JP7847134B2 - Information processing device, electronic device, information processing system, information processing method, and program - Google Patents

Description

Cross-reference to related applications

This application claims priority to Japanese Patent Application No. 2021-090694, filed in Japan on 28 May 2021, and the entire disclosure of the earlier application is incorporated herein by reference.

This disclosure relates to information processing equipment, electronic equipment, information processing systems, information processing methods, and programs.

Conventionally, techniques for evaluating the load applied to a user's joints are known.

For example, the joint load visualization system described in Patent Document 1 includes a distance camera for measuring a person's three-dimensional posture, a force sensor, and a calculation means. The force sensor detects the magnitude and direction of the force and moment applied to a device in contact with the person's hand. The calculation means calculates the joint load of a multi-joint link model that mimics a human, based on the posture information of the person acquired by the distance camera and the force and moment information acquired by the force sensor.

For example, the system described in Patent Document 2 comprises a first detection assembly that detects characteristics related to the physiological function of a joint, a second detection assembly that detects characteristics related to the structure of the joint, and a health status evaluation unit. The health status evaluation unit evaluates the health status of the joint by interpreting the characteristics from the first and second detection assemblies.

Japanese Patent Publication No. 2016-179048 Special Publication No. 2018-521722

An information processing apparatus according to one embodiment of this disclosure is
First data regarding the movement of the user's thigh is acquired from the first sensor device.
The system includes a control unit that estimates the timing of the user's foot landing based on at least the first data, and obtains an estimated value of the load applied to the user's knee joint.

An information processing apparatus according to one embodiment of this disclosure is
Third data regarding the user's ankle movement is acquired from the third sensor device.
Based on at least the third data, the user's reference angular velocity is obtained, and the reference angular velocity is the angular velocity of the ankle during the ground contact phase when at least a portion of the foot is in contact with the ground.
The system includes a control unit that acquires an estimated value of the load applied to the user's knee joint, calculated based on the correlation between the reference angular velocity and the load applied to the knee joint, and the user's reference angular velocity.

An electronic device according to one embodiment of the present disclosure includes a notification unit that notifies the information of the estimated value acquired by the information processing device.

An information processing system according to one embodiment of this disclosure is
First COM device and
The system includes an information processing device that acquires first data relating to the movement of the user's thigh from the first sensor device,
The information processing device estimates the timing of the user's foot landing and obtains an estimated value of the load applied to the user's knee joint, based at least on the first data.

An information processing method according to one embodiment of this disclosure is:
To acquire first data regarding the movement of the user's thigh from the first sensor device,
This includes, at least, estimating the timing of the user's foot landing based on the first data, and obtaining an estimated value of the load applied to the user's knee joint.

A program according to one embodiment of this disclosure is
On the computer,
To acquire first data regarding the movement of the user's thigh from the first sensor device,
The system is configured to estimate the timing of the user's foot landing based on at least the first data, and to obtain an estimated value of the load applied to the user's knee joint.

This figure shows a schematic configuration of an information processing system according to one embodiment of the present disclosure. Figure 1 is a functional block diagram showing the configuration of the information processing system. This is a schematic diagram showing the structure of the foot. This is a diagram to explain the gait cycle. This graph shows the knee joint angle and other parameters of subjects experiencing high stress on their knee joints. This graph shows the knee joint angle and other parameters of subjects with low load on the knee joint. This graph shows the angular velocity of the thigh of subjects experiencing high loads on the knee joint. This graph shows the angular velocity of the thigh of subjects with a small load on the knee joint. This figure shows the distribution of the load applied to the knee joint with respect to the angular velocity of the thigh. This graph shows the angular velocity of the knee joint in subjects experiencing high loads on their knee joints. This graph shows the angular velocity of the knee joint in subjects with low loads applied to the knee joint. This figure shows the distribution of load applied to the knee joint with respect to the angular velocity of the ankle. Figure 1 is a flowchart showing the operation of the evaluation process performed by the electronic device shown. A functional block diagram showing the configuration of an information processing system according to another embodiment of this disclosure. Figure 14 is a sequence diagram showing the operation of the evaluation process performed by the information processing system shown. Figure 14 is a sequence diagram showing the operation of the evaluation process performed by the information processing system shown.

There is a need for a technology that can easily evaluate the load applied to a user's joints. This disclosure provides a technology that can easily evaluate the load applied to a user's joints.

Embodiments of this disclosure will be described below with reference to the drawings. In the components shown in the following drawings, the same components are denoted by the same reference numerals.

In this disclosure, "local coordinate system" refers to a coordinate system based on the position of the sensor device. The local coordinate system is composed of, for example, three mutually orthogonal axes. Hereinafter, the three axes constituting the local coordinate system are assumed to be parallel to the front-to-back, left-to-right, and up-and-down directions as viewed from the sensor device.

In this disclosure, the "global coordinate system" is a coordinate system based on the user's position in the space in which they walk. The global coordinate system is composed of, for example, three mutually orthogonal axes. Hereinafter, the three axes constituting the global coordinate system are assumed to be parallel to the front-to-back, left-to-right, and up-and-down directions as viewed from the user.

(System configuration)
The information processing system 1 shown in Figure 1 can evaluate the load applied to the knee joint of a user while walking. The information processing system 1 includes a first sensor device 10A, a second sensor device 10B, and an electronic device 20. However, the information processing system 1 does not have to include the second sensor device 10B. The information processing system 1 may include a third sensor device 10C in place of either the first sensor device A or the second sensor device 10B, or in addition to the first sensor device A and the second sensor device 10B.

Hereafter, unless otherwise specified, the first sensor device 10A, the second sensor device 10B, and the third sensor device 10C will be collectively referred to as "sensor device 10."

The sensor device 10 and the electronic device 20 can communicate with each other via a communication line. The communication line consists of at least one of wired and wireless connections.

The first sensor device 10A is positioned to detect data indicating the movement of the user's thigh. In this embodiment, the first sensor device 10A is positioned to detect data indicating the movement of the left thigh of the user's two thighs. However, the first sensor device 10A may be positioned to detect data indicating the movement of the right thigh of the user's two thighs, or it may be positioned to detect data indicating the movement of both thighs.

The first sensor device 10A is attached, for example, to the user's thigh. In this embodiment, the first sensor device 10A is attached to the left thigh of the user's two thighs. However, the first sensor device 10A may be attached to the right thigh or both thighs of the user's two thighs. The first sensor device 10A may be a wearable device. The first sensor device 10A may be attached to the user's thigh by any method. The first sensor device 10A may be attached to the user's thigh by a belt. The first sensor device 10A may be attached to the thigh by being placed in a pocket near the thigh of the trousers worn by the user. The first sensor device 10A may be attached to the user's thigh by being installed in trousers, underwear, shorts, a supporter, a prosthesis or implant, etc.

The first sensor device 10A detects first data relating to the movement of the user's thigh. The first data may be data indicating the movement of the user's thigh. The first data may include, for example, data indicating at least one of the velocity, acceleration, angle, and angular velocity of the user's thigh. The first data may be, for example, data in a local coordinate system based on the position of the first sensor device 10A.

The local coordinate system based on the position of the first sensor device 10A is composed of axes A1, A2, and A3, as shown in Figure 3 below. In Figure 3, the position of the first sensor device 10A is shown by a dashed line. Axes A1, A2, and A3 are orthogonal to each other. Axes A1 and A2 are included in the sagittal plane, for example. The sagittal plane is, for example, a plane that divides the user's body symmetrically or a plane parallel to a plane that divides the user's body symmetrically. Axe A3 intersects the sagittal plane perpendicularly, for example.

The second sensor device 10B is positioned to detect data indicating the movement of the user's foot. In this embodiment, the foot is the part from the user's ankle to the toes. In this embodiment, the second sensor device 10B is positioned to detect data indicating the movement of the left foot of the user's two feet. However, the second sensor device 10B may be positioned to detect data indicating the movement of the right foot of the user's two feet, or it may be positioned to detect data indicating the movement of both feet.

The second sensor device 10B is attached, for example, to the user's foot. In this embodiment, the second sensor device 10B is attached to the left foot of the user's two feet. However, the second sensor device 10B may be attached to the right foot or both feet of the user's two feet. The second sensor device 10B may be a shoe-type wearable device. The second sensor device 10B may be attached to the user's foot by any method. The second sensor device 10B may be provided in a shoe. The second sensor device 10B may be attached to the user's foot by being installed in an anklet, band, friendship bracelet, artificial nail, tattoo sticker, supporter, cast, sock, insole, prosthetic leg, ring or implant, etc.

The second sensor device 10B detects second data relating to the movement of the user's foot. The second data may be data indicating the movement of the user's foot. The second data may include, for example, data indicating at least one of the speed, acceleration, angle, and angular velocity of the user's foot. The second data may be, for example, data in a local coordinate system based on the position of the second sensor device 10B.

The local coordinate system based on the position of the second sensor device 10B is composed of axes B1, B2, and B3, as shown in Figure 3 below. In Figure 3, the position of the second sensor device 10B is shown by a dashed line. Axes B1, B2, and B3 are orthogonal to each other. Axes B1 and B2 are included in the sagittal plane, for example. Axe B3 intersects the sagittal plane perpendicularly, for example.

The third sensor device 10C is positioned to detect data indicating the movement of the user's ankle. In this embodiment, the third sensor device 10C is positioned to detect data indicating the movement of the left ankle of the user's two ankles. However, the third sensor device 10C may be positioned to detect data indicating the movement of the right ankle of the user's two ankles, or it may be positioned to detect data indicating the movement of both ankles.

The third sensor device 10C is attached, for example, to the user's ankle. In this embodiment, the third sensor device 10C is attached to the left ankle of the user's two ankles. However, the third sensor device 10C may be attached to the right ankle or both ankles of the user's two ankles. The third sensor device 10C may be a wearable device. The third sensor device 10C may be attached to the user's ankle by a belt. The third sensor device 10C may be attached to the user's ankle by any method. The third sensor device 10C may be attached to the user's ankle by being installed on an anklet, band, friendship bracelet, tattoo sticker, supporter, cast, sock, prosthesis or implant, etc.

The third sensor device 10C detects third data relating to the movement of the user's ankle. The third data may be data indicating the movement of the user's ankle. The third data may include, for example, data indicating at least one of the velocity, acceleration, angle, and angular velocity of the user's ankle. The third data may be, for example, data in a local coordinate system based on the position of the third sensor device 10C.

The local coordinate system based on the position of the third sensor device 10C is composed of axes C1, C2, and C3, as shown in Figure 3 below. In Figure 3, the position of the third sensor device 10C is shown by a dashed line. Axes C1, C2, and C3 are orthogonal to each other. Axes C1 and C2 are included in the sagittal plane, for example. Axe C3 intersects the sagittal plane perpendicularly, for example.

In the following, unless otherwise specified, the first data detected by the first sensor device 10A, the second data detected by the second sensor device 10B, and the third data detected by the third sensor device 10C will be collectively referred to as "data."

The electronic device 20 is carried by the user while walking. In this embodiment, the electronic device 20 functions as an information processing device and obtains an estimated value of the load applied to the user's knee joint based on the data detected by the sensor device 10. The electronic device 20 is, for example, a mobile device such as a mobile phone, smartphone, or tablet.

As shown in Figure 2, the sensor device 10 is composed of a communication unit 11, a sensor unit 12, a storage unit 13, and a control unit 14.

The communication unit 11 comprises at least one communication module capable of communicating with the electronic device 20 via a communication line. The communication module is a communication module that conforms to the communication line standard. The communication line standard is a short-range wireless communication standard that includes, for example, Bluetooth®, Wi-Fi®, infrared, and NFC (Near Field Communication).

The sensor unit 12 is configured to include any sensor corresponding to the data to be detected by the sensor device 10. For example, the sensor unit 12 is configured to include at least one of a 3-axis motion sensor, a 3-axis acceleration sensor, a 3-axis velocity sensor, a 3-axis gyroscope sensor, a 3-axis geomagnetic sensor, and a camera. If the sensor unit 12 is configured to include a camera, data indicating the movement of a part of the user's body can be detected by analyzing the image generated when the camera captures a part of that part of the user's body.

The storage unit 13 is configured to include at least one semiconductor memory, at least one magnetic memory, at least one optical memory, or at least two combinations thereof. The semiconductor memory is, for example, RAM (Random Access Memory) or ROM (Read Only Memory). The RAM is, for example, SRAM (Static Random Access Memory) or DRAM (Dynamic Random Access Memory). The ROM is, for example, EEPROM (Electrically Erasable Programmable Read Only Memory). The storage unit 13 may function as a main memory, auxiliary memory, or cache memory. The storage unit 13 stores data used for the operation of the sensor device 10 and data obtained from the operation of the sensor device 10. For example, the storage unit 13 stores system programs, application programs, and embedded software.

The control unit 14 is configured to include at least one processor, at least one dedicated circuit, or a combination thereof. The processor is a general-purpose processor such as a CPU (Central Processing Unit) or GPU (Graphics Processing Unit), or a dedicated processor specialized for a specific process. The dedicated circuit is, for example, an FPGA (Field-Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit). The control unit 14 controls each part of the sensor device 10 and executes processes related to the operation of the sensor device 10.

The control unit 14 receives a signal from the electronic device 20 via the communication unit 11 to instruct it to start data detection. Upon receiving this signal, the control unit 14 starts data detection. For example, the control unit 14 acquires data detected by the sensor unit 12. The control unit 14 transmits the acquired data to the electronic device 20 via the communication unit 11.

The control unit 14 acquires data from the sensor unit 12 at a preset time interval and transmits the acquired data via the communication unit 11. This time interval may be set based on the walking speed of a typical user. If the information processing system 1 includes a first sensor device 10A and a second sensor device 10B, this time interval may be the same for the first sensor device 10A and the second sensor device 10B. By having the same time interval for the first sensor device 10A and the second sensor device 10B, the timing at which each of the first sensor device 10A and the second sensor device 10B detects data can be synchronized. If the information processing system 1 includes a third sensor device 10C in addition to the first sensor device 10A, this time interval may be the same for the first sensor device 10A and the third sensor device 10C. In other words, this time interval may be the same for all sensor devices 10 included in the information processing system 1.

As shown in Figure 2, the electronic device 20 is composed of a communication unit 21, an input unit 22, a notification unit for notifying information, a storage unit 24, and a control unit 25. In this embodiment, the notification unit is an output unit 23. However, the notification unit is not limited to an output unit 23.

The communication unit 21 is configured to include at least one communication module capable of communicating with the sensor device 10 via a communication line. The communication module is a communication module that conforms to the communication line standard. The communication line standard is a short-range wireless communication standard that includes, for example, Bluetooth®, Wi-Fi®, infrared, and NFC.

The communication unit 21 may further include at least one communication module that can connect to the network 2 as shown in Figure 14, which will be described later. The communication module is, for example, a communication module that supports mobile communication standards such as LTE (Long Term Evolution), 4G (4th Generation), or 5G (5th Generation).

The input unit 22 is capable of receiving input from the user. The input unit 22 is configured to include at least one input interface capable of receiving input from the user. The input interface is, for example, a physical key, a capacitive key, a pointing device, a touchscreen integrated with a display, or a microphone.

The output unit 23 is capable of outputting data. The output unit 23 is configured to include at least one output interface capable of outputting data. The output interface is, for example, a display or a speaker. The display is, for example, an LCD or an organic EL display.

The storage unit 24 is configured to include at least one semiconductor memory, at least one magnetic memory, at least one optical memory, or a combination of at least two of these. The semiconductor memory is, for example, RAM or ROM. RAM is, for example, SRAM or DRAM. ROM is, for example, EEPROM. The storage unit 24 may function as a main memory, auxiliary memory, or cache memory. The storage unit 24 stores data used for the operation of the electronic device 20 and data obtained through the operation of the electronic device 20. For example, the storage unit 24 stores system programs, application programs, and embedded software.

The control unit 25 is configured to include at least one processor, at least one dedicated circuit, or a combination thereof. The processor is a general-purpose processor such as a CPU or GPU, or a dedicated processor specialized for a specific process. The dedicated circuit is, for example, an FPGA or ASIC. The control unit 25 controls each part of the electronic device 20 and executes processes related to the operation of the electronic device 20.

The control unit 25 receives an input from the input unit 22 that instructs it to execute an evaluation process. This input causes the electronic device 20 to perform a process to evaluate the load applied to the knee joint. This input is, for example, received from the input unit 22 by a user wearing the sensor device 10. The user, for example, enters this input from the input unit 22 before starting to walk. When the control unit 25 receives this input from the input unit 22, it sends a signal to the sensor device 10 via the communication unit 21 that instructs it to start data detection.

If the information processing system 1 includes a first sensor device 10A and a second sensor device 10B, the control unit 25 may transmit a signal instructing the start of data detection as a broadcast signal to the first sensor device 10A and the second sensor device 10B via the communication unit 21. By transmitting a signal instructing the start of data detection as a broadcast signal to the first sensor device 10A and the second sensor device 10B, the multiple sensor devices 10 can start data detection simultaneously. If the information processing system 1 includes a third sensor device 10C in addition to the first sensor device 10A, the control unit 14 may transmit a signal instructing the start of data detection as a broadcast signal to the third sensor device 10C in addition to the first sensor device 10A, etc. via the communication unit 21. In other words, the control unit 14 may transmit a signal instructing the start of data detection as a broadcast signal to all sensor devices 10 included in the information processing system 1 via the communication unit 21.

The control unit 25 receives data detected by the sensor device 10 via the communication unit 21. The control unit 25 acquires data from the sensor device 10 by receiving the data from the sensor device 10. Based on at least the first data, the control unit 25 estimates the landing timing of the user's foot (described later) and acquires an estimated value of the load applied to the user's knee joint. Before explaining the details of the estimated value acquisition process, the principle of acquiring the estimated value of the load applied to the knee joint will be explained with reference to Figures 3 to 9.

Referring to Figure 3, the method for calculating the load on the knee joint will be explained. Figure 3 schematically shows the structure of the foot.

Foot 30 is the user's left foot of the user's two feet. Foot 30 includes a foot portion 31, a shin portion 32, a knee joint 33, and a thigh portion 34. The knee joint 33 is located between the shin portion 32 and the thigh portion 34. In the schematic configuration shown in Figure 3, the shin portion 32 and the thigh portion 34 are each considered as axes.

The load applied to the knee joint 33 is calculated by the product of the reaction force Fy of the knee joint 33 and the angular velocity ωz of the knee joint 33.

The reaction force Fy of the knee joint 33 is, for example, a force along the axial direction of the shin 32. The positive direction of the reaction force Fy of the knee joint 33 is, for example, the direction from the foot 31 toward the knee joint 33 within the axial direction of the shin 32. The reaction force Fy of the knee joint 33 is the sum of the force with which the knee joint 33 presses the shin 32 due to the weight of the thigh 34 and the upper body above the waist, the reaction force with which the shin 32 is pressed against the thigh 34 by the ground reaction force received from the ground via the foot 31, and the tension of the muscles that move the knee joint 33. Because these forces act in the negative direction of the reaction force Fy, the direction of these forces is the negative direction of the reaction force Fy. The muscles that move the knee joint 33 include, for example, the vastus lateralis and the vastus intermedius.

The angle of the knee joint 33 is expressed as the relative angle of the tibia 32 with respect to the thigh 34, with the extended state of the knee joint 33 being zero degrees. The positive direction of the angle of the knee joint 33 is, for example, the direction of rotation from the thigh 34 toward the user's rear, among the rotational directions around the knee joint 33 in the sagittal plane. The angular velocity ωz of the knee joint 33 is the angular velocity of the knee joint 33 in the sagittal plane. The positive direction of the angular velocity ωz of the knee joint 33 is, like the angle of the knee joint 33, for example, the direction of rotation from the thigh 34 toward the user's rear, among the rotational directions around the knee joint 33 in the sagittal plane.

Refer to Figure 4 to explain the user's gait cycle. The upper part of Figure 4 shows the user's gait. In Figure 4, the user's left foot is labeled with the letter L, and the right foot is labeled with the letter R. Figure 4 shows the user's gait from the moment the left foot lands on the ground until the left foot lands on the ground again.

The gait cycle is the period from when one of the user's two feet lands on the ground until it lands again. The start and end points of the gait cycle are the landing timing of one of the user's two feet. Landing timing is the moment when the foot lands on the ground. For example, in Figure 4, the gait cycle is the period from when the left foot of the user's two feet lands on the ground until it lands again. The gait cycle includes the stance phase and the swing phase.

The stance phase is the period from when one of the user's two feet touches the ground until it leaves the ground. The starting point of the stance phase is the moment when one of the user's two feet touches the ground. In Figure 4, the stance phase is the period from when the user's left foot touches the ground until it leaves the ground.

The ground contact phase is the period during which at least a portion of one of the user's two feet is in contact with the ground. The ground contact phase may be the period during which any portion of one of the user's two feet is in contact with the ground. The ground contact phase is part of the stance phase. In this embodiment, the ground contact phase is the period from the landing of one of the user's two feet until the heel of that foot leaves the ground. The ground contact phase may include the heel strike phase. The heel strike phase is the period during which the heel of one of the user's two feet is in contact with the ground. In Figure 4, the ground contact phase is the period from the landing of the left foot until the heel of the left foot leaves the ground.

The swing phase is the period from when one of the user's two feet leaves the ground until it lands on the ground. The start of the swing phase is the end of the stance phase. In Figure 4, the swing phase is the period from when the user's left foot leaves the ground until it lands on the ground.

Referring to Figures 5 and 6, we will explain that there is a correlation between the angular velocity of the knee joint and the load applied to the knee joint.

Figure 5 shows graphs of knee joint angle [deg], knee joint angular velocity [deg/s], vastus lateralis muscle tension [N], knee joint reaction force [N], and knee joint load [N・deg/s] for subjects with high loads on the knee joint.

Figure 6 shows graphs of knee joint angle [deg], knee joint angular velocity [deg/s], vastus lateralis muscle tension [N], knee joint reaction force [N], and knee joint load [N・deg/s] for subjects with a small load on the knee joint.

The horizontal axes in Figures 5 and 6 correspond to the gait cycle. In Figures 5 and 6, the gait cycle is shown as a normalized value from 0 to 1. The stance phase corresponds to the period from 0 to 0.75 on the horizontal axis. The ground contact phase corresponds to the period from 0 to 0.4 on the horizontal axis. The swing phase corresponds to the period from 0.75 to 1 on the horizontal axis.

The data for knee joint angular velocity, vastus lateralis muscle tension, and load applied to the knee joint shown in Figures 5 and 6 were obtained by inverse dynamics calculations. The knee joint angle and knee joint reaction force shown in Figures 5 and 6 were also used in the inverse dynamics calculations. Inverse dynamics calculations are a method for calculating the joint angular velocity and muscle force necessary to realize the subject's movement obtained through measurements. The data for the subject's knee joint angle, etc., used in the inverse dynamics calculations were obtained from data provided in "Yoshiyuki Kobayashi, Naoto Hida, Kanako Nakajima, Masahiro Fujimoto, Masaaki Mochimaru, "2019: AIST Walking Database 2019", [Online], [Retrieved May 24, 2021], Internet <https://unit.aist.go.jp/harc/ExPART/GDB2019_e.html>". This walking database contains walking data from multiple subjects. This subject's walking data was detected by a motion capture system and a force plate. The methods used for inverse dynamics calculations were those described in "OpenSim: Open-Source Software to Create and Analyze Dynamic Simulations of Movement" by Scott L. Delp et al., IEEE Transactions on Biomedical Engineering, 2007, Volume: 54, Issue: 11, pp. 1940-1950, the method described in "[Online] [Retrieved May 24, 2021], Internet <https://simtk-confluence.stanford.edu/display/OpenSim/Getting+Started+with+CMC>", and the method described in "Generating dynamic simulations of movement using computed muscle control" by Thelen D.G. et al., Journal of Biomechanics, 2003, Volume: 36, pp. 321-328.

As shown in Figure 5, in subjects with a large load on the knee joint, the knee joint angle is greater than 0 degrees during the ground contact phase, from 0 to 0.4 on the horizontal axis. In other words, in subjects with a large load on the knee joint, the knee joint is bent during the ground contact phase. Furthermore, the knee joint angle reaches a positive peak value around 0.1 on the horizontal axis during the ground contact phase.

As shown in Figure 6, in subjects with a small load on the knee joint, the knee joint angle is maintained at approximately 0 degrees (i.e., a constant value) during the ground contact phase, from 0 to 0.4 on the horizontal axis. In other words, in subjects with a small load on the knee joint, the knee joint is maintained in an almost extended state during the ground contact phase.

As shown in Figure 5, in subjects with a large load on the knee joint, the angular velocity of the knee joint shows fluctuations during the ground contact period from 0 to 0.4 on the horizontal axis. The angular velocity of the knee joint reaches a positive peak value around 0.04 on the horizontal axis. This positive peak value is the first positive peak value of the knee joint angular velocity from the landing timing. The angular velocity of the knee joint decreases from around 0.04 to around 0.2 on the horizontal axis. The angular velocity of the knee joint reaches a negative peak value around 0.2 on the horizontal axis. This negative peak value is the first negative peak value of the knee joint angular velocity from the landing timing.

As shown in Figure 6, in subjects with a small load on the knee joint, the angular velocity of the knee joint is maintained at approximately 0 [deg/s], i.e., a constant value, during the ground contact phase from 0 to 0.4 on the horizontal axis. In subjects with a small load on the knee joint, the knee joint is almost extended during the ground contact phase, so the angular velocity of the knee joint is maintained at approximately 0 [deg/s].

As shown in Figure 5, in subjects with a heavy load on the knee joint, the tension of the vastus lateralis muscle exceeds 0 [N] during the ground contact phase, from 0 to 0.4 on the horizontal axis. In subjects with a heavy load on the knee joint, the knee joint is bent during the ground contact phase, so the tension of the vastus lateralis muscle, which moves the knee joint, exceeds 0 [N]. Also, the tension of the vastus lateralis muscle reaches a positive peak value around 0.1 on the horizontal axis.

As shown in Figure 6, in subjects with a small load on the knee joint, the tension of the vastus lateralis muscle is maintained at approximately 0 [N] during the ground contact phase, from 0 to 0.4 on the horizontal axis. In subjects with a small load on the knee joint, the knee joint is maintained in a nearly extended state during the ground contact phase, and therefore the tension of the vastus lateralis muscle, which moves the knee joint, is maintained at approximately 0 [N].

As shown in Figure 5, in subjects with a large load on the knee joint, the knee joint reaction force shows greater fluctuations during the ground contact phase from 0 to 0.4 on the horizontal axis compared to subjects with a small load on the knee joint, as shown in Figure 6. As described above with reference to Figure 3, the knee joint reaction force is obtained by subtracting the tension of the muscles that move the knee joint, such as the vastus lateralis and vastus intermedius, from the ground reaction force that the knee joint receives from the ground via the foot, etc. In subjects with a large load on the knee joint, the knee joint reaction force has a negative peak value around 0.1 on the horizontal axis, where the tension of the vastus lateralis muscle reaches a positive peak value.

As shown in Figure 6, in subjects with a small load on the knee joint, the knee joint reaction force shows smaller fluctuations during the ground contact phase (from 0 to 0.4 on the horizontal axis) compared to subjects with a large load on the knee joint, as shown in Figure 5. As described above with reference to Figure 3, the knee joint reaction force is obtained by subtracting the tension of the muscles that move the knee joint, such as the vastus lateralis and vastus intermedius, from the ground reaction force that the knee joint receives from the ground via the foot, etc. As described above, in subjects with a small load on the knee joint, the tension of the vastus lateralis is maintained at approximately 0 [N] during the ground contact phase. Because the tension of the muscles that move the knee joint, such as the vastus lateralis, is maintained at approximately 0 [N], in subjects with a small load on the knee joint, the knee joint reaction force is mainly influenced by the ground reaction force that the knee joint receives from the ground.

As shown in Figure 5, in subjects with a large load on the knee joint, the load on the knee joint shows greater fluctuations during the ground contact phase from 0 to 0.4 on the horizontal axis compared to subjects with a small load on the knee joint, as shown in Figure 6. As described above with reference to Figure 3, the load on the knee joint is calculated by the product of the knee joint reaction force and the knee joint angular velocity. During the ground contact phase, the load on the knee joint has a negative peak value around 0.04 on the horizontal axis, where the knee joint angular velocity has a positive peak value.

As shown in Figure 6, in subjects with a small load on the knee joint, the load on the knee joint is maintained at approximately 0 [N·deg/s] during the ground contact phase, from 0 to 0.4 on the horizontal axis. As described above with reference to Figure 3, the load on the knee joint is calculated by the product of the knee joint reaction force and the knee joint angular velocity. In subjects with a small load on the knee joint, the knee joint angular velocity is maintained at approximately 0 [deg/s] during the ground contact phase, and therefore the load on the joint is also maintained at approximately 0 [N·deg/s].

Thus, a correlation exists between the angular velocity of the knee joint during the ground contact phase and the load applied to the knee joint. For example, as shown in Figure 5, in subjects with a large load on the knee joint, the load on the knee joint peaks negatively around 0.04 on the horizontal axis, where the angular velocity of the knee joint peaks positively. Also, as shown in Figure 6, in subjects with a small load on the knee joint, the load on the knee joint is maintained at approximately 0 [N·deg/s] because the angular velocity of the knee joint is maintained at approximately 0 [deg/s].

Therefore, if the angular velocity of the knee joint during the user's ground contact phase can be obtained, the load applied to the user's knee joint can be determined based on the correlation between the angular velocity of the knee joint during the ground contact phase and the load applied to the knee joint.

Referring to Figures 7 and 8, we will explain that there is a correlation between the angular velocity of the thigh and the load applied to the knee joint.

Figure 7 shows a graph of the angular velocity [deg/s] of the thigh of subjects with high loads on the knee joint. Figure 7 also shows graphs of the angular velocity [deg/s] of the thigh of subjects in both the local and global coordinate systems. Figure 7 also shows the graphs of the knee joint angle [deg] and knee joint angular velocity [deg/s] shown in Figure 5.

Figure 8 shows a graph of the angular velocity [deg/s] of the thigh of subjects with a small load on the knee joint. Figure 8 also shows graphs of the angular velocity [deg/s] of the thigh of subjects in both the local and global coordinate systems. Figure 8 also shows the graphs of the knee joint angle [deg] and knee joint angular velocity [deg/s] shown in Figure 6.

The horizontal axes in Figures 7 and 8, like the horizontal axes in Figures 5 and 6, correspond to the gait cycle.

The angular velocity data for the thigh shown in Figures 7 and 8 were obtained by inverse dynamics calculations, in the same or similar manner as the data for the angular velocity of the knee joint shown in Figures 5 and 6.

As shown in Figures 7 and 8, the angular velocity of the thigh in the global coordinate system is approximately the same as the angular velocity of the thigh in the local coordinate system. In other words, the angular velocity of the thigh in the local coordinate system detected by the first sensor device 10A may be used as the angular velocity of the thigh in the global coordinate system. Hereafter, when there is no particular distinction between the angular velocity of the thigh in the global coordinate system and the angular velocity of the thigh in the local coordinate system, these will be collectively referred to as "angular velocity of the thigh."

As shown in Figure 7, in subjects with a large load on the knee joint, the angular velocity of the thigh shows similar fluctuations to the angular velocity of the knee joint. For example, as mentioned above, the angular velocity of the knee joint decreases from around 0.04 to around 0.2 on the horizontal axis. Similar to the angular velocity of the knee joint, the angular velocity of the thigh decreases from 0 on the horizontal axis, i.e., the landing timing, to around 0.2 on the horizontal axis. Also, similar to the angular velocity of the knee joint, the angular velocity of the thigh reaches a negative peak value around 0.2 on the horizontal axis.

As shown in Figure 8, in subjects with a small load on the knee joint, the angular velocity of the thigh shows similar fluctuations to the angular velocity of the knee joint. For example, as mentioned above, the angular velocity of the knee joint is maintained at approximately 0 [deg/s], i.e., a constant value, during the ground contact period from 0 to 4 on the horizontal axis. Similar to the angular velocity of the knee joint, the angular velocity of the thigh is maintained at a negative constant value during the ground contact period from 0 to 4 on the horizontal axis.

Thus, during the ground contact phase, the angular velocity of the thigh shows similar fluctuations to those of the knee joint. One reason for this is that the thigh and knee joint move in coordination. As mentioned above, there is a correlation between the angular velocity of the knee joint during the ground contact phase and the load applied to the knee joint. Because the angular velocity of the thigh shows similar fluctuations to those of the knee joint during the ground contact phase, there is a correlation between the angular velocity of the thigh during the ground contact phase and the load applied to the knee joint, similar to the angular velocity of the knee joint.

Figure 9 shows the distribution of the load applied to the knee joint in relation to the angular velocity of the thigh. The horizontal axis of Figure 9 represents the negative peak value of the angular velocity of the thigh during the ground contact phase. The vertical axis of Figure 9 represents the negative peak value of the load applied to the knee joint during the ground contact phase. By performing regression analysis on the distribution shown in Figure 9, the regression equation (y = -64.72x - 4267.2) was obtained. The correlation coefficient was 0.8. It can be seen that there is a strong correlation between the angular velocity of the thigh during the ground contact phase and the load applied to the knee joint.

Thus, a correlation exists between the angular velocity of the thigh during the ground contact phase and the load applied to the knee joint. Therefore, if the angular velocity of the user's thigh during the ground contact phase can be obtained, the load applied to the user's knee joint can be determined based on the correlation between the angular velocity of the thigh during the ground contact phase and the load applied to the knee joint.

Referring to Figures 10 and 11, we will explain that there is a correlation between the angular velocity of the ankle and the load applied to the knee joint.

Figure 10 shows graphs of knee joint angle [deg], ankle angular velocity [deg/s], vastus lateralis muscle tension [N], knee joint reaction force [N], and knee joint load [N・deg/s] for subjects with high knee joint loads. Of these graphs, all except the ankle angular velocity [deg/s] graph are the same as those shown in Figure 5.

Figure 11 shows graphs of knee joint angle [deg], ankle angular velocity [deg/s], vastus lateralis muscle tension [N], knee joint reaction force [N], and knee joint load [N・deg/s] for subjects with a small load on the knee joint. Of these graphs, all except the ankle angular velocity [deg/s] graph are the same as those shown in Figure 6.

The horizontal axes in Figures 10 and 11 correspond to the gait cycle, just like the horizontal axes in Figures 5 and 6.

The ankle angular velocity data shown in Figures 10 and 11 were obtained by inverse dynamics calculations, in the same or similar manner as the knee joint angular velocity data shown in Figures 5 and 6.

In Figures 10 and 11, the ankle angular velocity is the ankle angular velocity in the sagittal plane.

As shown in Figure 10, in subjects with a large load on the knee joint, the ankle angular velocity shows fluctuations during the ground contact period from 0 to 0.4 on the horizontal axis. The ankle angular velocity reaches a negative peak value around 0.04 on the horizontal axis. This negative peak value is the first negative peak value of the ankle angular velocity from the landing timing. The ankle angular velocity increases from around 0.04 to around 0.2 on the horizontal axis. The ankle angular velocity reaches a positive peak value around 0.2 on the horizontal axis. This positive peak value is the first positive peak value of the ankle angular velocity from the landing timing. This fluctuation in ankle angular velocity is similar to the fluctuation in knee joint angular velocity shown in Figure 5.

As shown in Figure 11, in subjects with a small load on the knee joint, the ankle angular velocity is maintained at approximately 0 [deg/s], i.e., a constant value, during the ground contact phase from 0 to 0.4 on the horizontal axis. In subjects with a small load on the knee joint, the knee joint is almost extended during the ground contact phase. Therefore, the ankle angular velocity is maintained at approximately 0 [deg/s]. This variation in ankle angular velocity is similar to the variation in knee joint angular velocity shown in Figure 6.

Thus, during the ground contact phase, the angular velocity of the ankle shows similar fluctuations to those of the knee joint, as shown in Figures 5 and 6. One reason for this is that the ankle and knee joints move in coordination. As mentioned above, there is a correlation between the angular velocity of the knee joint during the ground contact phase and the load applied to the knee joint. Because the angular velocity of the ankle shows similar fluctuations to those of the knee joint during the ground contact phase, a correlation exists between the angular velocity of the ankle during the ground contact phase and the load applied to the knee joint, similar to the correlation between the angular velocity of the knee joint and those applied to the knee joint.

Figure 12 shows the distribution of the load applied to the knee joint in relation to the angular velocity of the ankle. The horizontal axis of Figure 12 represents the negative peak value of the angular velocity of the ankle during the ground contact phase. The vertical axis of Figure 12 represents the negative peak value of the load applied to the knee joint during the ground contact phase. By performing regression analysis on the distribution shown in Figure 12, the regression equation (y = -0.0008x + 0.0686) was obtained. The correlation coefficient was 0.6456. It can be seen that there is a strong correlation between the angular velocity of the ankle during the ground contact phase and the load applied to the knee joint.

[Process for obtaining estimated values]
The control unit 25 estimates the timing of the user's foot landing based on at least the first data and obtains the user's reference angular velocity. The reference angular velocity is the angular velocity of the thigh or the knee joint during the ground contact phase. As described above, the angular velocity of the thigh or the knee joint during the ground contact phase has a correlation with the load applied to the knee joint. Therefore, the reference angular velocity has a correlation with the load applied to the knee joint.

The control unit 25 obtains an estimated value of the load applied to the user's knee joint, calculated based on the correlation between the reference angular velocity and the load applied to the knee joint, and the user's reference angular velocity. The control unit 25 may use a regression equation obtained from a distribution as shown in Figure 9 as the correlation, or it may use a learning model that has learned the correlation between the reference angular velocity and the load applied to the knee joint. When using a regression equation as the correlation, the control unit 25 obtains the estimated value of the load applied to the knee joint by calculating it using the acquired user's reference angular velocity and the regression equation. The learning model is, for example, a neural network learning model. The learning model may calculate and output a score indicating the estimated value of the load applied to the knee joint when reference angular velocity information is input. When using a learning model as the correlation, the control unit 25 inputs the acquired user's reference angular velocity information into the learning model and obtains a score indicating the estimated value of the load applied to the knee joint calculated by the learning model. The regression equation or learning model is, for example, acquired in advance and stored in the memory unit 24.

The following examples illustrate cases where the reference angular velocity is the angular velocity of the thigh, and cases where the reference angular velocity is the angular velocity of the knee joint.

<Example 1>
The reference angular velocity may be the angular velocity of the thigh during the ground contact phase. In other words, the control unit 25 may obtain an estimated value of the load applied to the user's knee joint based on the correlation between the angular velocity of the thigh during the ground contact phase and the load applied to the knee joint, and the user's angular velocity of the thigh during the ground contact phase. In this case, the control unit 25 estimates the user's landing timing and obtains the user's angular velocity of the thigh during the ground contact phase based on at least the first data. The control unit 25 may obtain the user's angular velocity of the thigh according to the correlation.

As an example, the control unit 25 may use the correlation between the negative peak value of the angular velocity of the thigh during the ground contact phase and the load applied to the knee joint. In this case, the control unit 25 obtains the negative peak value of the user's thigh angular velocity during the ground contact phase as the user's thigh angular velocity according to the correlation. For example, as will be described later, the control unit 25 estimates the landing timing based on the first data or the second data. Once the landing timing is estimated, the control unit 25 obtains the first negative peak value of the user's thigh angular velocity from the landing timing using only the first data. As can be seen from Figure 7, the first negative peak value of the thigh angular velocity from the landing timing is the negative peak value of the thigh angular velocity during the ground contact phase. Here, as shown in Figure 8, for users with a small load applied to the knee joint, the negative peak value of the thigh angular velocity may not appear during the ground contact phase. In this case, it is expected that the negative peak value of the thigh angular velocity cannot be obtained during the ground contact phase. Therefore, if the control unit 25 cannot obtain a negative peak value of the angular velocity of the thigh within the first time T1a as shown in Figure 8 from the landing timing, it may obtain the user's thigh angular velocity at the time after the second time T2 has elapsed from the landing timing using the first data. The first time T1a may be set based on the average value of the length of the contact period, etc. The second time T2 may be set based on the average value of the time from the landing timing until a negative peak value appears in the angular velocity of the thigh, etc.

As another example, the control unit 25 may use the correlation between the angular velocity of the thigh at the landing timing and the load applied to the knee joint. In this case, the control unit 25 obtains the user's thigh angular velocity at the landing timing as the user's thigh angular velocity according to the correlation. For example, as will be described later, the control unit 25 estimates the landing timing based on the first data or the second data. Once the landing timing is estimated, the control unit 25 obtains the user's thigh angular velocity at the landing timing using only the first data.

Here, the control unit 25 may estimate the landing timing based only on the first data. The control unit 25 may estimate the landing timing by estimating the ground reaction force based on at least one of the acceleration of the thigh and the angular velocity of the thigh included in the first data. The user's thigh receives a ground reaction force from the ground via the foot, etc. As the user's thigh receives the ground reaction force, the acceleration of the thigh and the angular velocity of the thigh fluctuate in accordance with the fluctuation of the ground reaction force. In other words, the fluctuation of the ground reaction force can be estimated from the fluctuation of at least one of the acceleration of the thigh and the angular velocity of the thigh. Furthermore, the ground reaction force fluctuates when the user's foot lands on the ground. In other words, the landing timing can be estimated by estimating the fluctuation of the ground reaction force based on at least one of the acceleration of the thigh and the angular velocity of the thigh.

The control unit 25 may estimate the landing timing based on the second data. Since the second data represents the movement of the foot, the landing timing, which is the moment the foot touches the ground, can be estimated using the second data. By using the second data representing the movement of the foot, the landing timing can be estimated with high accuracy.

When the control unit 25 obtains the angular velocity of the user's thigh, it obtains an estimated value of the load applied to the user's knee joint based on the correlation and the obtained angular velocity of the user's thigh. As an example, the control unit 25 may use a regression equation obtained from the distribution of the load applied to the knee joint with respect to the angular velocity of the thigh, as shown in Figure 9, as the correlation. In this case, the control unit 25 obtains the estimated value of the load applied to the knee joint by calculating the estimated value of the load applied to the knee joint using the obtained angular velocity of the user's thigh and the regression equation. As another example, the control unit 25 may use a learning model that has learned the correlation between the angular velocity of the thigh and the load applied to the knee joint as the correlation. The learning model may calculate and output a score indicating the estimated value of the load applied to the knee joint when information on the angular velocity of the thigh is input. In this case, the control unit 25 inputs the information on the angular velocity of the user's thigh into the learning model and obtains a score indicating the estimated value of the load applied to the knee joint calculated by the learning model.

<Example 2>
The reference angular velocity may be the angular velocity of the knee joint during the ground contact phase. In other words, the control unit 25 may obtain an estimated value of the load applied to the user's knee joint based on the correlation between the angular velocity of the knee joint during the ground contact phase and the load applied to the knee joint, and the user's angular velocity of the knee joint during the ground contact phase. In this case, the control unit 25 estimates the user's landing timing and obtains the user's angular velocity of the knee joint during the ground contact phase based on at least the first data. The control unit 25 may obtain the user's angular velocity of the knee joint according to the correlation.

As an example, the control unit 25 may use the correlation between the positive or negative peak value of the angular velocity of the knee joint during the ground contact phase and the load applied to the knee joint. In this case, the control unit 25 obtains the positive or negative peak value of the user's knee joint angular velocity during the ground contact phase as the user's knee joint angular velocity according to the correlation. For example, as described above, the control unit 25 estimates the landing timing based on the first data or the second data. Once the landing timing is estimated, the control unit 25 obtains the first positive or negative peak value of the user's knee joint angular velocity from the landing timing based on the data detected by the sensor device 10. As can be seen from Figure 5, the first positive or negative peak value of the knee joint angular velocity from the landing timing is the positive or negative peak value of the knee joint angular velocity during the ground contact phase. The control unit 25 may obtain the user's knee joint angular velocity using the first data and the second data, as will be described later. Here, as shown in Figure 6, for users with a small load on the knee joint, the positive and negative peak values of the knee joint angular velocity may not appear during the ground contact phase. In this case, it is expected that the positive and negative peak values of the knee joint angular velocity cannot be obtained during the ground contact phase. Therefore, if the control unit 25 is to adopt the positive peak value of the knee joint angular velocity, and cannot obtain the positive peak value of the knee joint angular velocity within the first time T1b from the landing timing as shown in Figure 6, it may obtain the user's knee joint angular velocity at the third time T3 elapsed from the landing timing using first or second data. The first time T1b may be set based on the average value of the length of the ground contact phase, etc. The first time T1b may be the same as the first time T1a as shown in Figure 8, or it may be different from the first time T1a as shown in Figure 8. The third time T3 may be set based on the average value of the time from the landing timing until the positive peak value of the knee joint angular velocity appears, etc. Furthermore, if a negative peak value of the angular velocity of the knee joint is adopted, and the control unit 25 cannot obtain the negative peak value of the angular velocity of the knee joint within the first time T1b from the landing timing as shown in Figure 6, it may obtain the user's knee joint angular velocity at the fourth time T4 elapsed from the landing timing using the first or second data. The fourth time T4 may be set based on the average value of the time from the landing timing until a negative peak value appears in the angular velocity of the knee joint.

As another example, the control unit 25 may use the correlation between the angular velocity of the knee joint at the landing timing and the load applied to the knee joint. In this case, the control unit 25 obtains the user's knee joint angular velocity at the landing timing as the user's knee joint angular velocity according to the correlation. For example, as described above, the control unit 25 estimates the landing timing based on the first data or the second data. Once the landing timing is estimated, the control unit 25 obtains the user's knee joint angular velocity at the landing timing based on the data detected by the sensor device 10. The control unit 25 may obtain the user's knee joint angular velocity using the first data and the second data, as will be described later.

Here, the control unit 25 may estimate and obtain the angular velocity of the user's knee joint based on the first data and the second data. As shown in Figure 3, the knee joint is located between the thigh and the foot. Because the knee joint is located between the thigh and the foot, the angular velocity of the knee joint can be estimated using the first data, which represents the movement of the thigh, and the second data, which represents the movement of the foot.

When the control unit 25 acquires the angular velocity of the knee joint, it obtains an estimated value of the load applied to the user's knee joint based on the correlation and the acquired angular velocity of the user's knee joint. As an example, the control unit 25 may use a regression equation obtained from the distribution of the load applied to the knee joint with respect to the angular velocity of the knee joint as the correlation. In this case, the control unit 25 obtains the estimated value of the load applied to the knee joint by calculating the estimated value of the load applied to the knee joint using the acquired angular velocity of the user's knee joint and the regression equation. As another example, the control unit 25 may use a learning model that has learned the correlation between the angular velocity of the knee joint and the load applied to the knee joint as the correlation. The learning model may calculate and output a score indicating the estimated value of the load applied to the knee joint when information on the angular velocity of the knee joint is input. In this case, the control unit 25 inputs the information on the angular velocity of the user's knee joint that it has acquired into the learning model and obtains a score indicating the estimated value of the load applied to the knee joint calculated by the learning model.

[Other examples of processes for obtaining estimated values]
The reference angular velocity may be the angular velocity of the ankle during the ground contact phase. Below, we will explain another example of the estimation process, specifically the case where the reference angular velocity is the angular velocity of the ankle during the ground contact phase.

The control unit 25 estimates the timing of the user's foot landing and obtains the angular velocity of the user's ankle based on at least the third data. The control unit 25 obtains an estimated value of the load applied to the user's knee joint based on the correlation between the angular velocity of the ankle during the ground contact phase and the load applied to the knee joint, and the angular velocity of the user's ankle during the ground contact phase. The control unit 25 may obtain the angular velocity of the user's ankle according to the correlation.

As an example, the control unit 25 may use the correlation between the positive or negative peak value of the ankle angular velocity during the ground contact phase and the load applied to the knee joint. In this case, the control unit 25 obtains the positive or negative peak value of the user's ankle angular velocity during the ground contact phase as the user's ankle angular velocity according to the correlation. For example, as described above, the control unit 25 estimates the landing timing based on the first or second data. Once the landing timing is estimated, the control unit 25 obtains the first positive or negative peak value of the user's knee joint angular velocity from the landing timing based on the third data detected by the third sensor device 10C. As can be seen from Figure 10, the first positive or negative peak value of the ankle angular velocity from the landing timing is the positive or negative peak value of the ankle angular velocity during the ground contact phase. Here, as shown in Figure 11, for users with a small load applied to the knee joint, the positive and negative peak values of the ankle angular velocity may not appear during the ground contact phase. In this case, it is expected that the positive and negative peak values of the ankle angular velocity cannot be obtained during the ground contact phase. Therefore, if the control unit 25 adopts a negative peak value of the ankle angular velocity and cannot obtain a positive peak value of the knee joint angular velocity within the first time T1c from the landing timing as shown in Figure 11, it may obtain the user's ankle angular velocity at the fifth time T5 elapsed from the landing timing using third data. The first time T1c may be set based on the average value of the length of the ground contact phase, etc. The first time T1c may be the same as the first time T1a as shown in Figure 8, or it may be different from the first time T1a as shown in Figure 8. The fifth time T5 may be set based on the average value of the time from the landing timing until a negative peak value appears in the ankle angular velocity, etc. Furthermore, if the control unit 25 is adopting a positive peak value for the ankle angular velocity, and it is not possible to obtain a positive peak value for the ankle angular velocity within the first time T1c from the landing timing as shown in Figure 11, it may obtain the user's ankle angular velocity at the sixth time T6 elapsed from the landing timing using third data. The sixth time T6 may be set based on the average value of the time from the landing timing until a positive peak value appears in the ankle angular velocity.

As another example, the control unit 25 may use the correlation between the angular velocity of the ankle at the landing timing and the load applied to the knee joint. In this case, the control unit 25 obtains the user's ankle angular velocity at the landing timing as the user's ankle angular velocity according to the correlation. For example, as described above, the control unit 25 estimates the landing timing based on the first data or the second data. Once the landing timing is estimated, the control unit 25 obtains the user's ankle angular velocity at the landing timing based on the third data detected by the third sensor device 10C.

Here, the control unit 25 may estimate the landing timing based on the third data. Since the third data is data indicating the movement of the ankle, the landing timing, which is the timing when the foot touches the ground, can be estimated using the third data. By using the third data indicating the movement of the ankle, the landing timing can be estimated with high accuracy.

When the control unit 25 acquires the ankle angular velocity, it obtains an estimated value of the load applied to the user's knee joint based on the correlation and the acquired user's ankle angular velocity. As an example, the control unit 25 may use a regression equation obtained from the distribution of the load applied to the knee joint with respect to the ankle angular velocity as the correlation. In this case, the control unit 25 obtains the estimated value of the load applied to the knee joint by calculating the estimated value of the load applied to the knee joint using the acquired user's ankle angular velocity and the regression equation. As another example, the control unit 25 may use a learning model that has learned the correlation between the ankle angular velocity and the load applied to the knee joint as the correlation. The learning model may calculate and output a score indicating the estimated value of the load applied to the knee joint when ankle angular velocity information is input. In this case, the control unit 25 inputs the acquired user's ankle angular velocity information into the learning model and obtains a score indicating the estimated value of the load applied to the knee joint calculated by the learning model.

[Notification Processing]
The control unit 25 may have the output unit 23, which acts as a notification unit, provide information indicating an estimated value of the load applied to the user's knee joint. If the control unit 25 obtains the estimated value as a score output from the learning model, it may have the output unit 23, which acts as a notification unit, provide information indicating the score. As an example of notification, the control unit 25 may have the output unit 23 output information indicating an estimated value or score of the load applied to the knee joint. By outputting information indicating an estimated value or score of the load applied to the knee joint from the output unit 23, the user can understand whether or not the load applied to their knee joint is large.

As another example of notification, the control unit 25 may output information indicating an estimated value or score of the load applied to the user's knee joint as audio to the speaker of the output unit 23. Outputting information indicating an estimated value or score of the load applied to the knee joint as audio reduces the possibility of interfering with the user's walking.

The control unit 25 may transmit a signal indicating an estimated value or score of the load applied to the user's knee joint to an external device via the communication unit 21. For example, if the user is wearing earphones, the control unit 25 transmits a signal indicating an estimated value or score of the load applied to the knee joint to the earphones, which are external devices, via the communication unit 21. With this configuration, information indicating an estimated value or score of the load applied to the knee joint is output as audio from the earphones worn by the user. By outputting information indicating an estimated value or score of the load applied to the joint as audio from the earphones, the possibility of hindering the user's walking is reduced.

The control unit 25 may store an estimated value of the load applied to the user's knee joint in the storage unit 24 for a preset period, for example. The preset period may be set based on the frequency of the user's walking, etc. The control unit 25 may determine whether the stored estimated value exceeds a threshold. If the control unit 25 determines that the stored estimated value exceeds the threshold, it may have the output unit 23, which acts as a notification unit, send warning information. As an example of notification, the control unit 25 may output warning information to the output unit 23. The threshold may be set based on the amount of load that, when accumulated in the knee joint, could cause knee joint disease. By having the output unit 23, which acts as a notification unit, send warning information, the user can understand that the load accumulated in their knee joint is somewhat large.

If the control unit 25 determines that the accumulated estimated value exceeds a threshold, it may transmit a warning signal to an external device via the communication unit 21. For example, if the user is wearing earphones, the control unit 25 transmits a warning signal to the earphones, which are considered an external device, via the communication unit 21. With this configuration, the warning information is output as audio from the earphones worn by the user. By outputting the warning information as audio from the earphones, the possibility of hindering the user's walking is reduced.

(System operation)
Figure 13 is a flowchart showing the operation of the evaluation process performed by the electronic device 20 shown in Figure 1. This operation corresponds to an example of the information processing method according to this embodiment. When the control unit 25 receives an input from the input unit 22 instructing it to perform the evaluation process, for example, it starts the evaluation process from the process in step S10. Hereinafter, the reference angular velocity will be the angular velocity of the thigh during the ground contact phase. The control unit 25 will also obtain an estimated value of the load applied to the user's knee joint using a learning model that has learned the correlation between the angular velocity of the thigh during the ground contact phase and the load applied to the knee joint.

The control unit 25 receives an input from the input unit 22 instructing it to execute the evaluation process (step S10). This input is provided by the user wearing the sensor device 10 through the input unit 22.

The control unit 25 transmits a signal to the first sensor device 10A via the communication unit 21 to instruct it to start data detection (step S11). If the information processing system 1 includes the first sensor device 10A and the second sensor device 10B, the control unit 25 may transmit the signal to instruct it to start data detection as a broadcast signal to the first sensor device 10A and the second sensor device 10B via the communication unit 21. After the processing in step S11 is executed, the data detected by the sensor device 10 is transmitted from the sensor device 10 to the electronic device 20.

The control unit 25 receives data detected by the sensor device 10 via the communication unit 21 (step S12).

The control unit 25 estimates the user's landing timing based on the data received in step S12 (step S13). The control unit 25 obtains the angular velocity of the user's thigh during the ground contact period (step S14).

The control unit 25 inputs the angular velocity of the user's thigh, acquired in step S14, into the learning model to obtain a score indicating an estimated value of the load applied to the user's knee joint (step S15). In the process of step S15, the control unit 25 stores the estimated value indicated by the score in the storage unit 24.

The control unit 25 causes the output unit 23, which acts as a notification unit, to notify the output unit 23 of the information indicating the score obtained in the processing of step S15 (step S16).

The control unit 25 determines whether the accumulated estimated value exceeds a threshold (step S17). If the control unit 25 determines that the accumulated estimated value exceeds the threshold (step S17: YES), it proceeds to the process in step S18. On the other hand, if the control unit 25 does not determine that the accumulated estimated value exceeds the threshold (step S17: NO), it terminates the evaluation process.

In step S18, the control unit 25 causes the output unit 23, which acts as a notification unit, to send warning information. After executing step S18, the control unit 25 terminates the evaluation process.

The control unit 25 may execute the evaluation process again at any time interval after completing the evaluation process. This time interval may be set based on the walking speed of a typical user, etc. In the evaluation process executed again, the control unit 25 may start from the process of step S11. The control unit 25 may repeatedly execute the evaluation process until it receives an input from the input unit 22 indicating the end of the evaluation process. This input is, for example, provided by the user through the input unit 22. For example, the user provides this input through the input unit 22 when they have finished walking.

In this electronic device 20, which functions as an information processing device, the control unit 25 estimates the user's landing timing and obtains an estimated value of the load applied to the user's knee joint based on at least the first data. In other words, in this embodiment, if there is a sensor device 10 capable of detecting data for estimating the user's landing timing, etc., an estimated value of the load applied to the user's knee joint can be obtained even without a load sensor that detects, for example, ground reaction force. Therefore, according to this embodiment, a technology for easily evaluating the load applied to the user's joints can be provided.

Furthermore, the reference angular velocity may be the angular velocity of the thigh during the ground contact phase. In other words, the control unit 25 may obtain an estimated value of the load applied to the user's knee joint based on the correlation between the angular velocity of the thigh during the ground contact phase and the load applied to the knee joint, and the user's angular velocity of the thigh during the ground contact phase. In this case, the control unit 25 may estimate the landing timing based only on the first data detected by the first sensor device 10A. The control unit 25 may obtain the user's thigh angular velocity using only the first data detected by the first sensor device 10A. With this configuration, an estimated value of the load applied to the user's knee joint can be obtained using only the first data detected by the first sensor device 10A. In other words, the user only needs to wear one of the first sensor devices 10A. Therefore, user convenience is improved.

Furthermore, the reference angular velocity may be the angular velocity of the knee joint during the ground contact phase. In other words, the control unit 25 may obtain an estimated value of the load applied to the user's knee joint based on the correlation between the angular velocity of the knee joint during the ground contact phase and the load applied to the knee joint, and the user's angular velocity of the knee joint during the ground contact phase. As described above with reference to Figure 3, the load applied to the knee joint is calculated by the product of the knee joint reaction force and the knee joint angular velocity. There is a stronger correlation between the angular velocity of the knee joint and the load applied to the knee joint than, for example, between the angular velocity of the thigh and the load applied to the knee joint. Therefore, by using the correlation between the angular velocity of the knee joint during the ground contact phase and the load applied to the knee joint, it is possible to obtain an estimated value of the load applied to the user's knee joint with greater accuracy.

In recent years, walking has gained attention as an easy form of exercise. However, users are required to pay attention to obstacles in front of or near them while walking. Because users are required to pay attention to obstacles in front of or near them while walking, they may not be able to pay attention to their own posture. If users are unable to pay attention to their own posture while walking, they may walk with an incorrect posture without realizing it. If a user walks with an incorrect posture, the load on the user's knee joint may become excessive. If a user continues to walk with an excessive load on their knee joint, it may cause diseases such as osteoarthritis of the knee in the user's knee joint.

In the electronic device 20 according to this embodiment, the control unit 25 can output information indicating an estimated value or score of the load applied to the user's knee joint to the output unit 23, etc. With this configuration, the user can understand whether or not the load applied to their knee joint is excessive. Because the user can understand whether or not the load applied to their knee joint is excessive, the possibility of the user continuing to walk with an excessive load on their knee joint is reduced. By reducing the possibility of the user continuing to walk with an excessive load on their knee joint, the possibility of the user developing diseases such as osteoarthritis of the knee is reduced.

(Configuration of other systems)
Figure 14 is a functional block diagram showing the configuration of an information processing system 101 according to another embodiment of the present disclosure.

The information processing system 101 includes a sensor device 10, an electronic device 20, and a server 40. In the information processing system 101, the server 40 functions as an information processing device and evaluates the load applied to the user's knee joint.

The electronic device 20 and the server 40 can communicate with each other via the network 2. The network 2 may be any network, including mobile communication networks and the Internet.

The control unit 25 of the electronic device 20 receives data detected by the sensor device 10 from the sensor device 10 via the communication unit 21, in the same or similar manner as the information processing system 1. In the information processing system 101, the control unit 25 transmits the data detected by the sensor device 10 to the server 40 via the network 2 using the communication unit 21.

Server 40 is, for example, a server belonging to a cloud computing system or other computing system. Server 40 has a communication unit 41, a storage unit 42, and a control unit 43.

The communication unit 41 is configured to include at least one communication module that can connect to the network 2. The communication module is, for example, a communication module compatible with standards such as wired LAN (Local Area Network) or wireless LAN. The communication unit 41 is connected to the network 2 via the communication module through the wired LAN or wireless LAN.

The storage unit 42 is configured to include at least one semiconductor memory, at least one magnetic memory, at least one optical memory, or at least two combinations thereof. The semiconductor memory is, for example, RAM or ROM. The RAM is, for example, SRAM or DRAM. The ROM is, for example, EEPROM. The storage unit 42 may function as a main memory, auxiliary memory, or cache memory. The storage unit 42 stores data used for the operation of the server 40 and data obtained through the operation of the server 40. For example, the storage unit 42 stores system programs, application programs, and embedded software.

The control unit 43 is configured to include at least one processor, at least one dedicated circuit, or a combination thereof. The processor is a general-purpose processor such as a CPU or GPU, or a dedicated processor specialized for a specific process. The dedicated circuit is, for example, an FPGA or ASIC. The control unit 43 controls each part of the server 40 and executes processes related to the operation of the server 40.

The control unit 43 receives data detected by the sensor device 10 from the electronic device 20 via the network 2 using the communication unit 41. The control unit 43 acquires the data detected by the sensor device 10 by receiving the data detected by the sensor device 10 via the electronic device 20. The control unit 43 acquires an estimated value of the load applied to the user's knee joint by performing the same or similar processing as the processing performed by the control unit 25 of the electronic device 20 described above. For example, the control unit 43 estimates the user's landing timing based on at least the first data and acquires an estimated value of the load applied to the user's knee joint.

The control unit 43 transmits a signal indicating an estimated value of the load applied to the user's knee joint to the electronic device 20 via the network 2 using the communication unit 41. If the control unit 43 obtains the estimated value as a score output from the learning model, it may transmit a signal indicating the score to the electronic device 20 via the network 2 using the communication unit 41. In the electronic device 20, the control unit 25 receives a signal indicating the estimated value or a signal indicating the score from the server 40 via the network 2 using the communication unit 21. The control unit 25 causes the output unit 23, which acts as a notification unit, to notify the information indicating the estimated value or the information indicating the score. As an example of notification, the control unit 25 causes the output unit 23 to output the information indicating the estimated value or the information indicating the score.

The control unit 43 may store an estimated value of the load applied to the user's knee joint in, for example, the storage unit 42 for the set period. If the control unit 43 determines that the stored estimated value exceeds the threshold, it may send a warning signal to the electronic device 20 via the network 2 using the communication unit 41. In the electronic device 20, the control unit 25 receives the warning signal from the server 40 via the network 2 using the communication unit 21. The control unit 25 causes the output unit 23, which acts as a notification unit, to notify the warning information. As an example of notification, the control unit 25 causes the output unit 23 to output the warning information.

(Operation of other systems)
Figures 15 and 16 are sequence diagrams showing the operation of the evaluation process performed by the information processing system 101 shown in Figure 14. This operation corresponds to an example of the information processing method according to this embodiment. When the electronic device 20 receives an input instructing the execution of a gait evaluation, the information processing system 101 starts the evaluation process from step S20 as shown in Figure 15. Hereinafter, the reference angular velocity will be the angular velocity of the thigh during the ground contact phase. The control unit 43 will acquire an estimated value of the load applied to the user's knee joint using a learning model that has learned the correlation between the angular velocity of the thigh during the ground contact phase and the load applied to the knee joint.

In the electronic device 20, the control unit 25 receives an input instructing the execution of the evaluation process via the input unit 22 (step S20). The control unit 25 transmits a signal instructing the start of data detection to the sensor device 10 via the communication unit 21 (step S21). If the information processing system 101 includes a first sensor device 10A and a second sensor device 10B, the control unit 25 may transmit the signal instructing the start of data detection as a broadcast signal to the first sensor device 10A and the second sensor device 10B via the communication unit 21.

In the sensor device 10, the control unit 14 receives a signal from the electronic device 20 via the communication unit 11 to instruct the start of data detection (step S22). Upon receiving this signal, the control unit 14 starts data detection. The control unit 14 acquires the data detected by the sensor unit 12 from the sensor unit 12 and transmits the acquired data to the electronic device 20 via the communication unit 11 (step S23).

In the electronic device 20, the control unit 25 receives data from the sensor device 10 via the communication unit 21 (step S24). The control unit 25 transmits the data detected by the sensor device 10 to the server 40 via the network 2 using the communication unit 21 (step S25).

In the server 40, the control unit 43 receives data detected by the sensor device 10 from the electronic device 20 via the network 2 using the communication unit 41 (step S26). Based on the data received in step S26, the control unit 43 estimates the user's landing timing (step S27). Based on the data received in step S26, the control unit 43 obtains the angular velocity of the user's thigh during the ground contact period (step S28). By inputting the angular velocity of the user's thigh obtained in step S28 into a learning model, the control unit 43 obtains a score indicating an estimated value of the load applied to the user's knee joint (step S29). In step S29, the control unit 43 stores the estimated value indicated by the score in the storage unit 42. The control unit 43 transmits a signal indicating the score to the electronic device 20 via the network 2 using the communication unit 41 (step S30).

After executing the process in step S30, the information processing system 101 proceeds to the process in step S31, as shown in Figure 16.

In the electronic device 20, the control unit 25 receives a signal indicating the score from the server 40 via the network 2 using the communication unit 21 (step S31). The control unit 25 then broadcasts the score information to the output unit 23, which acts as a notification unit (step S32).

In the server 40, the control unit 43 determines whether the accumulated estimated value exceeds a threshold (step S33). If the control unit 43 determines that the accumulated estimated value exceeds the threshold (step S33: YES), it transmits a warning signal to the electronic device 20 via the network 2 using the communication unit 41 (step S34). After the execution of step S34, the information processing system 101 proceeds to step S35. On the other hand, if the control unit 43 does not determine that the accumulated estimated value exceeds the threshold (step S33: NO), the information processing system 101 terminates the evaluation process.

In step S35, the control unit 25 of the electronic device 20 receives a warning signal from the server 40 via the network 2 using the communication unit 21 (step S35). The control unit 25 then broadcasts the warning information to the output unit 23, which acts as a notification unit (step S36). After executing the process in step S36, the information processing system 101 terminates the evaluation process.

The information processing system 101 may execute the evaluation process again at any time interval as described above after completing the evaluation process. In the evaluation process executed again, the information processing system 101 may start from the process in step S23. The information processing system 101 may repeatedly execute the evaluation process until it receives an input from the input unit 22 indicating that the electronic device 20 has finished the evaluation process.

Information processing system 101 can achieve the same or similar effects as information processing system 1.

While embodiments relating to this disclosure have been described based on the drawings and examples, it should be noted that those skilled in the art can make various modifications or alterations based on this disclosure. Therefore, it should be noted that these modifications or alterations are within the scope of this disclosure. For example, the functions included in each component can be rearranged in a logically consistent manner, and multiple components can be combined into one or separated.

For example, the communication unit 11 of the sensor device 10 may further include at least one communication module that can be connected to a network 2 as shown in Figure 14. The communication module is, for example, a communication module compatible with a mobile communication standard such as LTE, 4G, or 5G. In this case, in the information processing system 101 as shown in Figure 14, the control unit 15 of the sensor device 10 may transmit the data detected by the sensor device 10 to the server 40 via the network 2 using the communication unit 11.

For example, it is also possible to use a general-purpose computer as the electronic device 20 according to this embodiment. Specifically, a program describing the processing content that realizes each function of the electronic device 20 according to this embodiment is stored in the memory of the general-purpose computer, and the processor reads and executes the program. Therefore, the configuration according to this embodiment can also be realized as a program that can be executed by a processor or as a non-temporary computer-readable medium that stores said program.

In this disclosure, the designations "First," "Second," etc., are identifiers used to distinguish the configurations. Configurations distinguished by the designations "First," "Second," etc., in this disclosure may have their numbers swapped. For example, the first sensor device may have its identifiers "First" and "Second" swapped with those of the second sensor device. The identifier swapping occurs simultaneously. Even after the identifier swapping, the configurations remain distinguishable. Identifiers may be deleted. Configurations from which identifiers have been deleted are distinguished by codes. The designations "First," "Second," etc., in this disclosure should not be used solely as a basis for interpreting the order of the configurations or for determining the existence of smaller numbered identifiers.

1,101 Information Processing System 2 Network 10 Sensor Equipment 10A First Sensor Equipment 10B Second Sensor Equipment 10C Third Sensor Equipment 11 Communication Unit 12 Sensor Unit 13 Memory Unit 14 Control Unit 20 Electronic Equipment 21 Communication Unit 22 Input Unit 23 Output Unit 24 Memory Unit 25 Control Unit 30 Foot 31 Foot Section 32 Shin Section 33 Knee Joint 34 Thigh Section 40 Server 41 Communication Unit 42 Memory Unit 43 Control Unit

Claims (14)

First data regarding the movement of the user's thigh is acquired from the first sensor device.
The system includes a control unit that estimates the timing of the user's foot landing based on at least the first data, and obtains an estimated value of the load applied to the user's knee joint ,
The control unit,
Based on at least the first data, the user's reference angular velocity is obtained, and the reference angular velocity is the angular velocity of the thigh or the angular velocity of the knee joint during the ground contact phase when at least a portion of the foot is in contact with the ground.
The estimated value is obtained based on the correlation between the reference angular velocity and the load applied to the knee joint and the user's reference angular velocity .
An information processing device that uses a learning model that has learned the aforementioned correlation . The information processing apparatus according to claim 1 , wherein the control unit estimates the user's landing timing based solely on the first data. The control unit,
Second data regarding the movement of the user's foot is acquired from the second sensor device.
The information processing device according to claim 1 , which estimates the user's landing timing based on the second data. The aforementioned reference angular velocity is the angular velocity of the thigh during the ground contact period.
The aforementioned correlation is the correlation between the angular velocity of the thigh during the ground contact phase and the load applied to the knee joint.
The control unit,
The information processing device according to claim 2 , which obtains the angular velocity of the user's thigh during the ground contact period using only the first data. The aforementioned reference angular velocity is the angular velocity of the knee joint during the ground contact phase.
The aforementioned correlation is the correlation between the angular velocity of the knee joint during the ground contact phase and the load applied to the knee joint.
The control unit,
The information processing device according to claim 2, which estimates and obtains the angular velocity of the user's knee joint during the ground contact period based on the first data and the second data indicating the movement of the user's foot detected by the second sensor device. Third data regarding the user's ankle movement is acquired from the third sensor device.
Based on at least the third data, the user's reference angular velocity is obtained, and the reference angular velocity is the angular velocity of the ankle during the ground contact phase when at least a portion of the foot is in contact with the ground.
The system includes a control unit that acquires an estimated value of the load applied to the user's knee joint, calculated based on the correlation between the reference angular velocity and the load applied to the knee joint and the user's reference angular velocity .
The control unit is an information processing device that uses a learning model that has learned the correlation as the correlation . Furthermore, with the addition of a news department,
The information processing apparatus according to any one of claims 1 to 6 , wherein the control unit causes the notification unit to report information indicating the estimated value. Furthermore, with the addition of a news department,
The information processing apparatus according to any one of claims 1 to 6 , wherein the control unit causes the notification unit to notify information indicating a warning when the accumulated estimated value exceeds a threshold. With an additional communications unit,
The information processing apparatus according to any one of claims 1 to 6 , wherein the control unit transmits a signal indicating the estimated value to an external device via the communication unit. With an additional communications unit,
The information processing apparatus according to any one of claims 1 to 6 , wherein the control unit transmits a warning signal to an external device via the communication unit when the accumulated estimated value exceeds a threshold. An electronic device comprising a notification unit that notifies information of the estimated value acquired by the information processing device according to any one of claims 1 to 6 . First COM device and
The system includes an information processing device that acquires first data relating to the movement of the user's thigh from the first sensor device,
The aforementioned information processing device is
Based at least the first data, the timing of the user's foot landing is estimated, and an estimated value of the load applied to the user's knee joint is obtained .
Based on at least the first data, the user's reference angular velocity is obtained, and the reference angular velocity is the angular velocity of the thigh or the angular velocity of the knee joint during the ground contact phase when at least a portion of the foot is in contact with the ground.
The estimated value is obtained based on the correlation between the reference angular velocity and the load applied to the knee joint and the user's reference angular velocity .
An information processing system that uses a learning model that has learned the aforementioned correlation . To acquire first data regarding the movement of the user's thigh from the first sensor device,
Based at least the first data, the timing of the user's foot landing is estimated, and an estimated value of the load applied to the user's knee joint is obtained.
The method involves obtaining the user's reference angular velocity based on at least the first data, wherein the reference angular velocity is the angular velocity of the thigh or the angular velocity of the knee joint during the ground contact phase when at least a portion of the foot is in contact with the ground.
Obtaining the estimated value calculated based on the correlation between the reference angular velocity and the load applied to the knee joint and the user's reference angular velocity,
An information processing method comprising using a learning model that has learned the correlation as the correlation . On the computer,
To acquire first data regarding the movement of the user's thigh from the first sensor device,
Based at least the first data, the timing of the user's foot landing is estimated, and an estimated value of the load applied to the user's knee joint is obtained.
The method involves obtaining the user's reference angular velocity based on at least the first data, wherein the reference angular velocity is the angular velocity of the thigh or the angular velocity of the knee joint during the ground contact phase when at least a portion of the foot is in contact with the ground.
Obtaining the estimated value calculated based on the correlation between the reference angular velocity and the load applied to the knee joint and the user's reference angular velocity,
The aforementioned correlation is defined as a program that uses a learning model that has learned the aforementioned correlation .