 112 Sensing information acquisition unit 113 Analysis unit 114 Status information acquisition unit 115 Model generation unit 116 Evaluation unit 117 Evaluation presentation unit 131 User information storage unit 132 Sensing information storage unit 133 Status information storage unit 134 Model storage unit 301 Processor 302 Memory 303 Storage device 304 Communication interface 305 Sensor 306 Output device 311 Sensing unit 312 Communication unit 313 Control unit 331 Sensing information storage unit 3001 Contact layer 3002 Shock absorbing layer 3003 Sensor layer 3004 Mounting layer

Claims

1. An insole for evaluating a user's gait, comprising: a sensor layer equipped with a pressure sensor; and at least either an upper layer arranged closer to the foot than the sensor layer, or a lower layer arranged closer to the sole than the sensor layer, wherein at least either the upper layer or the lower layer has a convex structure at a position corresponding to the position where the pressure sensor is arranged in the sensor layer.

2. The insole according to claim 1, wherein the sensor layer includes a plurality of the pressure-sensitive sensors, and the convex structure is disposed at a position corresponding to at least one of the pressure-sensitive sensors.

3. The insole according to claim 1 or 2, wherein the convex structure is arranged on the sensor layer side of either the upper layer or the lower layer.

4. The insole according to claim 1 or 2, wherein the convex structure has a predetermined flexibility.

5. The insole according to item 2, wherein the convex structure is disposed at a position corresponding to the position of the pressure sensor that detects pressure at least in the lateral longitudinal arch portion.

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