Biological information detection device, biological information measurement system, insole, and footwear

Abstract

A biological information detection device according to one embodiment of the present technology comprises a sensor sheet and a control unit. The sensor sheet has a sensor layer that is capable of detecting pressure distribution and an intermediate layer that is disposed on the surface of the sensor layer and that is elastically deformable, and detects a pressure distribution waveform including a slope component of foot pressure of a user input to the sensor layer via the intermediate layer. The control unit calculates the slope component on the basis of the pressure distribution waveform.

Description

Biological information detection device, biological information measurement system, insole and footwear

[0001] The present technology relates to a technology for a biological information detection device that detects information about foot and body movements and the like.

[0002] There is known a technology that enables assistance with stable walking by estimating a floor reaction force vector from foot pressure and simultaneously displaying the skeletal direction of the foot. For example, Patent Document 1 discloses a biometric system that includes a camera that photographs a subject, a pressure information acquisition unit that detects the pressure value of at least one sole of the subject, a skeletal direction vector calculation unit that calculates a skeletal direction vector of the subject photographed by the camera, a floor reaction force vector calculation unit that calculates a floor reaction force vector based on pressure information from the pressure information collection unit, and an analysis result output unit that displays the skeletal direction vector and the floor reaction force vector in an overlapping manner.

[0003] Furthermore, Patent Document 2 discloses a technology for acquiring foot pressure distribution information of at least one foot of a subject while walking using a pressure sensor provided in a planar manner in an insole, and analyzing the ground contact state of the subject's foot using information on the pressure distribution of the toes and the pressure distribution of the sole extracted from the acquired foot pressure distribution information.

[0004] JP 2021-65393 A JP 2020-18365 A

[0005] The technology described in Patent Document 1 uses a camera to calculate the subject's skeletal direction vector, so it is essential to use it in combination with other equipment such as a camera to detect, for example, the inclination of the subject's feet. Also, the technology described in Patent Document 2 can only obtain limited information such as the vertical load and the center of gravity position of the sole of the foot, so it cannot quantitatively evaluate the walking state.

[0006] In view of the above circumstances, an object of the present technology is to provide a biometric information detection device, a biometric information measurement system, an insole, and footwear that can quantitatively evaluate walking conditions without requiring a camera or the like.

[0007] According to one aspect of the present technology, there is provided a biological information detecting device including a sensor sheet and a control unit. The sensor sheet includes a sensor layer capable of detecting a pressure distribution and an intermediate layer disposed on a surface of the sensor layer and capable of elastically deforming, and detects a pressure distribution waveform including a gradient component of a user's foot pressure input to the sensor layer via the intermediate layer. The control unit calculates the gradient component based on the pressure distribution waveform.

[0008] In this way, this technology makes it possible to calculate, for example, the inclination of the foot when walking, thereby enabling quantitative evaluation of force vectors, foot twist, walking state indicators, KAM (Knee Adduction Moment), and the like.

[0009] The control unit may be configured to separately calculate a tilt component in the forefoot region, which is the region on the toe side, and a tilt component in the rearfoot region, which is the region on the heel side, based on the pressure distribution waveform, thereby making it possible to estimate the position of the user's knee and the tilt of the foot when walking.

[0010] The control unit may further calculate at least one of the vertical loads and the center of gravity positions of the forefoot and rearfoot based on the pressure distribution waveforms.

[0011] The control unit may further calculate a vertical load in a midfoot region, which is a region between the forefoot region and the rearfoot region, based on the pressure distribution waveform.

[0012] The sensor layer may be an electrostatic sensor having a plurality of capacitive elements.

[0013] The arrangement interval of the plurality of capacitive elements in the forefoot portion may be narrower than the arrangement interval of the plurality of capacitive elements in the rearfoot portion.

[0014] The number of the plurality of capacitive elements in the forefoot portion may be greater than the number of the plurality of capacitive elements in the rearfoot portion.

[0015] The sensor layer may include a sensor electrode layer in which the plurality of capacitance elements are arranged in a matrix, a reference electrode layer connected to a reference potential, and a deformation layer disposed between the sensor electrode layer and the reference electrode layer.

[0016] The control unit may separate the pressure distribution waveform into a first region where the slope component is relatively dominant and a second region where the shear component is relatively dominant, and calculate the slope component based on the first region.

[0017] The control unit may set a region of the pressure distribution waveform where the pressure value is equal to or greater than a predetermined threshold as a first region, and set a region where the pressure value is less than the predetermined threshold as a second region.

[0018] The control unit may acquire image data including the pressure distribution waveform, and perform image processing on the image data to set the predetermined threshold value.

[0019] The control unit may calculate an inclination angle of the first region with respect to a direction parallel to the sensor sheet, and calculate the inclination component based on the inclination angle.

[0020] A biological information measurement system according to one embodiment of the present technology includes a sensor sheet, a control unit, and a processing device. The sensor sheet has a sensor layer capable of detecting a pressure distribution and an elastically deformable intermediate layer disposed on the surface of the sensor layer, and detects a pressure distribution waveform including a gradient component of a user's foot pressure input to the sensor layer via the intermediate layer. The control unit calculates the gradient component based on the pressure distribution waveform. The processing device measures the gradient or posture of the user's foot based on the output of the control unit.

[0021] The biometric information measurement system may further include at least one of an inertial sensor, a vibration sensor, and a camera that detects the movement of the user.

[0022] The processing device may generate image information for displaying on a screen at least one of the vertical load on the user's foot, the position of the center of gravity, and the force of the tilt component, or changes over time thereof.

[0023] According to one aspect of the present technology, there is provided an insole including a sensor sheet and a control unit. The sensor sheet includes a sensor layer capable of detecting a pressure distribution and an intermediate layer disposed on the surface of the sensor layer and capable of elastically deforming, and detects a pressure distribution waveform including a gradient component of a user's foot pressure input to the sensor layer via the intermediate layer. The control unit calculates the gradient component based on the pressure distribution waveform.

[0024] According to one aspect of the present technology, there is provided footwear including an insole. The insole includes a sensor sheet and a control unit. The sensor sheet includes a sensor layer capable of detecting a pressure distribution and an elastically deformable intermediate layer disposed on the surface of the sensor layer, and detects a pressure distribution waveform including a gradient component of a user's foot pressure input to the sensor layer via the intermediate layer. The control unit calculates the gradient component based on the pressure distribution waveform.

[0025] 1 is a block diagram showing a configuration of a biological information measuring system according to an embodiment of the present technology. FIG. 1 is a schematic perspective view showing an example of application of a sensor sheet to an insole in the biological information detection system. FIG. 2 is a schematic side cross-sectional view of the sensor sheet. FIG. 3 is a schematic side cross-sectional view showing a cross-sectional structure of a sensor layer in the sensor sheet. FIG. 4 is a schematic plan view showing a sensor electrode layer in the sensor layer. FIG. 5 is an explanatory diagram of an electrode structure of a sensing unit in the sensor layer. FIG. 6 is a schematic plan view showing an example of an arrangement of the sensor layer in the plane of the insole. FIG. 7 is a schematic plan view showing another example of an arrangement of the sensor layer in the plane of the insole. FIG. 8 is a schematic plan view of a main part showing yet another example of an arrangement of the sensor layer in the plane of the insole. FIG. 9 is a diagram for explaining a concept related to a processing algorithm of a control unit in the biological information detection system. FIG. 10 is a diagram for explaining a concept related to a processing algorithm of the control unit. FIG. 11 is a diagram for explaining a concept related to a processing algorithm of the control unit. FIG. 12 is a flowchart showing processing of the control unit. FIG. 13 is a diagram showing sensor data including a mountain-shaped pressure distribution waveform. FIG. 14 is a diagram showing a state when an approximation plane of a first region in the pressure distribution waveform gradually tilts from a state close to parallel to a horizontal plane. FIG. 15 is a schematic diagram showing a state when the approximation plane of the first region tilts. 1 is a schematic diagram showing a state when the center of gravity position of the second region in the pressure distribution waveform moves in a planar direction. FIG. 2 is an experimental result showing an example of a time change in the gradient component of the sole load acting on the sensor sheet (insole) when a user is walking. FIG. 3 is a flowchart showing a part of the processing procedure in the bioinformation detection system. FIG. 4 is a flowchart explaining a part of the processing procedure executed in the processing device in the bioinformation detection system. FIG. 5 is a flowchart explaining another part of the processing procedure executed in the processing device in the bioinformation detection system. FIG. 6 shows an example of output in a heat map of pressure distribution. In the figure, (A) is the raw output of sensor data, and (B) is an image divided into regions by image processing. FIG. 7 is an explanatory diagram of KAM. FIG. 8 is an explanatory diagram of a rocker function.27 shows the center of gravity of each region in the heat map of sensor data at an arbitrary time, showing the time change of the position and tilt angle of each center of gravity shown in FIG. 27, where (A) shows the position in the x direction, (B) shows the position in the y direction, (C) shows the angle in the roll direction, (D) shows the angle in the pitch direction, and (E) shows the magnitude of the vertical load.

[0026] Hereinafter, embodiments of the present technology will be described with reference to the drawings.

[0027] 1 is a block diagram showing a configuration of a biological information measurement system 100 according to an embodiment of the present technology. The biological information measurement system 100 includes a pressure detection device 10 and a processing device 20.

[0028] The pressure detection device 10 is configured as a biological information detection device according to the present technology, and includes a sensor sheet 11 , a control unit 12 , a storage unit 13 , a communication unit 14 , and a battery 15 .

[0029] The sensor sheet 11 is a pressure distribution sensor placed on the soles of one or both legs of a user (subject). The sensor sheet 11 detects the in-plane distribution of the magnitude and direction (inclination) of the load applied from the soles at a predetermined period (for example, 10 to 100 milliseconds) and outputs the results to the control unit 12. The sensor sheet 11 is typically placed on footwear worn by the user, such as shoes, sandals, or slippers.

[0030] The control unit 12 executes various calculations based on various programs stored in the memory unit 13, and comprehensively controls each unit of the pressure detection device 10. Typically, the control unit 12 calculates various components of the force applied to the sensor sheet 11 based on the pressure distribution waveform acquired by the sensor sheet 11.

[0031] In this embodiment, the control unit 12 calculates the various components of the force, including a pressure component, a tilt component, and a shear component. The pressure component is a component (vertical load) in the Z-axis direction in a three-axis Cartesian coordinate system, and indicates the magnitude of the force applied downward to the sensor sheet 11. The tilt component is an inclination with respect to a direction parallel to the sensor sheet 11, and is expressed, for example, by an angle θ from the Z-axis direction or an angle φ from the X-axis direction in a spherical coordinate system (see FIGS. 16 and 17 for θ and φ), and indicates the direction (φ) and degree of inclination (θ) at which the force is applied.

[0032] The shear component is a component in a direction parallel to the XY plane in a three-axis Cartesian coordinate system, and refers to the magnitude of the force applied in a planar direction (XY plane) when an object (e.g., a finger) applying force to the sensor sheet 11 moves in a planar direction (XY plane) without sliding on the surface of the sensor sheet 11 (some sliding is acceptable). In other words, when an object (e.g., a finger) applying force to the sensor sheet 11 moves in a planar direction (XY plane) without sliding on the surface of the sensor sheet 11 (some sliding is acceptable), the layered structure on the sensor sheet 11 undergoes shear deformation (see FIGS. 12 and 13). The magnitude of this shear deformation correlates with the magnitude of the force applied in the planar direction, and this relationship is used to calculate the magnitude of the force in the planar direction.

[0033] The control unit 12 is realized by hardware or a combination of hardware and software. The hardware is configured as part or all of the control unit 12, and examples of this hardware include a central processing unit (CPU), a graphics processing unit (GPU), a vision processing unit (VPU), a digital signal processor (DSP), a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), or a combination of two or more of these.

[0034] The storage unit 13 includes a non-volatile memory that stores various programs and various data required for processing by the control unit 12, and a volatile memory that is used as a work area for the control unit 12.

[0035] The communication unit 14 is a communication module for transmitting and receiving data between the control unit 12 and the processing device 20. Communication performed by the communication circuit of the communication unit 14 may be wireless or wired. Wireless communication may be a communication method using electromagnetic waves or infrared rays, communication using an electric field, or communication using sound waves. Specific communication methods include communication methods using bands ranging from several hundred MHz (megahertz) to several GHz (gigahertz), such as "Wi-Fi (registered trademark)," "Zigbee (registered trademark)," "Bluetooth (registered trademark)," "Bluetooth Low Energy," and "UART." Proximity wireless communication may also be used, such as near-field wireless communication (NFC). Proximity wireless communication refers to near-field wireless communication of, for example, a few centimeters to 1 meter. Examples of such communication methods include NFC, communication methods using RFID (Radio Frequency Identifier) ​​such as ISO / IEC 14443, and infrared communication.

[0036] The battery 15 is configured as a power supply for the pressure detection device 10. The battery 15 may be any of various secondary batteries such as a lithium ion secondary battery, an electric double layer capacitor, a lithium ion capacitor, a polyacenic semiconductor (PAS) capacitor, a ceramic capacitor, a film capacitor, an aluminum electrolytic capacitor, a tantalum capacitor, or the like. A combination of these storage elements may be used depending on the purpose. The battery 15 may be charged wirelessly, for example, from a power supply coil installed on the floor, which allows the battery 15 to be charged while wearing shoes. Furthermore, a power generation system using a piezoelectric element that converts shoe deformation into electrical energy may also be employed.

[0037] The processing device 20 is a calculation device for measuring the inclination or posture of the user's foot based on the output of the control unit 12. The processing device 20 is typically configured as a computer (PC terminal or tablet terminal) including a CPU and memory. The processing device 20 is connected to a display unit 31 that displays the measurement results, a server 32 that stores various processing data including the measurement results, and the like. The display unit 31 may be configured integrally with the processing device 20. The processing device 20 generates image information for displaying on the display unit 31 (screen) at least one of the vertical load, center of gravity position, and inclination component force of the user's foot, or changes over time of these.

[0038] The processing device 20 measures the following, for example, and these will be described in detail later: (1) Center of gravity and trajectory of the forefoot, rearfoot, left and right, or overall, (2) Amount of movement due to change in center of gravity from when the sole of the foot touches the ground, (3) Applied load (body weight), (4) Change in tilt over time based on change in sole shape over time, KAM (determination of knee OA / knock-knee / bow-knee, sum of knee impulses, calculation of torsion from front and rear vectors, measurement of supination angle / pronation angle), (5) Presence or absence of toe contact / applied load, (6) Gait cycle, and (7) Walking condition (determination of normal gait (determination of rehabilitation progress), determination of normality of rocker function).

[0039] The bioinformation measurement system 100 may further include various auxiliary sensors 33 separate from the pressure detection device 10. Examples of the sensors 33 include inertial sensors (IMUs) such as acceleration sensors and angular velocity sensors that detect the movement of the user's feet, as well as vibration sensors that detect vibrations and cameras that photograph the user's feet. The output of the sensors 33 may be transmitted to the control unit 12 of the pressure detection device 10 or directly to the processing device 20. The bioinformation measurement system 100 may also include a tactile sensation providing device that provides tactile sensations to the foot F based on control commands transmitted from the control unit 12 or the processing device 20. Furthermore, the bioinformation measurement system 100 may be integrated with a motion capture device equipped with IMUs on the user's entire body.

[0040] [Pressure Detection Device] Next, the pressure detection device 10 will be described in detail.

[0041] (Sensor Sheet) In this embodiment, the sensor sheet 11 is configured as an insole 41 of the shoe 4 or as a part thereof, as shown in Fig. 2. Fig. 3 is a schematic side cross-sectional view of the sensor sheet 11.

[0042] The insole 41 serves as the inner sole of the shoe 4 and is disposed, for example, on the upper surface of the midsole 40. The insole 41 is a deformable sheet formed to a size that contacts the entire sole of the foot. As shown in FIG. 3 , the sensor sheet 11 serving as the insole 41 has a sensor layer 42 and an intermediate layer 43 disposed on the surface of the sensor layer 42.

[0043] The sensor layer 42 is disposed on the upper surface of the midsole 40. The sensor layer 42 is a capacitance-type piezoelectric distribution sensor as described below, but is not limited to this as long as it has multiple nodes, and any sensor sheet with a different detection principle, such as an optical type, a resistive type, or a piezoelectric type, can be applied.

[0044] The intermediate layer 43 is typically formed of a material that is more flexible than the midsole 40. Any material that is generally used as an insole material can be applied to the intermediate layer 43, and typically, the intermediate layer 43 is formed of an elastically deformable material having cushioning properties, such as rubber, gel, or foam material.

[0045] The midsole 40 is formed of a material that is sufficiently harder than the sensor layer 42 and has appropriate flexibility to follow the deformation of the outsole 4 A. Typical examples of this type of material include molded bodies of resin materials such as EVA (ethylene-vinyl acetate copolymer) and PU (polyurethane), as well as metal materials.

[0046] The sensor sheet 11 detects a pressure distribution waveform including a gradient component of the user's foot pressure input to the sensor layer 42 via the intermediate layer 43. If necessary, an outermost layer 44 made of a material harder than the intermediate layer 43 may be provided on the surface of the intermediate layer 43. This allows the gradient component to be detected more accurately.

[0047] Fig. 4 is a schematic side cross-sectional view showing the cross-sectional structure of the sensor layer 42. Fig. 5 is a schematic plan view showing the sensor electrode layer 122 in the sensor layer 42.

[0048] 4 and 5, the X-axis direction and the Y-axis direction are directions parallel to the pressure detection surface S of the sensor sheet 11 (insole 41) (hereinafter also referred to as in-plane directions), and in this embodiment, are directions parallel or approximately parallel to the ground. The Z-axis direction is a direction perpendicular to the pressure detection surface S (hereinafter also referred to as the vertical direction). The pressure detection surface S corresponds to the surface of the sensor sheet 11 (insole 41) to which foot pressure is applied.

[0049] 4, the sensor layer 42 is a capacitive pressure sensor 121 having a plurality of capacitance elements. The pressure sensor 121 has a sensor electrode layer 122, a reference electrode layer 125, and a deformation layer 127 disposed between the sensor electrode layer 122 and the reference electrode layer 125. The pressure sensor 121 is integrated with the back surface of the mid layer 43 via an adhesive layer. The pressure sensor 121 may also be integrated with the surface of the midsole 40 via an adhesive layer.

[0050] The sensor electrode layer 122 is configured by a flexible printed circuit board or the like. As shown in Fig. 5, the sensor electrode layer 122 has a main body portion 122a that is rectangular in plan view and an extension portion 122b that extends outward from the main body portion 122a. The main body portion 122a is provided with a sensing portion 128 (described later), and the control unit 12 (or a connector part 70 connected to the control unit 12) is mounted on the tip of the extension portion 122b.

[0051] The sensor electrode layer 122 has a flexible substrate 129 and a plurality of sensing units 128 provided on the surface of the substrate 129 or inside the substrate 129. Examples of materials that can be used for the substrate 129 include polymer resins such as polyethylene terephthalate, polyimide, polycarbonate, and acrylic resin. The sensing units 128 are regularly arranged in a matrix at predetermined intervals in both the vertical and horizontal directions (vertical: y-axis direction, horizontal: x-axis direction). The thickness of the sensor electrode layer 122 is, for example, 50 μm to 300 μm, and is 125 μm in this embodiment.

[0052] The sensing unit 128 is composed of a plurality of capacitive elements (detection elements) that can detect a change in distance from the reference electrode layer 125 as a change in capacitance. As shown in Fig. 6 , the sensing unit 128 includes a comb-shaped pulse electrode 281 and a comb-shaped sense electrode 282. The comb-shaped pulse electrode 281 and the comb-shaped sense electrode 282 are arranged so that their teeth face each other, and each sensing unit 128 is composed of an area (node ​​area) where one comb tooth is positioned between the other comb tooth.

[0053] Each pulse electrode 281 is connected to a wiring portion 281a extending in the Y-axis direction, and each sense electrode 281 is connected to a wiring portion 282a extending in the X-axis direction. The wiring portions 281a are arranged in the X-axis direction on the front surface of the substrate 129, and the wiring portions 282a are arranged in the Y-axis direction on the back surface of the substrate 129. Each sense electrode 282 is electrically connected to the wiring portion 282a via a through-hole 283 provided in the substrate 29. The sensor electrode layer 122 may have a ground line. The ground line is provided, for example, on the outer periphery of the sensor electrode layer 122 or in a portion where the wiring portions 281a, 282a run parallel to each other.

[0054] The structure of the sensing unit 128 is not limited to the above example, and any structure may be used. For example, the sensor electrode layer 122 may be formed of a laminate of a first electrode sheet having a lattice-shaped first electrode pattern extending in the X-axis direction and a second electrode sheet having a lattice-shaped second electrode pattern extending in the Y-axis direction. In this case, the sensing unit 128 is formed at the intersection of the first electrode pattern and the second electrode pattern.

[0055] The reference electrode layer 125 is connected to a reference potential. In this embodiment, the reference electrode layer 125 is a so-called ground electrode and is connected to the ground potential. The reference electrode layer 125 is flexible and has a thickness of, for example, about 0.03 mm to 0.5 mm, and in this embodiment, it is 0.1 mm (100 μm). Examples of materials that can be used for the reference electrode layer 125 include inorganic conductive materials, organic conductive materials, and conductive materials containing both inorganic and organic conductive materials.

[0056] Examples of inorganic conductive materials include metals such as aluminum, copper, and silver, alloys such as stainless steel, and metal oxides such as zinc oxide and indium oxide. Examples of organic conductive materials include carbon materials such as carbon black and carbon fiber, and conductive polymers such as substituted or unsubstituted polyaniline and polypyrrole. The reference electrode layer 125 may be composed of a thin metal plate such as stainless steel or aluminum, conductive fiber, or conductive nonwoven fabric. The reference electrode layer 125 may be formed on a plastic film by a method such as vapor deposition, sputtering, adhesion, or coating.

[0057] The deformation layer 127 is disposed between the sensor electrode layer 122 and the reference electrode layer 125. The deformation layer 127 is configured to be elastically deformable in response to an external force. When an external force is applied perpendicularly to the sensor sheet 120, the deformation layer 127 elastically deforms in response to the external force, and the reference electrode layer 125 approaches the sensor electrode layer 122. At this time, the capacitance between the pulse electrode 281 and the sense electrode 282 in the sensing unit 128 changes, and the sensing unit 128 can detect this change in capacitance as a pressure value.

[0058] The thickness of the deformation layer 127 is, for example, 100 μm or more and 1000 μm or less, and the weight per unit area of ​​the deformation layer 127 is, for example, 50 mg / cm ２ By setting the thickness and basis weight of the deformation layer 27 within this range, the detection sensitivity of the pressure sensor 121 in the vertical direction can be improved.

[0059] The lower limit of the thickness of the deformation layer 127 may be, for example, 150 μm or more, 200 μm or more, 250 μm or more, 300 μm or more, etc. The upper limit of the thickness of the deformation layer 27 may be, for example, 800 μm or less, 600 μm or less, 500 μm or less, 400 μm or less, etc. In this embodiment, the thickness of the deformation layer 127 is set to 300 μm or more and 400 μm or less (e.g., 355 μm).

[0060] To facilitate deformation in the z-axis direction, the deformation layer 127 may be configured with a patterning structure including, for example, a columnar structure. This patterning structure can be a matrix, stripe, mesh, radial, geometric pattern, spiral, or other structure.

[0061] (Layout of Sensor Layer) The sensor layer 42 may be configured to cover the entire surface of the insole 41 with a single sheet member, but in this embodiment, the insole 41 is divided into three regions, and a sensor layer is disposed in each of the divided regions.

[0062] 7 is a schematic plan view showing an example of the arrangement of the sensor layer 42 within the plane of the insole 41. The insole 41 of this embodiment has a first sensor layer 42F arranged in the forefoot portion, which is the region on the toe side, a second sensor layer 42B arranged in the rearfoot portion, which is the region on the heel side, and a third sensor layer 42M arranged in the midfoot portion, which is the region between the forefoot and rearfoot portions.

[0063] As shown in the figure, the forefoot refers to the region of the foot F (see FIG. 2) from the metatarsophalangeal joint (MP joint) toward the toes. Because the forefoot includes the behavior of the toes, the first sensor layer 42F is subjected to a pressure distribution different from that of the second and third sensor layers 42B, 42M disposed in the rearfoot and midfoot. By disposing different sensor layers 42 in the forefoot, rearfoot, and midfoot, it is possible to more accurately detect the pressure acting on the sole, particularly the gradient component.

[0064] Here, in order to detect the movement of the toes in the forefoot with higher accuracy, the number of nodes (the number of sensing units 128) in the first sensor layer 42F may be greater than the number of nodes in the second sensor layer 42B and the third sensor layer 42M. Alternatively, the node pitch (or the arrangement interval of the sensing units 128) in the first sensor layer 42F may be narrower than the node pitch in the second sensor layer 42B and the third sensor layer 42M.

[0065] Furthermore, because the midfoot region has little effect on the movement of the center of gravity of the entire sole, the area of ​​the third sensor layer 42M disposed in the midfoot region may be smaller than the other sensor layers 42F, 42B, or the third sensor layer 42M may be omitted as shown in Fig. 8. Alternatively, the third sensor layer 42M may be configured as a common sensor layer with the second sensor layer 42B. Furthermore, as shown in Fig. 9, the second sensor layer 42B may not be a pressure distribution sensor, but may instead have multiple pressure sensors scattered at multiple locations in the rearfoot region.

[0066] Furthermore, the node arrangement of the first sensor layer 42F arranged in the forefoot, for example, is not limited to a matrix (lattice) arrangement and may be arbitrarily changed depending on the shape and size of the forefoot region. For example, any node may be partially missing as shown in Fig. 10(A), there may be regions with irregular arrangement pitch or number as shown in Fig. 10(B), the nodes may be arranged diagonally rather than orthogonally as shown in Fig. 10(C), the node shape may be circular or elliptical rather than rectangular as shown in Fig. 10(D), or the number of nodes in the row or column direction may be different as shown in Fig. 10(E).

[0067] (Concept of Processing Algorithm of Control Unit) Next, the concept of the processing algorithm of the control unit 12 will be described. Figures 11 to 13 are diagrams for explaining the concept of the processing algorithm of the control unit 12. Note that in Figures 11 to 13, the sensor sheet 11 will be described using an example of the laminated structure of the sensor layer 42 and intermediate layer 43 shown in Figure 3.

[0068] The upper left of Fig. 11 shows what happens when the tapping element 5 applies a downward force to the intermediate layer 43, causing the intermediate layer 43 to be pressed, and the dashed line in the center of Fig. 11 indicates the pressure distribution waveform W detected by the sensor layer 42 at this time. The lower left of Fig. 11 also shows what happens when the tapping element 5 tilts after the intermediate layer 43 is pressed, causing the intermediate layer 43 to deform accordingly, and the solid line in the center of Fig. 11 indicates the pressure distribution waveform W detected by the sensor layer 42 at this time.

[0069] From FIG. 11, it can be seen that when the tapping element 5 is tilted, the shape of the upper region (first region R) of the mountain-shaped pressure distribution waveform W changes significantly, while the shape of the lower region (second region R') of the pressure distribution waveform W does not change much.

[0070] The upper left of Fig. 12 shows what happens when the tapping element 5 applies a downward force to the intermediate layer 43, causing the intermediate layer 43 to be pressed, and the dashed line in the center of Fig. 12 indicates the pressure distribution waveform W detected by the sensor layer 42 at this time. The lower left of Fig. 12 also shows what happens when the tapping element 5 moves in a planar direction (XY plane) after the intermediate layer 43 is pressed, causing the intermediate layer 43 to undergo shear deformation, and the solid line in the center of Fig. 12 indicates the pressure distribution waveform W detected by the sensor layer 42 at this time.

[0071] 12, it can be seen that when the tapping element 5 moves (shears) in a planar direction, the shape of the upper region of the mountain-shaped pressure distribution waveform W remains unchanged (moves in a planar direction), while the lower region of the pressure distribution waveform W moves in a planar direction (XY plane) (without changing shape). Here, there are cases where the tapping element 5 moves in a planar direction (XY plane) while changing its inclination. This state is shown in FIG. 5.

[0072] The upper left of Fig. 13 shows a state in which a downward force is applied to the tapping element 5 while it is tilted counterclockwise, thereby pressing the intermediate layer 43, and the dashed line in the center of Fig. 13 indicates the pressure distribution waveform W detected by the sensor layer 42 at this time. The lower left of Fig. 13 also shows a state in which the tapping element 5 subsequently tilts clockwise while simultaneously moving in a planar direction (XY plane), and the solid line in the center of Fig. 13 indicates the pressure distribution waveform W detected by the sensor layer 42 at this time.

[0073] 13, it can be seen that when the tapping element 5 is tilted, the shape of the upper region (first region R) of the mountain-shaped pressure distribution waveform W changes significantly, while the shape of the lower region (second region R') of the pressure distribution waveform W does not change much. Also, it can be seen from Fig. 13 that when the tapping element 5 moves (shears) in a planar direction, the lower region of the mountain-shaped pressure distribution waveform W moves in the planar direction (XY plane) (without changing its shape much).

[0074] As is clear from the explanations of Figures 11 to 13, it can be seen that the upper region (first region R) of the mountain-shaped pressure distribution waveform W is the region that is dominant for the gradient component of the force applied by the tapping element 5, and the lower region (second region R') is the region that is dominant for the shear component of the force applied by the tapping element 5.

[0075] Therefore, in this embodiment, the control unit 12 executes the following process. First, the control unit 12 separates the mountain-shaped pressure distribution waveform W into a first region R where the pressure value is equal to or greater than the separation threshold, and a second region R' where the pressure value is less than the separation threshold. Next, the control unit 12 calculates the gradient component of the force based on the first region R, and calculates the shear component of the force based on the second region R'. This makes it possible to calculate both the gradient component and the shear component of the force from a single pressure distribution waveform W.

[0076] In this way, if the gradient and shear components of the force can be determined from a single pressure distribution waveform W, there is no need to complicate the structure of the entire sensor unit 12 in order to determine the gradient and shear components, and it also becomes easier to miniaturize the structure of the entire sensor unit 12.

[0077] (Processing Procedure in Control Unit) Next, a processing procedure in the control unit 12 will be described. Figures 14 and 15 are flowcharts showing the processing of the control unit 12. Figure 16 is a diagram showing sensor data including a mountain-shaped pressure distribution waveform W.

[0078] First, the control unit 12 acquires sensor data (data having pixels of WxH pixels) including a pressure distribution waveform W from the sensor layer 42 (ST101) (see FIG. 16 ). If there are multiple sensor layers 42, the control unit 12 acquires sensor data including a pressure distribution waveform W individually from each sensor layer (first sensor layer 42F, second sensor layer 42B, third sensor layer 42M).

[0079] Next, the control unit 12 determines whether the sensor layer 42 has been pressed (ST102) based on the pressure distribution waveform W. Whether the sensor layer 42 has been pressed is determined based on, for example, whether the maximum pressure value among the pressure values ​​indicated by the pressure distribution waveform W is equal to or greater than a predetermined input determination threshold value.

[0080] In this case, when the maximum pressure value is equal to or greater than the input determination threshold, it is determined that the sensor layer 42 has been pressed, whereas when the maximum pressure value is less than the input determination threshold, it is determined that the sensor layer 42 has not been pressed. The input determination threshold is a value that serves as a criterion for determining input to the sensor layer 42, and is set to an appropriate value so that intended inputs can be appropriately determined and unintended inputs can be appropriately rejected. When there are multiple sensor layers 42, the input determination thresholds for the respective sensor layers (the first sensor layer 42F, the second sensor layer 42B, and the third sensor layer 42M) may be the same or may be set to different values ​​depending on the individual sensor layers.

[0081] If the sensor layer 42 is not pressed (NO in ST102), the control unit 12 determines whether or not the sensor layer 42 was determined to be pressed in the previous determination in ST102 (ST103).

[0082] If it was determined in the previous determination that the sensor layer 42 was pressed (YES in ST103), the control unit 12 determines that the input to the sensor layer 42 has been released (ST104) and returns to ST101. On the other hand, if it was determined in the previous determination that the sensor layer 42 was not pressed (NO in ST103), the control unit 12 returns to ST101 without going through ST104.

[0083] If it is determined in ST102 that the sensor layer 42 has been pressed (YES in ST102), the control unit 12 determines whether the sensor data has a multi-peak distribution including multiple mountain-shaped pressure distribution waveforms W (ST105).

[0084] If the sensor data has a multi-modal distribution (YES in ST105), the control unit 12 selects one pressure distribution waveform W from the multiple pressure distribution waveforms W (ST106). In this case, the control unit 12 typically preferentially selects the waveform showing the highest maximum pressure value or the waveform with the largest size from the multiple pressure distribution waveforms W. It is also possible to perform subsequent calculations for each of the multiple distribution waveforms that appear.

[0085] In the determination of ST106, for example, if the number of pixels in the sensor data is large, object detection processing such as SSD (Single Shot Multi-box Detector) or YOLO (You Only Look Once) is performed. On the other hand, if the number of pixels in the sensor data is small, a search for multiple local maxima is performed. After one pressure distribution waveform W is determined, the control unit 12 performs noise removal processing using a method such as a Gaussian filter, a bilateral filter, or a constant threshold (ST107).

[0086] Next, the control unit 12 separates the pressure distribution waveform W into a first region R where the pressure value is equal to or greater than the separation threshold, and a second region R' where the pressure value is less than the separation threshold (ST108). Typically, the first region R is a region on the upper side of the mountain-shaped pressure distribution waveform W that appropriately includes a portion where the mountain shape is broken and deformed, and the second region R' is a region on the lower side of the pressure distribution waveform W that excludes the deformed upper region (first region R).

[0087] As a method for setting a separation threshold for separating the first region R and the second region R', the following four methods 1. to 4. can be given, for example.

[0088] 1. Constant: A certain pressure value is preset as a constant, and this value is used as the separation threshold. 2. Ratio: For example, a pressure value that is a certain ratio (e.g., 50%) of the maximum pressure of the pressure distribution waveform W is used as the separation threshold (i.e., variable). 3. Otsu's binarization method: Image processing using Otsu's binarization method is performed on image data including the pressure distribution waveform W, and the separation threshold is determined (i.e., variable). 4. Edge extraction processing: Edge extraction processing (image processing) using, for example, a Laplacian filter (second-order differential) is performed on image data including the pressure distribution waveform W, and the separation threshold is determined based on the extraction results (i.e., variable). The separation threshold may be determined by combining two or more of the methods 1 to 4 above. The separation threshold may also be determined by machine learning.

[0089] After separating the pressure distribution waveform W into the first region R and the second region R' using the separation threshold, the control unit 12 then calculates the current tilt angle based on the first region R (ST109). When calculating the tilt angle, for example, the control unit 12 calculates an approximate plane P for the first region R and calculates the angle at which this approximate plane P is tilted with respect to the planar direction (XY plane), thereby calculating the tilt angle. In this embodiment, the approximate plane P for the first region R is calculated by sequentially performing a process of extracting edge information from the pressure distribution waveform W using a Laplacian filter or the like and a process of determining contact portions using a method such as labeling.

[0090] Fig. 17 is a diagram showing a state in which the approximate plane P of the first region R gradually tilts from a state in which it is nearly parallel to the horizontal plane. Fig. 18 is a schematic diagram showing a state in which the approximate plane P of the first region R tilts.

[0091] After calculating the current tilt angle, control unit 12 next determines whether this is the first time in the press determination in ST102 (ST110). If this is the first time (YES in ST110), control unit 12 stores the current tilt angle as the first tilt angle in storage unit 13 (ST111), skips ST112 and ST113, and proceeds to ST114. If this is not the first time but the second or subsequent time (NO in ST110), control unit 12 calculates the difference between the current tilt angle and the first tilt angle (current tilt angle - first tilt angle) (ST112).

[0092] Next, the control unit 12 converts the difference amount into a force gradient component, for example, by affine transformation (ST113). Note that although the method for determining the gradient angle from a change in the approximate plane P of the first region R has been described here, the gradient angle may also be determined from a change in the center of gravity position of the first region R.

[0093] Referring to FIG. 15, next, control unit 12 calculates the current center of gravity position of second region R' (ST114).

[0094] FIG. 19 is a schematic diagram showing a state when the center of gravity position of the second region R′ moves in a planar direction (XY plane).

[0095] After calculating the current center of gravity position, the control unit 12 next determines whether this is the first time in the press determination in ST102 (ST115). If this is the first time (YES in ST115), the control unit 12 stores the current center of gravity position as the first center of gravity position in the storage unit 13 (ST116), skips ST117 and ST118, and returns to ST101. If this is not the first time but the second or later time (NO in ST115), the control unit 12 calculates the difference between the current center of gravity position and the first center of gravity position (current center of gravity position - first center of gravity position: movement distance) (ST117).

[0096] Next, the control unit 12 converts the difference amount into a shear component of the force, for example, by affine transformation (ST118), and returns to ST101. Thereafter, the processes from ST101 onwards are repeatedly executed at a predetermined cycle (for example, on the order of tens to hundreds of ms).

[0097] Here, the control unit 12 determines that a tilt operation has been input when the pressure component of the force is equal to or greater than the input determination threshold (see ST102) and the tilt angle (θ) of the tilt component of the force is equal to or greater than a predetermined angle. Also, the control unit 12 determines that a shear operation has been input when the pressure component of the force is equal to or greater than the input determination threshold (see ST102) and the shear component of the force is equal to or greater than a predetermined value.

[0098] In addition, the control unit 12 determines that a pressing operation has been input when the tilt component is less than a predetermined angle and the shear component is less than a predetermined value, and the pressing component of the force is greater than or equal to a predetermined threshold (a threshold set to a value higher than the input determination threshold).

[0099] In this embodiment, the control unit 12 calculates the gradient component of the pressure acting on the forefoot and its time change, and the gradient component of the pressure acting on the rearfoot and its time change, separately, based on the output of the first sensor layer 42F that detects the pressure distribution in the forefoot and the output of the second sensor layer 42B that detects the pressure distribution in the rearfoot, thereby contributing to quantitative evaluation of the position of the user's knee and the gradient of the foot during walking.

[0100] The control unit 12 is further configured to calculate at least one of the vertical load and the center of gravity position in the forefoot and rearfoot based on the pressure distribution waveforms detected by the first and second sensor layers 42F, 42B. For example, the user's weight can be measured by combining the vertical loads acquired from these sensor layers 42F, 42B. Note that the user's weight can be measured with even greater accuracy by adding the vertical load detected by the third sensor layer 42M located in the midfoot to the evaluation target.

[0101] Furthermore, since the forefoot can also detect the behavior of the toes, for example, based on the pressure detection data of the first sensor layer 42F, the forefoot may be divided into the right and left sides, and the pressure distribution and its change over time may be detected separately.

[0102] FIG. 20 shows experimental results illustrating an example of the change over time in the tilt component of the sole load acting on the sensor sheet 11 (insole 41) while the user is walking. The graph shows the change over time in the angle of the X- and Y-direction tilt components detected by the first sensor layer 42F located in the forefoot, and the change over time in the angle of the X- and Y-direction tilt components detected by the second sensor layer 42B located in the rearfoot. Note that the figure shows instantaneous images at a given time, representing the pressure distribution waveform and its in-plane pressure distribution. In the figure, X indicates the coordinate position in the length direction of the sole, and Y indicates the coordinate position in the width direction (left-right direction) of the sole.

[0103] As shown in Figure 20, the gradient component of the pressure acting on the sensor sheet 11 (insole 41) behaves differently in the forefoot and rearfoot. Therefore, it is expected that separating and extracting the gradient components of the pressure in the forefoot and rearfoot will greatly contribute to more accurate measurement of the gradient or posture of the user's foot F relative to the ground.

[0104] [Processing Device] Next, the processing device 20 will be described in detail.

[0105] The processing device 20 measures the inclination or posture of the user's foot F based on the output of the pressure detection device 10 (controller 12) as described above. The processing device 20 may execute the calculation process of the pressure gradient component executed by the control unit 12 described above in place of the control unit 12, or the control unit 12 may be configured as part of the processing device 20. The processing device 20 executes, for example, a calculation process (hereinafter also referred to as process A) of a quantitative index for evaluating the inclination or posture of the foot F based on the pressure gradient component detected by the sensor layer 42, and an output process (hereinafter also referred to as process B) of a target evaluation object based on the calculated quantitative index.

[0106] FIG. 21 is a flowchart showing part of the processing procedure in the biological information detection system 100 of this embodiment.

[0107] When the process of acquiring sole load data (sensor data) acting on the sensor sheet 11 (insole 41) in the pressure detection device 10 starts (ST201), calculation of inclination components, etc. is performed from the sole load data until the process is completed (No in ST202, ST203, 204).

[0108] If the calculation of the tilt component is performed by the control unit 12, the output result by the control unit 12 is sent to the processing device 20 and processing A is executed (Yes in ST203, ST205). On the other hand, if the calculation of the tilt component is performed by the processing device 20, the sensor data is sent from the control unit 12 to the processing device 20, and then processing A is executed (No in ST203, ST205).

[0109] After executing process A, processing device 20 executes process B (ST206). Processing device 20 displays the calculated values ​​in processes A and B on display unit 31 and stores the calculated values ​​in server 32 (ST207, 208). When processing device 20 subsequently executes process B, it reads out the calculated values ​​necessary for the process from server 32. This makes it possible to execute process B even after acquiring sensor data.

[0110] FIG. 22 is a flowchart illustrating the procedure of process A executed in the processing device 20.

[0111] The processing device 20 first divides the user's left and right sole load data into four data groups: detection data for the forefoot (first sensor layer 42F) and the rear and midfoot (second sensor layer 42B and third sensor layer 42M) of the left foot; and detection data for the forefoot (first sensor layer 42F) and the rear and midfoot (second sensor layer 42B and third sensor layer 42M) of the right foot (ST301).

[0112] Next, the processing device 20 performs a process of calculating the gradient component of the pressure on the sensor sheet for each of the four data groups (ST302), and then performs a process of converting the calculated gradient component into the actual angle of the leg from a reference plane such as the ground (ST303).

[0113] The tilt component may be calculated by using the method of calculating the tilt angle of the approximate plane P as described above, or may be calculated based on the amount of movement of the center of gravity position of the first region R in the pressure distribution waveform W (see FIG. 13 ). On the other hand, the actual leg angle may be calculated (ST303) using, for example, polynomial approximation or a machine learning device. Note that if the tilt component is calculated in the control unit 12, the process in the processing device 20 (ST302) can be omitted.

[0114] For each of the data groups for the four regions, the processing device 20 executes a process of calculating the center of gravity position of each region (ST304) and a process of calculating the total weight for each region (ST305). The process of calculating the center of gravity position and the total weight for each region is performed in parallel with the process of calculating the gradient component for each region (ST302, ST303), but this is not limitative, and each process may be performed in a predetermined order.

[0115] The various calculated values ​​(tilt angle, center of gravity position, total load) and their time series data calculated in this process A are stored in a predetermined database of the server 32 (see tilt angle history database 51, center of gravity position history database 52, and load history database 53 in Figure 23).

[0116] FIG. 23 is a block diagram illustrating the process B executed in the processing device 20. As shown in FIG.

[0117] The processing device 20 has a calculation unit 21 that performs gait cycle calculation, gait mode determination, KAM calculation, rocker function status (soundness evaluation), gait disturbance determination, etc. based on various calculated values ​​(tilt angle, center of gravity position, total load) calculated by executing process A. The calculation unit 21 performs various target calculations or determinations using techniques such as polynomial approximation and machine learning based on the various calculated values.

[0118] For example, the walking cycle and walking mode are calculated or determined based on the center of gravity and trajectory of the forefoot, rearfoot, left and right or overall, the amount of movement due to change in the center of gravity from the time the sole of the foot touches the ground, and the change in load on the left and right over time.

[0119] Figure 24 shows an example of a heat map output of pressure distribution. In the figure, (A) is the raw output of sensor data, and (B) is an image segmented using image processing. By using labeling to determine contact points, polynomial approximation, and machine learning techniques, the state of each part during walking is evaluated from the segmented image. For example, the ratio of load on the little finger and thumb can be used to determine whether the walking mode is correct.

[0120] Knee Adduction Moment (KAM) refers to the external knee joint adduction (inversion) moment during walking, and is used as a substitute measure of the contact force on the inside of the knee joint to predict the progression of knee OA (osteoarthritis). In addition, evaluating KAM makes it possible to determine whether a person is bow-legged or bow-legged, calculate the sum of knee impulses, calculate torsion from the anterior-posterior vector, and measure the supination angle / pronation angle.

[0121] As shown in Figure 25, KAM is calculated from the product of the floor reaction force Fz and the distance L from the center of the knee joint to the ground (sole of the foot). The floor reaction force Fz is obtained from the vertical load (total load on the sensor layer) applied to the sensor sheet 11. Since the length L of the knee is known, if the inclination angle of the foot relative to the ground (angle θ from the z-axis direction, angle φ from the x-axis direction) is known, KAM during walking can be calculated from the following equation (1), and the total KAM applied during a series of walking movements can be calculated from the following equation (2). KAM = L x Fz sin θ (1) ΣKAM = L x Σ|Fz sin θ| (2)

[0122] As shown in Figure 26, the rocker function includes a heel rocker (Figure 26(A)) with the heel as the center of rotation, an ankle rocker (Figure 26(B)) with the ankle joint as the center of rotation, and a forefoot rocker (Figure 26(C)) with the MTP joint as the center of rotation. The rocker function is evaluated when determining the soundness of walking and the progress of rehabilitation. Furthermore, the presence or absence of gait disturbance can be determined from the trajectory of the center of gravity.

[0123] (Example of operation of the bioinformation measurement system) The bioinformation measurement system 100 is operated or operates, for example, in the following procedure: 1. Put on shoes with insoles 41. 2. Start the app on the user's mobile phone or PC and start recording sensor data. 3. Display walking status and cycle in real time and make announcements by voice or on screen. 4. Stop recording sensor data when walking ends and close the app. 5. Save the recorded information on the server 32. 6. Provide feedback on the overall (average) walking behavior to the user's mobile phone or PC. 7. Provide feedback on difference information from past history to the user as well.

[0124] 27 is a diagram showing the centers of gravity P1 to P5 of each region in the heat map of sensor data at any time. Here, P1 represents the center of gravity of the left forefoot LF, P2 the center of gravity of the left rearfoot LB, P3 the center of gravity of the right forefoot RF, P4 the center of gravity of the right rearfoot RB, and P5 the center of gravity of both feet.

[0125] Figure 28 shows the changes over time in the position and tilt angle of each of the centers of gravity P1 to P5 shown in Figure 27, where (A) shows the position in the x direction, (B) shows the position in the y direction, (C) shows the angle in the roll direction (around the y axis), (D) shows the angle in the pitch direction (around the x axis), and (E) shows the magnitude of the vertical load.

[0126] According to this embodiment, the center of gravity position, tilt component, and magnitude of vertical load of each region during walking can be acquired individually and in real time, thereby enabling accurate quantitative evaluation of foot tilt and other aspects of the walking state.

[0127] [Others] Existing insoles incorporating pressure sensors can only obtain limited information, such as load and sole center of gravity. To obtain important information, such as foot and body movement, it is necessary to use large-scale devices such as treadmills or other sensors, such as IMUs and cameras. On the other hand, existing insoles incorporating pressure sensors have a limited number of nodes capable of acquiring pressure, and the pitch between sensors is large, so only simple algorithms can be implemented. Furthermore, multi-node insole sensors often have complex sensor arrangements to cover the entire sole of the foot, making information and calculation processing difficult. In contrast, this embodiment uses sensors with a narrow-pitch, matrix-shaped pressure distribution, facilitating image processing and vector processing. This makes it possible to calculate the inclination of the foot during walking, making it possible to estimate the foot's condition, vector, and walking state during walking using only the insole.

[0128] In response to the problem that quantitative evaluation of walking status cannot be achieved using only an insole with a pressure sensor, this embodiment uses an algorithm that can estimate the contact direction vector from pressure distribution gradient information, making it possible to provide foot tilt information in addition to existing pressure and center of gravity information. This embodiment makes it possible to provide quantitative walking status indicators for walking, running, and sports, contributing to efficient training. Furthermore, by combining it with a trial entertainment version, user movement information can be obtained more accurately than with a camera, improving the value experience for multiple people.

[0129] Furthermore, according to this embodiment, it is possible to detect the force distribution using an insole with a pressure sensor, and to calculate the inclination of the foot during walking from the force distribution. In particular, it is possible to calculate KAM using a simple formula from the inclination of the leg, the load on the foot, and the known foot length, without using any other sensors. Furthermore, it is possible to determine whether the walking is correct, and to correct the walking to an appropriate level by quantitatively intervening using an angle correction actuator.

[0130] Furthermore, in this embodiment, an approximate plane or approximate cone is created from the heat map output of the sole, and by observing the inclination of this plane, the degree to which the foot is inclined when it lands and when it leaves the ground is calculated. In this case, by separating the output of the toes using edge detection, it is possible to calculate the inclination of the ball of the foot (forefoot), which is the main contact point when walking. It is possible to estimate the proportion of the toes used when walking from the ratio of the load on the separated big toe and other toes to the load during walking. This value also makes it possible to evaluate whether the walking is being performed correctly.

[0131] Furthermore, it will be possible to quantitatively calculate knee load using only the sole sensor, which until now could only be calculated using indicators other than actual values ​​such as load and center of gravity. Intervention can improve knee osteoarthritis. Because it can calculate how correctly a person is walking, it will be possible to provide insoles that can obtain useful data for the health status of healthy people and the training of athletes, as well as for patients with knee symptoms. Daily use will enable the accumulation of data such as weight and amount of exercise, which can be used to collect big data for predicting other diseases.

[0132] By collecting IMU sensor data, it is possible to obtain robust output to the knee. By resetting the IMU when walking to prevent the accumulation of integration errors and by matching the foot trajectory with the insole tilt, it is possible to create an insole system with fewer false detections.

[0133] [Modification] In the above embodiment, the load on the sole of the foot is detected by the sensor sheet 11 (insole 41). In addition, the load on the instep or side of the foot may also be detected using a similar sensor sheet.

[0134] The insole 41 may be integral with footwear such as shoes, may replace the insole of an existing shoe, or may be placed on top of the insole of an existing shoe. There are no particular limitations on the type of footwear, and the insole 41 can be applied to sandals, clogs, boots, etc.

[0135] Furthermore, the sensor sheet 11 is not limited to being formed as an insole, but may be a sheet member of any shape laid on the walking surface of the floor, in which case the inclination of the foot when walking can be measured even when the user has taken off their shoes.

[0136] The present technology can also be configured as follows. (1) A bioinformation detection device including: a sensor sheet having a sensor layer capable of detecting a pressure distribution; and an elastically deformable intermediate layer disposed on the surface of the sensor layer, the sensor sheet detecting a pressure distribution waveform including a gradient component of a user's foot pressure input to the sensor layer via the intermediate layer; and a control unit calculating the gradient component based on the pressure distribution waveform. (2) The bioinformation detection device described in (1) above, wherein the control unit separately calculates a gradient component in a forefoot region that is a region on the toe side and a gradient component in a rearfoot region that is a region on the heel side based on the pressure distribution waveform. (3) The bioinformation detection device described in (2) above, wherein the control unit further calculates at least one of a vertical load and a center of gravity position of the forefoot and the rearfoot based on the pressure distribution waveform. (4) The biological information detection device according to (3) above, wherein the control unit further calculates a vertical load in a midfoot region, which is a region between the forefoot and the rearfoot, based on the pressure distribution waveform. (5) The biological information detection device according to any one of (2) to (4) above, wherein the sensor layer is an electrostatic sensor having a plurality of capacitive elements. (6) The biological information detection device according to (5) above, wherein the arrangement interval of the plurality of capacitive elements in the forefoot region is narrower than the arrangement interval of the plurality of capacitive elements in the rearfoot region. (7) The biological information detection device according to (5) or (6) above, wherein the number of the plurality of capacitive elements in the forefoot region is greater than the number of the plurality of capacitive elements in the rearfoot region. (8) A bioinformation detection device according to any one of (5) to (7) above, wherein the sensor layer has a sensor electrode layer in which the plurality of capacitance elements are arranged in a matrix, a reference electrode layer connected to a reference potential, and a deformation layer disposed between the sensor electrode layer and the reference electrode layer.(9) The biological information detection device according to any one of (1) to (8), wherein the control unit separates the pressure distribution waveform into a first region where the slope component is relatively dominant and a second region where the shear component is relatively dominant, and calculates the slope component based on the first region. (10) The biological information detection device according to (9), wherein the control unit sets, in the pressure distribution waveform, a region where the pressure value is equal to or greater than a predetermined threshold as a first region, and a region where the pressure value is less than the predetermined threshold as a second region. (11) The biological information detection device according to (10), wherein the control unit acquires image data including the pressure distribution waveform and performs image processing on the image data to set the predetermined threshold. (12) The biological information detection device according to (10), wherein the control unit calculates a slope angle of the first region with respect to a direction parallel to the sensor sheet, and calculates the slope component based on the slope angle. (13) A bioinformation measurement system comprising: a sensor sheet having a sensor layer capable of detecting pressure distribution, and an elastically deformable intermediate layer disposed on the surface of the sensor layer, the sensor sheet detecting a pressure distribution waveform including a gradient component of a user's foot pressure input to the sensor layer via the intermediate layer, a control unit calculating the gradient component based on the pressure distribution waveform, and a processing device measuring the gradient or posture of the user's foot based on the output of the control unit. (14) The bioinformation measurement system according to (13), further comprising at least one of an inertial sensor, a vibration sensor, and a camera that detects the movement of the user. (15) The bioinformation measurement system according to (13) or (14), wherein the processing device generates image information for displaying on a screen at least one of the vertical load, center of gravity position, and gradient component force of the user's foot, or changes over time thereof. (16) An insole comprising: a sensor sheet having a sensor layer capable of detecting pressure distribution; and an intermediate layer arranged on the surface of the sensor layer and elastically deformable, the sensor sheet detecting a pressure distribution waveform including a gradient component of a user's foot pressure input to the sensor layer via the intermediate layer; and a control unit calculating the gradient component based on the pressure distribution waveform.(17) Footwear comprising an insole having: a sensor layer capable of detecting pressure distribution; and an intermediate layer arranged on the surface of the sensor layer and elastically deformable, the sensor sheet detecting a pressure distribution waveform including a gradient component of a user's foot pressure input to the sensor layer via the intermediate layer; and a control unit calculating the gradient component based on the pressure distribution waveform.

[0137] DESCRIPTION OF SYMBOLS 10...Pressure detection device (biological information detection device) 11...Sensor sheet 12...Control unit 13...Memory unit 14...Communication unit 15...Battery 20...Processing device 31...Display unit 32...Server 40...Midsole 41...Insole 42...Sensor layer 42F...First sensor layer 42B...Second sensor layer 42M...Third sensor layer 43...Intermediate layer 44...Outermost layer 100...Biological information measurement system 121...Pressure sensor 122...Sensor electrode layer 125...Reference electrode layer 127...Deformation layer 128...Sensing unit (capacitive element)

Claims

1. A biometric information detection device comprising: a sensor sheet having a sensor layer capable of detecting pressure distribution; an intermediate layer arranged on the surface of the sensor layer and capable of elastically deforming; the sensor sheet detecting a pressure distribution waveform including a gradient component of a user's foot pressure input to the sensor layer via the intermediate layer; and a control unit calculating the gradient component based on the pressure distribution waveform.

2. A bioinformation detection device as described in claim 1, wherein the control unit separately calculates the tilt component in the forefoot area, which is the area on the toe side, and the tilt component in the rearfoot area, which is the area on the heel side, based on the pressure distribution waveform.

3. A biological information detection device according to claim 2, wherein the control unit further calculates at least one of the vertical load and the center of gravity position in the forefoot and rearfoot based on the pressure distribution waveform.

4. A bioinformation detection device according to claim 3, wherein the control unit further calculates a vertical load in the midfoot, which is the region between the forefoot and the rearfoot, based on the pressure distribution waveform.

5. A biological information detection device according to claim 2, wherein the sensor layer is an electrostatic sensor having a plurality of capacitance elements.

6. A biological information detection device according to claim 5, wherein the arrangement interval of the plurality of capacitance elements in the forefoot is narrower than the arrangement interval of the plurality of capacitance elements in the hindfoot.

7. A biological information detection device according to claim 5, wherein the number of the plurality of capacitance elements in the forefoot is greater than the number of the plurality of capacitance elements in the hindfoot.

8. A bioinformation detection device according to claim 5, wherein the sensor layer has a sensor electrode layer in which the plurality of capacitance elements are arranged in a matrix, a reference electrode layer connected to a reference potential, and a deformation layer disposed between the sensor electrode layer and the reference electrode layer.

9. A bioinformation detection device as described in claim 1, wherein the control unit separates the pressure distribution waveform into a first region where the gradient component is relatively dominant and a second region where the shear component is relatively dominant, and calculates the gradient component based on the first region.

10. A bioinformation detection device as described in claim 9, wherein the control unit sets a region of the pressure distribution waveform where the pressure value is equal to or greater than a predetermined threshold as a first region, and sets a region where the pressure value is less than the predetermined threshold as a second region.

11. A biological information detection device according to claim 10, wherein the control unit acquires image data including the pressure distribution waveform, and performs image processing on the image data to set the predetermined threshold value.

12. A biometric information detection device as described in claim 10, wherein the control unit calculates the inclination angle of the first region with respect to a direction parallel to the sensor sheet, and calculates the inclination component based on the inclination angle.

13. A biometric information measurement system comprising: a sensor sheet having a sensor layer capable of detecting pressure distribution; an elastically deformable intermediate layer disposed on the surface of the sensor layer; the sensor sheet detecting a pressure distribution waveform including a gradient component of a user's foot pressure input to the sensor layer via the intermediate layer; a control unit calculating the gradient component based on the pressure distribution waveform; and a processing device measuring the gradient or posture of the user's foot based on the output of the control unit.

14. The biometric information measurement system according to claim 13, further comprising at least one of an inertial sensor, a vibration sensor, and a camera for detecting the movement of the user.

15. A biometric information measuring system as described in claim 13, wherein the processing device generates image information for displaying on a screen at least one of the vertical load on the user's foot, the position of the center of gravity and the force of the tilt component, or changes in these over time.

16. An insole comprising: a sensor sheet having a sensor layer capable of detecting pressure distribution; an intermediate layer arranged on the surface of the sensor layer and elastically deformable; the sensor sheet detecting a pressure distribution waveform including a gradient component of a user's foot pressure input to the sensor layer via the intermediate layer; and a control unit calculating the gradient component based on the pressure distribution waveform.

17. Footwear comprising an insole having a sensor layer capable of detecting pressure distribution, an elastically deformable intermediate layer arranged on the surface of the sensor layer, a sensor sheet that detects a pressure distribution waveform including a gradient component of a user's foot pressure input to the sensor layer via the intermediate layer, and a control unit that calculates the gradient component based on the pressure distribution waveform.

Images