Knee trajectory information generation device, knee trajectory information generation method, and program

Abstract

To provide a knee track information generation device or the like capable of generating information related to a knee track including a behavior of a knee in a lateral direction.SOLUTION: A knee track information generation device comprises: an acquisition section for acquiring walking data including time series data of foot positions and knee positions of an object person; a first calculation section for calculating a first movement route obtained by connecting a start point and an end point of a walking period with the use of the time series data of the foot positions included in the walking data; a second calculation section for calculating a second movement route corresponding to a track of the knee position between the start point and the end point of the walking period with the use of the time series data of the knee positions included in the walking data; an information generation section for calculating a difference between the first movement route and the second movement route so as to generate knee track information including visual information corresponding to the calculated difference; and an output section for outputting the generated knee track information.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present disclosure relates to a knee trajectory information generation device that generates information related to knee trajectories during walking and the like.

Background Art

[0002] With the increasing interest in healthcare, attention has been focused on information corresponding to features (also referred to as gait) included in walking patterns. If information corresponding to gait can be utilized, healthcare services corresponding to various symptoms that people have can be provided. Information indicating the movement of the knees during walking is useful for diagnosing diseases such as osteoarthritis of the knee. In particular, if the behavior of the knees in the left - right direction can be grasped, there is a possibility of realizing early detection and prevention of osteoarthritis of the knee.

[0003] Patent Document 1 discloses a walking analysis system that calculates walking parameters used for evaluating the walking motion of a subject. The system of Patent Document 1 measures acceleration and angular velocity using a three - axis acceleration sensor and a three - axis angular velocity sensor attached to the lower limb portion of the subject. The system of Patent Document 1 calculates the posture of the lower limb portion during walking based on the measured acceleration and angular velocity. The system of Patent Document 1 connects the lower limb portions in the calculated posture to each other to construct a three - dimensional model including the movement trajectories of joints. The system of Patent Document 1 calculates, as a walking parameter, the angle formed by the acceleration vector of the joint at the time of heel strike with respect to the movement trajectory in the sagittal plane.

[0004] Patent Document 2 discloses an operation information display device that displays the periodic operation of a living organism. The device of Patent Document 2 acquires the operation information of the target living organism from a moving image of the target living organism. The device of Patent Document 2 corrects the influence of the translational movement of a specific part based on the operation information criteria. The device of Patent Document 2 stores the position information of the corrected specific part over a plurality of frames of the moving image. The device of Patent Document 2 superimposes the trajectory of the specific part on the moving image and displays the moving image with the trajectory superimposed.

Prior Art Documents

Patent Documents

[0005] [Patent Document 1] Japanese Patent Publication No. 2017-023436 [Patent Document 2] Japanese Patent Publication No. 2021-176347 [Overview of the project] [Problems that the invention aims to solve]

[0006] The method described in Patent Document 1 uses a 3-axis acceleration sensor and a 3-axis angular velocity sensor attached to the lower limb to calculate the angle (corresponding to the knee angle) that the joint acceleration vector makes with respect to the motion trajectory at heel strike as a gait parameter. However, the method described in Patent Document 1 could not generate information that could capture the movement of the knee in the lateral direction.

[0007] According to the method described in Patent Document 2, the trajectory of the ankle joint as viewed from a lateral perspective can be displayed in two dimensions based on a video of the target organism. However, the method described in Patent Document 2 could not display information that would allow one to understand the movement of the knee as viewed from a frontal perspective.

[0008] The purpose of this disclosure is to provide a knee trajectory information generation device, etc., that can generate information about the knee trajectory, including the movement of the knee in the left-right direction. [Means for solving the problem]

[0009] A knee trajectory information generating device according to one aspect of the present disclosure includes: an acquisition unit that acquires walking data including time-series data of the subject's foot position and knee position; a first calculation unit that calculates a first movement path connecting the start and end points of a walking cycle using the time-series data of the foot position included in the walking data; a second calculation unit that calculates a second movement path corresponding to the trajectory of the knee position between the start and end points of a walking cycle using the time-series data of the knee position included in the walking data; an information generating unit that calculates the difference between the first movement path and the second movement path and generates knee trajectory information including visual information corresponding to the calculated difference; and an output unit that outputs the generated knee trajectory information.

[0010] In one embodiment of the knee trajectory information generation method of this disclosure, walking data including time-series data of the subject's foot position and knee position is acquired, a first movement path connecting the start and end points of the walking cycle is calculated using the time-series data of the foot position included in the walking data, a second movement path corresponding to the trajectory of the knee position between the start and end points of the walking cycle is calculated using the time-series data of the knee position included in the walking data, the difference between the first movement path and the second movement path is calculated, knee trajectory information including visual information corresponding to the calculated difference is generated, and the generated knee trajectory information is output.

[0011] A program according to one aspect of this disclosure causes a computer to perform the following steps: acquire gait data including time-series data of the subject's foot position and knee position; calculate a first movement path connecting the start and end points of a gait cycle using the time-series data of the foot position included in the gait data; calculate a second movement path corresponding to the trajectory of the knee position between the start and end points of a gait cycle using the time-series data of the knee position included in the gait data; calculate the difference between the first movement path and the second movement path; generate knee trajectory information including visual information corresponding to the calculated difference; and output the generated knee trajectory information. [Effects of the Invention]

[0012] This disclosure makes it possible to provide a knee trajectory information generation device, etc., that can generate information about the knee trajectory, including the movement of the knee in the left-right direction. [Brief explanation of the drawing]

[0013] [Figure 1] This is a block diagram showing an example of the configuration of a knee trajectory information generation device according to the first embodiment. [Figure 2] This is a conceptual diagram illustrating an example of a walking event in the first embodiment. [Figure 3] This is a conceptual diagram illustrating an example of a human body surface in the first embodiment. [Figure 4]A graph showing an example of time-series data of the difference between the first movement path and the second movement path calculated by the knee trajectory information generation device according to the first embodiment. [Figure 5] A graph showing another example of time-series data of the difference between the first movement path and the second movement path calculated by the knee trajectory information generation device according to the first embodiment. [Figure 6] A conceptual diagram for explaining the first example of the visual information generated by the knee trajectory information generation device according to the first embodiment. [Figure 7] A conceptual diagram for explaining the second example of the visual information generated by the knee trajectory information generation device according to the first embodiment. [Figure 8] A conceptual diagram for explaining the third example of the visual information generated by the knee trajectory information generation device according to the first embodiment. [Figure 9] A conceptual diagram for explaining the fourth example of the visual information generated by the knee trajectory information generation device according to the first embodiment. [Figure 10] A conceptual diagram for explaining the fifth example of the visual information generated by the knee trajectory information generation device according to the first embodiment. [Figure 11] A conceptual diagram for explaining the fifth example of the visual information generated by the knee trajectory information generation device according to the first embodiment. [Figure 12] A conceptual diagram for explaining the sixth example of the visual information generated by the knee trajectory information generation device according to the first embodiment. [Figure 13] A flowchart for explaining an example of the operation of the knee trajectory information generation device according to the first embodiment. [Figure 14] A conceptual diagram for explaining Application Example 1-1 related to the first embodiment. [Figure 15] A conceptual diagram for explaining Application Example 1-1 related to the first embodiment. [Figure 16] A conceptual diagram for explaining Application Example 1-2 related to the first embodiment. [Figure 17] A conceptual diagram for explaining Application Example 1-2 related to the first embodiment. [Figure 18] It is a conceptual diagram for explaining Application Examples 1-3 related to the first embodiment. [Figure 19] It is a conceptual diagram for explaining Application Examples 1-3 related to the first embodiment. [Figure 20] It is a conceptual diagram for explaining Application Examples 1-3 related to the first embodiment. [Figure 21] It is a block diagram showing an example of the configuration of a knee trajectory information generation device according to the second embodiment. [Figure 22] It is a block diagram showing an example of the hardware configuration for executing the processing according to each embodiment.

Embodiments for Carrying Out the Invention

[0014] Hereinafter, embodiments for carrying out the present invention will be described with reference to the drawings. However, although the embodiments described below have technically preferable limitations for carrying out the present invention, they do not limit the scope of the invention below. In all the drawings used in the following description of the embodiments, the same reference numerals are given to the same parts unless there is a particular reason. Also, in the following embodiments, repeated explanations of the same configurations and operations may be omitted.

[0015] (First Embodiment) First, the configuration of the knee trajectory information generation device according to the first embodiment will be described while referring to the drawings. The knee trajectory information generation device according to the present embodiment acquires walking data measured according to the walking of the subject. The walking data includes foot position data and knee position data. The knee trajectory information generation device according to the present embodiment uses the walking data to generate information regarding a knee trajectory (also referred to as knee trajectory information) indicating the movement of the knee.

[0016] In this embodiment, the center position of the knee is referred to as the knee position. The knee position may be offset from the center position of the knee, as long as it does not affect the verification of the knee trajectory. Also in this embodiment, the center position of the foot is referred to as the foot position. The foot position may be offset from the center position of the foot, as long as it does not affect the verification of the knee trajectory.

[0017] (composition) Figure 1 is a block diagram showing the configuration of the knee trajectory information generation device 10 according to this embodiment. The knee trajectory information generation device 10 comprises an acquisition unit 11, a first calculation unit 12, a second calculation unit 13, an information generation unit 15, and an output unit 17.

[0018] The acquisition unit 11 acquires the subject's walking data. The walking data includes the subject's foot position data and knee position data. The foot position data is the time change of the three-dimensional foot position. The knee position data is the time change of the three-dimensional knee position. There are no particular limitations on the measurement method for the foot position data and knee position data.

[0019] For example, foot position data and knee position data are measured using motion capture. In motion capture, markers are placed on various parts of the subject's body. For example, markers are placed on parts including the feet and knees. The subject is photographed with a camera while walking, and the foot position and knee position are measured according to the position of the markers in the captured image (video). Because motion capture allows for the direct measurement of foot and knee positions, highly accurate foot and knee position data can be obtained.

[0020] For example, foot position data and knee position data are measured by analyzing images (videos) captured by a camera. Using software such as OpenPose, foot position data and knee position data can be measured by calculating the foot position and knee position based on the positions of the skeleton and joints detected from the person in the image.

[0021] For example, foot position data and knee position data are measured using acceleration and angular velocity measured by an inertial sensor attached to the knee. When using an inertial sensor, foot position and knee position can be calculated by integrating the acceleration and angular velocity. For example, foot position data and knee position data may also be measured using smart apparel equipped with inertial sensors on various parts of the body.

[0022] For example, foot position data is measured according to the foot position measured using an inertial sensor installed in the footwear. In that case, knee position data is estimated according to the measured foot position.

[0023] The acquisition unit 11 acquires walking data in a predetermined walking section. For example, the predetermined walking section is a single walking cycle. The predetermined walking section may consist of multiple walking cycles. In the following, the period from when the heel of the right foot lands until the heel of the right foot lands again is defined as one walking cycle of the right foot. Similarly, the period from when the heel of the left foot lands until the heel of the left foot lands again is defined as one walking cycle of the left foot. The event of the heel landing is called heel strike. The start and end points of a walking cycle may be set to the timing of events other than heel strike.

[0024] Figure 2 is a conceptual diagram illustrating gait events detected in a single gait cycle based on the right foot. The horizontal axis of Figure 2 represents the gait cycle normalized with one gait cycle of the right foot set as 100 percent (%). The point when the right heel touches the ground is defined as the starting point (0%), and the point when the right heel touches the ground again is defined as the ending point (100%). Each of the multiple timings included in one gait cycle is called a gait phase. One gait cycle of one foot is broadly divided into the stance phase, in which at least a portion of the sole of the foot is in contact with the ground, and the swing phase, in which the sole of the foot is off the ground. In the example in Figure 2, the gait cycle is normalized so that the stance phase accounts for 60% and the swing phase accounts for 40%. The stance phase is subdivided into early stance T1, mid-stance T2, late stance T3, and early swing T4. The swing phase is subdivided into early swing T5, mid-swing T6, and late swing T7. The gait waveform for one gait cycle does not necessarily have to start from the moment the heel touches the ground. For example, the starting point of the gait waveform for one gait cycle may be set to the middle of the stance phase.

[0025] Walking event E1 represents heel contact (HC), the beginning of a single step cycle. Heel contact occurs when the heel of the right foot, which was off the ground during the swing phase, lands on the ground. Walking event E2 represents opposite toe off (OTO). Opposite toe off occurs when the toes of the left foot leave the ground while the sole of the right foot remains in contact with the ground. Walking event E3 represents heel rise (HR). Heel rise occurs when the heel of the right foot lifts off the ground while the sole of the right foot remains in contact with the ground. Walking event E4 represents opposite heel strike (OHS). Opposite heel strike occurs when the heel of the left foot, which was off the ground during the swing phase of the left foot, lands on the ground. Walking event E5 represents toe-off (TO). Toe-off is the event where the toes of the right foot leave the ground while the sole of the left foot remains in contact with the ground. Walking event E6 represents foot-adjacent (FA). Foot-adjacent is the event where the left and right feet cross while the sole of the left foot remains in contact with the ground. Walking event E7 represents tibia vertical (TV). Tibia vertical is the event where the tibia of the right foot becomes nearly perpendicular to the ground while the sole of the left foot remains in contact with the ground. Walking event E8 represents heel strike (HS), the end of one walking cycle. Walking event E8 corresponds to the end of the walking cycle that began with walking event E1, and also to the beginning of the next walking cycle.

[0026] Figure 3 is a conceptual diagram illustrating the planes (also called body planes) set for the human body. In this embodiment, the sagittal plane divides the body into left and right halves, the coronal plane divides the body into front and back halves, and the horizontal plane divides the body horizontally. In this embodiment, rotation in the sagittal plane with the x-axis as the axis of rotation is defined as roll, rotation in the coronal plane with the y-axis as the axis of rotation is defined as pitch, and rotation in the horizontal plane with the z-axis as the axis of rotation is defined as yaw. Furthermore, the angle of rotation in the sagittal plane with the x-axis as the axis of rotation is defined as the roll angle, the angle of rotation in the coronal plane with the y-axis as the axis of rotation is defined as the pitch angle, and the angle of rotation in the horizontal plane with the z-axis as the axis of rotation is defined as the yaw angle. In this embodiment, with respect to the coronal plane, the right side is defined as positive for the right foot, and the left side is defined as positive for the left foot.

[0027] The first calculation unit 12 acquires foot position data for a predetermined walking cycle. The foot position data includes the foot position at the start and end points of each walking cycle. In this embodiment, the points of consecutive heel strikes are set as the start and end points for each walking cycle. For example, the foot position data includes the foot position in a single walking cycle with heel strike as the start and end point. For example, the foot position data includes, for a predetermined walking cycle, the foot position in the horizontal plane at the start point (heel strike) and the foot position in the horizontal plane at the end point (heel strike).

[0028] The first calculation unit 12 calculates a walking path (also called the first movement path) connecting the start point and the end point included in the foot position data. In this embodiment, the first movement path is defined as a straight line connecting the foot position in the horizontal plane at the start point (heel strike) and the foot position in the horizontal plane at the end point (heel strike).

[0029] The second calculation unit 13 acquires knee position data for a predetermined gait cycle. The knee position data includes the knee position at the start and end points of each gait cycle. For example, the knee position data includes the knee position in a single gait cycle with heel strike as the start / end point. For a predetermined gait cycle, the knee position data includes the knee position in the horizontal plane at the start point (heel strike) and the knee position in the horizontal plane at the end point (heel strike).

[0030] The second calculation unit 13 calculates the knee movement path (also called the second movement path) connecting the start point and the end point included in the knee position data. In this embodiment, the second movement path is defined as the curve connecting the knee position in the horizontal plane at the start point (heel strike) and the knee position in the horizontal plane at the end point (heel strike). The second movement path corresponds to the knee trajectory.

[0031] The information generation unit 15 acquires the first and second movement paths in a predetermined walking cycle. The information generation unit 15 calculates the difference between the first and second movement paths for each predetermined walking cycle. In this embodiment, the information generation unit 15 calculates the difference between the first and second movement paths in the horizontal plane. The information generation unit 15 calculates the difference between the first and second movement paths in the horizontal plane, associating it with the walking phases included in a predetermined walking section. For the right foot, the right side of the difference between the first and second movement paths is positive. For the left foot, the left side of the difference between the first and second movement paths is positive. For example, the information generation unit 15 calculates the difference between the first and second movement paths in the horizontal plane for one walking cycle. For example, the information generation unit 15 associates the calculated difference with the position (direction of travel position) in the sagittal plane for one walking cycle. For example, the direction of travel position for one walking cycle is converted to a walking cycle and associated with the difference.

[0032] Figure 4 is a graph that maps the difference between the first and second movement paths in the horizontal plane for one step cycle to the position in the direction of travel for one step cycle. Figure 4 shows the difference for the right foot. When the difference is positive, the knee position is shifted to the right from the first movement path. In other words, when the difference is positive, the knee position is shifted outward from the center of the body. Conversely, when the difference is negative, the knee position is shifted to the left from the first movement path. In other words, when the difference is negative, the knee is shifted inward from the center of the body. The larger the absolute value of the difference, the greater the amount of shift of the knee position from the center of the body.

[0033] Figure 5 is a graph that maps the difference between the first and second movement paths in the horizontal plane for one walking cycle to the walking cycle. Figure 5 is a graph in which the horizontal axis (position in the direction of movement) of the graph in Figure 4 has been normalized to the walking cycle. As shown in Figure 5, by converting the horizontal axis of the time-series data of the difference to the walking cycle, it is possible to compare the variation in knee trajectory over multiple walking cycles for each walking phase.

[0034] The knee trajectory information generation device 10 generates knee trajectory information corresponding to the difference between the first movement path and the second movement path. The knee trajectory information includes visual information that represents the knee trajectory corresponding to the subject's walking. For example, visual information regarding knee trajectory is an arrow indicating the direction and magnitude of the difference between the first and second movement paths. For example, visual information regarding knee trajectory is a graph overlaying time-series data of the difference between the first and second movement paths over multiple gait cycles. For example, visual information regarding knee trajectory is a marker (also called the first marker) indicating knee height. For example, visual information regarding knee trajectory is an arrow (also called the second marker) representing the direction and magnitude of the difference between the first and second movement paths. For example, visual information regarding knee trajectory is a marker that combines the first and second markers. For example, the marker is displayed in accordance with the video of the walking subject (character). Knee trajectory information is not particularly limited as long as it includes visual information regarding knee trajectory.

[0035] Figure 6 is the first example of visual information related to the knee trajectory. Figure 6 is an example of displaying arrows on screen 100 that correspond to the direction of travel position and represent the direction and magnitude of the difference between the first movement path and the second movement path. The direction of the arrow indicates the direction of the difference. The length of the arrow indicates the magnitude of the difference. The length of the arrow is set according to the magnitude of the difference. For example, the arrow is set to a length that matches the magnitude of the difference. For example, the arrow is set to a length that is a multiple of the magnitude of the difference. It is also possible to display only the arrows that represent the direction and magnitude of the difference without displaying the time-series data of the difference between the first movement path and the second movement path. According to the visual information in Figure 6, the change in the knee trajectory can be intuitively grasped by the direction and length of the arrows that correspond to the direction of travel position.

[0036] Figure 7 is a second example of visual information related to knee trajectory. Figure 7 shows an example of displaying arrows on screen 100 that represent the direction and magnitude of the difference between the first and second movement paths, corresponding to the gait cycle. Figure 7 is a graph obtained by converting the horizontal axis of the graph in Figure 6 to the gait cycle. Alternatively, only arrows representing the direction and magnitude of the difference can be displayed without displaying the time-series data of the difference between the first and second movement paths. According to the visual information in Figure 7, the changes in the knee trajectory according to the gait phase can be intuitively grasped by the direction and magnitude of the arrows corresponding to the gait cycle.

[0037] Figure 8 shows a third example of visual information related to knee trajectory. In the example in Figure 8, arrows representing the direction and magnitude of the difference between the first and second movement paths are displayed on screen 100, corresponding to the gait cycle. The graph in Figure 8 is the same as the graph in Figure 7. In addition, in the example in Figure 8, a character representing the walking state corresponding to a walking event is displayed on screen 100, corresponding to the gait cycle. The character may be a conceptual representation of a person walking, or it may be an image of a person walking. Alternatively, the time-series data of the difference between the first and second movement paths may not be displayed, and only arrows representing the direction and magnitude of the difference may be shown. According to the visual information in Figure 8, the changes in the knee trajectory corresponding to a walking event can be intuitively grasped by the direction and magnitude of the arrows corresponding to the gait cycle and the character representing the walking state corresponding to the walking event.

[0038] Figure 9 is a fourth example of visual information regarding knee trajectory. Figure 9 shows an example of displaying time-series data of the difference between the first and second movement paths over multiple gait cycles on screen 100. According to the visual information in Figure 9, the variation in knee trajectory can be intuitively grasped by comparing the time-series data of the difference over multiple gait cycles. For example, statistical values ​​such as the arithmetic mean, geometric mean, variance, and standard deviation of the knee trajectory (knee position) over multiple gait cycles can be derived. By using the average values ​​such as the arithmetic mean and geometric mean of the knee trajectory (knee position) over multiple gait cycles, the movement of the knee over multiple gait cycles can be grasped on average. Furthermore, by using the variance and standard deviation of the knee trajectory (knee position) over multiple gait cycles, the variation in knee movement over multiple gait cycles can be grasped.

[0039] Figures 10 and 11 are conceptual diagrams illustrating the fifth example of visual information related to knee trajectory. Figure 10 is a conceptual diagram of a walking person (character) viewed from the front. In Figure 10, the person (character) has the left foot as the supporting leg and the right foot is off the ground. Figure 10 shows the knee position K in the coronal plane, the knee height H in the coronal plane, the first movement path W, the difference d between the first movement path W and the second movement path (knee position K), and the position K0 of the knee height H directly above the first movement path W.

[0040] Figure 11 is a conceptual diagram showing an example of displaying visual information related to knee trajectories on screen 100 in conjunction with video representing a person (character) walking. Figure 11 shows the consecutive heel contact positions (start point H1, end point H2) and the first movement path W connecting the start point H1 and the end point H2 for each of the left and right feet. In Figure 11, a pin P with its head at knee height H (position K0 in Figure 10) directly above the first movement path W is placed on the first movement path W. The pin P is placed on the first movement path W corresponding to the walking phase for each of the left and right feet. The position where the pin P is placed may be offset from the first movement path W. Also, the first movement path W on which the pin P is placed may be offset from the straight line connecting the start point H1 and the end point H2. In the example in Figure 11, the straight line representing the first movement path W includes an arrowhead indicating the direction of travel. The straight line representing the first movement path W does not have to include an arrowhead indicating the direction of travel.

[0041] In the example in Figure 11, starting from the head of pin P, arrow A is displayed to show the direction and magnitude of the difference between the first movement path W and the second movement path (knee position K in Figure 10). Similar to the arrows in Figures 7 and 8, the direction of arrow A indicates the direction of the difference between the first and second movement paths. The length of arrow A indicates the magnitude of the difference. For example, arrow A may be set to a length that matches the magnitude of the difference. For example, arrow A may be set to a length that is a multiple of the magnitude of the difference. The direction and length of arrow A are changed in conjunction with the walking phase of the person (character). For example, the video may only show the lower half of the person (character), not the whole body. According to the visual information in Figure 11, the changes in the knee trajectory corresponding to walking can be intuitively grasped in accordance with the movement of pin P and arrow A, which change in accordance with the video of the person (character).

[0042] Figure 12 is a conceptual diagram showing a sixth example of displaying visual information related to the knee trajectory on screen 100 in conjunction with video representing a person (character) walking. Figure 12 shows the consecutive heel contact positions (start point H1, end point H2) and the first movement path W connecting the start point H1 and the end point H2 for each of the left and right feet. In Figure 12, the knee trajectory T is displayed in conjunction with the movement of the knee. The knee trajectory T corresponds to the time-series data of the difference between the first movement path and the second movement path in Figures 7 and 8. In the example of Figure 12, the knee trajectory T is displayed corresponding to the knee position. The position where the knee trajectory is displayed may be offset from the knee position. For example, the knee position in the knee trajectory T can be changed in conjunction with the walking phase of the person (character). According to the visual information in Figure 12, the changes in the knee trajectory corresponding to walking can be intuitively grasped according to the knee trajectory T displayed in conjunction with the video of the person (character).

[0043] The output unit 17 outputs the knee trajectory information generated by the information generation unit 15. For example, the output unit 17 outputs the knee trajectory information to a terminal device having a screen. The knee trajectory information output to the terminal device is displayed on the screen of the terminal device. For example, the output unit 17 displays the knee trajectory information on the screen of the subject's (user's) mobile terminal. For example, the output unit 17 displays the knee trajectory information on the screen of a terminal device used by professionals such as doctors, physical therapists, and care workers who examine the subject's physical condition. The professionals can then provide the subject with a diagnosis or advice based on the knee trajectory information displayed on the terminal device screen. For example, the output unit 17 may also output the knee trajectory information to an external system that uses the knee trajectory information. There are no particular limitations on how the knee trajectory information output from the output unit 17 can be used.

[0044] For example, the knee trajectory information generation device 10 connects to an external system built on a cloud or server via a mobile terminal (not shown) carried by the subject (user). The mobile terminal is a portable communication device. For example, the mobile terminal is a portable communication device with communication functions such as a smartphone, smartwatch, or mobile phone.

[0045] For example, the knee trajectory information generation device 10 is connected to a terminal device (not shown) used by a person verifying the physical condition of the subject (user). The terminal device is equipped with software that processes knee trajectory information and displays images corresponding to the knee trajectory information. For example, the terminal device is an information processing device such as a stationary personal computer, a notebook personal computer, a tablet, or a mobile terminal. The terminal device may also be a dedicated terminal for processing knee trajectory information.

[0046] For example, the knee trajectory information generator 10 is connected to a mobile terminal or terminal device via a wired connection such as a cable. For example, the knee trajectory information generator 10 is connected to a mobile terminal or terminal device via wireless communication. For example, the knee trajectory information generator 10 is connected to a mobile terminal or terminal device via a wireless communication function (not shown) conforming to standards such as Bluetooth® or WiFi®. The communication function of the knee trajectory information generator 10 may conform to standards other than Bluetooth® or WiFi®. The knee trajectory information may be used by an application installed on the mobile terminal or terminal device. In that case, the mobile terminal or terminal device performs processing using the knee trajectory information by application software installed on the device. The knee trajectory information generator 10 may also be implemented in the mobile terminal or terminal device.

[0047] (operation) Next, an example of the operation of the knee trajectory information generation device 10 will be explained with reference to the drawings. Figure 13 is a flowchart for explaining an example of the operation of the knee trajectory information generation device 10. In the explanation following the flowchart in Figure 13, the knee trajectory information generation device 10 will be the main operator.

[0048] In Figure 13, first, the knee trajectory information generator 10 acquires walking data for a predetermined walking cycle (step S11). The walking data includes time-series data of foot position (foot position data) and time-series data of knee position (knee position data). For example, the knee trajectory information generator 10 acquires walking data for one walking cycle. The knee trajectory information generator 10 may acquire walking data over multiple walking cycles.

[0049] Next, the knee trajectory information generator 10 detects heel strike from the foot position data included in the walking data (step S12). The knee trajectory information generator 10 detects heel strikes corresponding to the start / end points of the foot position data for one walking cycle. If there are multiple walking cycles, the knee trajectory information generator 10 detects heel strikes corresponding to the start / end points of the foot position data for each walking cycle.

[0050] Next, the knee trajectory information generation device 10 calculates a first movement path connecting the foot positions during consecutive heel strikes (step S13). The first movement path is a straight line that serves as the reference for the knee trajectory.

[0051] Next, the knee trajectory information generator 10 extracts knee position data from the gait data, with consecutive heel strikes as the starting and ending points (step S14). If the data spans multiple gait cycles, the knee trajectory information generator 10 extracts knee position data for each gait cycle from the gait data, with consecutive heel strikes as the starting and ending points.

[0052] Next, the knee trajectory information generation device 10 calculates a second movement path using the extracted waist position data (step S15). The second movement path is a curve corresponding to the knee trajectory. If it spans multiple walking cycles, the knee trajectory information generation device 10 calculates a second movement path for each walking cycle.

[0053] Next, the knee trajectory information generation device 10 calculates the difference between the second movement path and the first movement path (step S16). The difference between the second movement path and the first movement path is a curve corresponding to the knee trajectory based on the first movement path. If it spans multiple gait cycles, the knee trajectory information generation device 10 calculates the difference for each gait cycle.

[0054] Next, the knee trajectory information generation device 10 generates knee trajectory information corresponding to the calculated difference (step S17). The knee trajectory information includes visual information related to the knee trajectory. For example, the knee trajectory information generation device 10 generates visual information corresponding to any of the first to sixth examples (Figures 6 to 12) described above.

[0055] Next, the knee trajectory information generation device 10 outputs the generated knee trajectory information (step S18). The knee trajectory information generation device 10 outputs knee trajectory information that includes visual information related to the knee trajectory. The visual information included in the output knee trajectory information is displayed on the screen of a terminal device (not shown) or the like used by the user who is using the knee trajectory information.

[0056] (Examples of application) Next, an example of application of the knee trajectory information generation device 10 will be explained with reference to the drawings. In the example, an example will be given in which knee trajectory information relating to the fifth example in Figures 10 to 11 is displayed on the screen of a terminal device. In the following example, an example will be given in which knee trajectory information (also called display information), including visual information, is superimposed on a video of a walking subject viewed from diagonally above. The video of the subject may be an actual video, or it may be a virtual person (character) that mimics the movements of the subject. In the following example, an example will be given in which a character is displayed in the video. The display information shown below may be generated by the knee trajectory information generation device 10, or it may be generated by another device or system that has acquired the knee trajectory information.

[0057] [Application Example 1-1] Figures 14 and 15 are conceptual diagrams relating to Application Example 1-1 of the knee trajectory information generation device 10. Figures 14 and 15 represent the first display pattern D1. In the first display pattern D1, knee trajectory information with a pin P placed directly above the first movement path W is displayed on the screen 100.

[0058] A display switching area 110, including buttons to switch display patterns, is displayed in the upper right corner of screen 100. Figures 14 and 15 show the state when the first display pattern D1 is selected. The second display pattern D2 and the third display pattern D3 will be described later.

[0059] A viewpoint switching area 111, which includes buttons for switching viewpoints, is displayed in the upper left corner of screen 100. The viewpoint switching area 111 displays buttons for switching viewpoints between a frontal viewpoint (first viewpoint V1) and a viewpoint diagonally to the left and in front (second viewpoint V2), with the person (character) at the center. The viewpoints correspond to the viewpoint of the user viewing screen 100. The display switching area 110 and the viewpoint switching area 111 are interface areas that accept user input.

[0060] Figure 14 shows an example where the image of a person (character) is displayed on screen 100, centered on the person (character) and viewed from a frontal viewpoint (first viewpoint V1). In Figure 14, the first display pattern D1 is selected in the display switching area 110. Also, the first viewpoint V1 is selected in the viewpoint switching area 111. From the first viewpoint V1, it is easy to grasp the trajectory of the knee within the coronal plane. That is, from the first viewpoint V1, it is easy to grasp the movement of the knee in the left-right direction (within the coronal plane).

[0061] Figure 15 shows an example of displaying an image of a character on screen 100, centered on the character and viewed from a viewpoint slightly to the left and slightly in front (second viewpoint V2). In Figure 15, the viewpoint has switched from the first viewpoint V1 (Figure 14) to the second viewpoint V2 in the viewpoint switching region 111, according to the selection of the second viewpoint V2. When viewed from a viewpoint slightly in front of the character's direction of movement, such as the second viewpoint V2, it is easier to grasp the knee trajectory in three dimensions.

[0062] [Application Example 1-2] Figures 16 and 17 are conceptual diagrams relating to application example 1-2 of the knee trajectory information generation device 10. Figures 16 and 17 represent the second display pattern D2. In the second display pattern, knee trajectory information, with pins P placed at positions away from the first movement path W within the coronal plane, is displayed on the screen 100. For example, pins P are displayed at a position that is a multiple of the distance between the body's center of gravity and the knee position, away from the knee position.

[0063] A display switching area 110, including a button to switch the display pattern, is displayed in the upper right corner of screen 100. Figure 16 shows the state after the display pattern has been switched from the first display pattern D1 (Figure 15) to the second display pattern D2, according to the selection of the second display pattern D2. In the second display pattern D2, a pin P is placed in the coronal plane at a position away from the first movement path W.

[0064] A viewpoint switching area 112, including a button to switch viewpoints, is displayed in the upper left corner of screen 100. For example, the viewpoint switching area 111 may be set to switch to the viewpoint switching area 112 in response to a switch in the display pattern from the first display pattern D1 to the second display pattern D2. Alternatively, the viewpoint switching area 112 may be set in the first display pattern D1, or the viewpoint switching area 111 may be set in the second display pattern D2.

[0065] The viewpoint switching area 112 displays nine buttons for selecting viewpoints. The upper section of the viewpoint switching area 112 displays buttons for selecting viewpoint BR (right rear), viewpoint B (rear), and viewpoint BL (left rear), centered on the character. The middle section of the viewpoint switching area 112 displays buttons for selecting viewpoint R (right), viewpoint U (up), and viewpoint L (left), centered on the character. The lower section of the viewpoint switching area 112 displays buttons for selecting viewpoint FR (right front), viewpoint F (front), and viewpoint FL (left front), centered on the character. Figures 16 and 17 are examples and do not limit the viewpoints that can be selected in the viewpoint switching area 112. The display switching area 110 and the viewpoint switching area 112 are interface areas that accept user input.

[0066] Figure 16 shows an example of displaying an image of a person (character) on screen 100, centered on the character and viewed from a frontal viewpoint (viewpoint F). Figure 16 shows the state where the display pattern has switched from the first display pattern D1 (Figure 15) to the second display pattern D2, according to the selection of the second display pattern D2 in the display switching area 110. In Figure 16, the second display pattern D2 is selected in the display switching area 110. Also, viewpoint F is selected in the viewpoint switching area 112. Viewpoint F is the same viewpoint as the first viewpoint V1 (Figure 14). From viewpoint F, it is easier to grasp the movement of the knee in the left-right direction (within the coronal plane).

[0067] Figure 17 shows an example of displaying an image of a character, centered on the character, from a viewpoint (viewpoint FL) slightly to the left and in front of the character, on screen 100. Figure 17 shows the state after the viewpoint has switched from viewpoint F (Figure 16) to viewpoint FL, depending on the selection of viewpoint FL in the viewpoint switching region 112. Viewpoint FL is the same viewpoint as the second viewpoint V2 (Figure 15). From viewpoint FL, it is easier to grasp the three-dimensional knee trajectory.

[0068] In this application example, knee trajectory information, with pins P placed at a position away from the first movement path W within the coronal plane, is displayed on screen 100. In this application example, since pins P and arrows A do not overlap with the person (character), it is easy to understand the knee trajectory in accordance with changes in pins P and arrows A.

[0069] [Application Examples 1-3] Figures 18-19 are conceptual diagrams relating to application examples 1-3 of the knee trajectory information generation device 10. Figures 18-19 represent the third display pattern D3. In the third display pattern D3, knee trajectory information with a first movement path W set at a position away from the person (character) is displayed on the screen 100. In addition, in the third display pattern D3, knee trajectory information is displayed with a pin P placed directly above the first movement path W. For example, the first movement path W is displayed at a position that is a multiple of the distance between the body's center of gravity and the knee position, away from the knee position.

[0070] A display switching area 110, including a button to switch display patterns, is displayed in the upper right corner of screen 100. Figure 18 shows the state after the display pattern has been switched from the second display pattern D2 (Figure 17) to the third display pattern D3, according to the selection of the third display pattern D3. In the third display pattern D3, the first movement path W is displayed at a position away from the person (character). Also, in the third display pattern D3, a pin P is placed directly above the first movement path W.

[0071] A viewpoint switching area 113, which includes a user interface for switching viewpoints, is displayed in the upper left corner of screen 100. For example, the viewpoint switching area 112 may be set to switch to the viewpoint switching area 113 in response to a switch in the display pattern from the second display pattern D2 to the third display pattern D3. Alternatively, the viewpoint switching area 113 may be set in the first display pattern D1 or the second display pattern D2.

[0072] The viewpoint switching area 113 displays a circular user interface (hereinafter referred to as the circle) for switching viewpoints. The circle displays a slider (hatching) for selecting a viewpoint. The slider moves along the circumference of the circle. By aligning the slider with the desired viewpoint position, the viewpoint is selected. The viewpoint selected through the user interface is a viewpoint centered on the person (character). In the example shown in Figures 18-19, the slider position corresponds to the viewpoint in the horizontal plane. In the circle, the bottom corresponds to the front viewpoint F, the right to the left viewpoint L, the top to the back viewpoint B, and the left to the right viewpoint R. By moving the slider along the circumference of the circle, the 360-degree viewpoint in the horizontal plane is switched. The display switching area 110 and the viewpoint switching area 113 are interface areas that accept user operations. Figures 18-19 are examples and do not limit the viewpoints that can be selected in the viewpoint switching area 113.

[0073] Figure 18 shows an example of displaying an image of a person (character) on screen 100, centered on the person (character) and viewed from a frontal viewpoint F. Figure 18 shows the state where the display pattern has switched from the second display pattern D2 (Figure 17) to the third display pattern D3, according to the selection of the third display pattern D3 in the display switching area 110. In Figure 18, the third display pattern D3 is selected in the display switching area 110. Also, viewpoint F is selected in the viewpoint switching area 113. Viewpoint F is the same viewpoint as the first viewpoint V1 (Figure 14). From viewpoint F, it is easy to grasp the movement of the knees in the left-right direction (within the coronal plane).

[0074] Figure 19 is an example of displaying an image of a character on screen 100, centered on the character, from a viewpoint diagonally to the left and slightly forward, between the front viewpoint F and the left viewpoint L. Figure 19 shows the state where the viewpoint has switched from the front and above viewpoint F (Figure 18) to the viewpoint diagonally to the left and slightly forward, centered on the character, in response to the operation of the circle slider in the viewpoint switching area 113. The viewpoint diagonally to the left and slightly forward, centered on the character, is the same viewpoint as the second viewpoint V2 (Figure 15). When viewed from the viewpoint diagonally to the left and slightly forward relative to the direction of movement of the character, it is easier to grasp the three-dimensional knee trajectory.

[0075] Figure 20 is a conceptual diagram showing an example of displaying the first movement path W, pin P, and arrow A in accordance with a video in application examples 1-3. Figure 20 shows a view from a diagonal front-right perspective, centered on a person (character). Figure 20 shows three frames extracted from multiple frames included in the video related to the person's (character's) walking. The actual video consists of many more frames. The three frames in Figure 20 progress from the top left to the bottom right as time (walking cycle) progresses. As time (walking cycle) progresses, the video showing the person's (character's) walking state changes. The first movement path W, pin P, and arrow A change in accordance with the walking phase of the person's (character's) walking.

[0076] In this example, the first movement path W is displayed at a distance from the person (character). Also, in this example, a pin P is placed directly above the first movement path W. In this example, the first movement path W, pin P, and arrow A do not overlap with the person (character). Therefore, it is easy to understand the change in the knee trajectory relative to the first movement path in accordance with the movement of pin P and arrow A, which move directly above the first movement path.

[0077] As described above, the knee trajectory information generation device of this embodiment comprises an acquisition unit, a first calculation unit, a second calculation unit, an information generation unit, and an output unit. The acquisition unit acquires walking data including time-series data of the subject's foot position and knee position. The first calculation unit uses the time-series data of foot position included in the walking data to calculate a first movement path connecting the start and end points of the walking cycle. The second calculation unit uses the time-series data of knee position included in the walking data to calculate a second movement path corresponding to the trajectory of the knee position between the start and end points of the walking cycle. The information generation unit calculates the difference between the first movement path and the second movement path. The information generation unit generates knee trajectory information including visual information corresponding to the calculated difference. The output unit outputs the generated knee trajectory information.

[0078] In this embodiment, knee trajectory information is generated, which includes visual information representing the knee trajectory of the subject. The visual information representing the subject's knee trajectory includes the lateral movement of the knee. In other words, according to this embodiment, it is possible to generate information about the knee trajectory that includes the lateral movement of the knee.

[0079] In one embodiment of this system, the acquisition unit acquires walking data of a subject, with consecutive heel strikes as the start and end points of the walking cycle. The first calculation unit calculates a first movement path connecting the start and end points of the walking cycle in a horizontal plane. The second calculation unit calculates a second movement path corresponding to the trajectory of the knee position between the start and end points of the walking cycle in a horizontal plane. The information generation unit calculates the difference in the horizontal plane, corresponding to the walking phases included in the walking cycle. The information generation unit generates knee trajectory information, including visual information to which the difference is associated with the walking phases. According to this embodiment, it is possible to generate information about the knee trajectory, including the behavior of the knee in the left-right direction, with respect to a walking cycle with consecutive heel strikes as the start and end points.

[0080] In one embodiment of this design, the information generation unit generates visual information in which arrows indicating the direction and magnitude of the difference are associated with the walking phases included in the walking cycle. According to this design, the behavior of the knee can be intuitively understood according to the direction and length of the arrows associated with the walking phases.

[0081] In one embodiment of this design, the information generation unit generates visual information by overlaying a marker, which is a combination of a first marker indicating the height of the knee position and a second marker indicating the direction and magnitude of the difference, onto a frame that constitutes a video showing the walking state of the subject. According to this design, the behavior of the knee can be intuitively grasped in accordance with the changing marker that is linked to the subject's walking.

[0082] In one embodiment of this model, the information generation unit generates visual information in which a marker is superimposed on the knee position of the subject displayed in the frame. According to this model, the behavior of the knee can be intuitively understood in accordance with the marker displayed on the knee position of the subject.

[0083] In one embodiment of this model, the information generation unit generates visual information in which a sign is displayed at a position away from the subject shown in the frame. According to this model, the movement of the knees can be intuitively understood in accordance with the sign displayed at a position away from the subject.

[0084] In one embodiment of this system, the information generation unit generates visual information that combines a straight line and a sign indicating a first movement path. According to this embodiment, it becomes easier to intuitively grasp the movement of the knees in accordance with the walking phase of the subject.

[0085] In one embodiment of this system, the output unit outputs knee trajectory information relating to the subject to a terminal device. The output unit displays display information relating to the knee trajectory information on the screen of the terminal device. According to this embodiment, the behavior of the knee can be intuitively understood by visually observing the display information shown on the screen of the terminal device.

[0086] Osteoarthritis of the knee is a condition in which inflammation and other symptoms occur in the knee joint due to the degeneration and deterioration of the cartilage in the knee joint. Early detection and prevention of osteoarthritis of the knee are important. Diagnosis of osteoarthritis of the knee is mainly based on the subjective judgment of the physician. Therefore, there is a need to provide information that supports the physician's diagnosis. In particular, the movement of the knee during the initial stance phase is an important diagnostic indicator for osteoarthritis of the knee. From the perspective of early detection and prevention, it is desirable to detect early signs of knee-related diseases such as osteoarthritis of the knee. According to the method of this embodiment, the movement of the knee in the left-right direction can be clearly observed by visual information representing the knee trajectory of the subject. Therefore, according to the method of this embodiment, mild lateral thrust can be easily detected according to the visual information displayed in the image. The method of this embodiment can be applied to any knee-related symptoms other than osteoarthritis of the knee. The method of this embodiment can be applied to various fields such as the diagnosis and rehabilitation of leg-related symptoms, frailty prevention, and assessment of fall risk.

[0087] (Second embodiment) Next, a knee trajectory information generation device according to the second embodiment will be described with reference to the drawings. The knee trajectory information generation device of this embodiment has a simplified configuration compared to the first knee trajectory information generation device.

[0088] Figure 21 is a block diagram showing an example of the configuration of the knee trajectory information generation device 20 according to this embodiment. The knee trajectory information generation device 20 comprises an acquisition unit 21, a first calculation unit 22, a second calculation unit 23, an information generation unit 25, and an output unit 27.

[0089] The acquisition unit 21 acquires gait data, including time-series data of the subject's foot and knee positions. The first calculation unit 22 uses the time-series foot position data included in the gait data to calculate a first movement path connecting the start and end points of the gait cycle. The second calculation unit 23 uses the time-series knee position data included in the gait data to calculate a second movement path, which corresponds to the trajectory of the knee position between the start and end points of the gait cycle. The information generation unit 25 calculates the difference between the first movement path and the second movement path. The information generation unit 25 generates knee trajectory information, including visual information corresponding to the calculated difference. The output unit 27 outputs the generated knee trajectory information.

[0090] In this embodiment, knee trajectory information is generated, which includes visual information representing the knee trajectory of the subject. The visual information representing the subject's knee trajectory includes the lateral movement of the knee. In other words, according to this embodiment, it is possible to generate information about the knee trajectory that includes the lateral movement of the knee.

[0091] (Hardware) Here, the hardware configuration for executing the processing according to each embodiment of this disclosure will be explained using the information processing device 90 (computer) in Figure 22 as an example. Note that the information processing device 90 in Figure 22 is an example configuration for executing the processing of each embodiment and does not limit the scope of this disclosure.

[0092] As shown in Figure 22, the information processing device 90 comprises a processor 91, main memory 92, auxiliary storage 93, input / output interface 95, and communication interface 96. In Figure 22, interface is abbreviated as I / F (Interface). The processor 91, main memory 92, auxiliary storage 93, input / output interface 95, and communication interface 96 are connected to each other via a bus 98, enabling data communication. Furthermore, the processor 91, main memory 92, auxiliary storage 93, and input / output interface 95 are connected to a network such as the Internet or an intranet via the communication interface 96.

[0093] The processor 91 loads programs (instructions) stored in the auxiliary storage device 93, etc., into the main memory 92. For example, the program is a software program for executing the processing of each embodiment. The processor 91 executes the program loaded into the main memory 92. By executing the program, the processor 91 executes the processing of each embodiment.

[0094] The main memory 92 has an area where the program is loaded. The processor 91 loads the program stored in the auxiliary memory 93, etc., into the main memory 92. The main memory 92 is implemented by volatile memory such as DRAM (Dynamic Random Access Memory). Alternatively, non-volatile memory such as MRAM (Magneto Resistive Random Access Memory) may be configured / added as the main memory 92.

[0095] The auxiliary storage device 93 stores various data, such as programs. The auxiliary storage device 93 is implemented by a local disk such as a hard disk or flash memory. It is also possible to omit the auxiliary storage device 93 by configuring the system to store various data in the main memory 92.

[0096] The input / output interface 95 is an interface for connecting the information processing device 90 to peripheral devices, based on standards and specifications. The communication interface 96 is an interface for connecting to external systems and devices via a network such as the Internet or an intranet, based on standards and specifications. The input / output interface 95 and the communication interface 96 may be shared as interfaces for connecting to external devices.

[0097] The information processing device 90 may be connected to input devices such as a keyboard, mouse, or touch panel, as needed. These input devices are used to input information and settings. When a touch panel is used as an input device, the screen with touch panel functionality serves as the interface. The processor 91 and the input devices are connected via an input / output interface 95.

[0098] The information processing device 90 may be equipped with a display device for displaying information. If a display device is provided, the information processing device 90 is equipped with a display control device (not shown) for controlling the display of the display device. The information processing device 90 and the display device are connected via an input / output interface 95.

[0099] The information processing device 90 may be equipped with a drive device. The drive device mediates between the processor 91 and the recording medium (program recording medium) by reading data and programs stored on the recording medium and writing the processing results of the information processing device 90 to the recording medium. The information processing device 90 and the drive device are connected via an input / output interface 95.

[0100] The above is an example of a hardware configuration for enabling the processing according to each embodiment of the present invention. The hardware configuration in Figure 22 is an example of a hardware configuration for executing the processing according to each embodiment and does not limit the scope of the present invention. A program that causes a computer to execute the processing according to each embodiment is also included in the scope of the present invention.

[0101] A program recording medium that stores the program according to each embodiment is also included in the scope of the present invention. The recording medium can be implemented as an optical recording medium such as a CD (Compact Disc) or DVD (Digital Versatile Disc). The recording medium may also be implemented as a semiconductor recording medium such as a USB (Universal Serial Bus) memory or an SD (Secure Digital) card. Furthermore, the recording medium may be implemented as a magnetic recording medium such as a flexible disk, or other recording media. When a program executed by a processor is recorded on a recording medium, that recording medium corresponds to a program recording medium.

[0102] The components of each embodiment may be combined in any way. The components of each embodiment may be implemented by software. The components of each embodiment may be implemented by circuitry.

[0103] Although the present invention has been described above with reference to embodiments, the present invention is not limited to the above embodiments. Various modifications to the configuration and details of the present invention can be made that will be understood by those skilled in the art within the scope of the present invention. [Explanation of Symbols]

[0104] 10, 20 Knee trajectory information generation device 11, 21 Acquisition Department 12, 22 1st calculation section 13, 23 2nd calculation section 15, 25 Information generation section 17, 27 Output section

Claims

1. A means for acquiring gait data, including time-series data of the subject's foot position and knee position, A first calculation means calculates a first movement path connecting the start and end points of a walking cycle using the time-series data of foot position included in the walking data, A second calculation means calculates a second movement path corresponding to the trajectory of the knee position between the start and end points of the walking cycle, using the time-series data of the knee position included in the walking data. Information generation means that calculates the difference between the first movement path and the second movement path and generates knee trajectory information including visual information corresponding to the calculated difference, The system includes an output means for outputting the generated knee trajectory information, The acquisition means is, The gait data of the subject is acquired, with consecutive heel strikes as the start and end points of the gait cycle. The first calculation means is, The first movement path connecting the start and end points of the walking cycle in the horizontal plane is calculated. The second calculation means is, The second movement path corresponding to the trajectory of the knee position between the start and end points of the walking cycle in the horizontal plane is calculated. The information generation means is The difference in the horizontal plane is calculated in correspondence with the walking phases included in the walking cycle. A knee trajectory information generating device that generates knee trajectory information including the visual information, in which the difference is associated with the walking phase, and a sign combining a first sign indicating the height of the knee position and a second sign indicating the direction and magnitude of the difference is superimposed on a frame constituting a video showing the walking state of the subject.

2. The information generation means is The knee trajectory information generating device according to claim 1, wherein an arrow indicating the direction and magnitude of the difference generates the visual information associated with the walking phase included in the walking cycle.

3. The information generation means is The knee trajectory information generating device according to claim 1, which generates visual information in which the marker is superimposed on the knee position of the subject displayed in the frame.

4. The information generation means is The knee trajectory information generating device according to claim 1, which generates visual information in which the sign is displayed at a position away from the subject displayed in the frame.

5. The information generation means is The knee trajectory information generating device according to claim 1, which generates the visual information obtained by combining the straight line indicating the first movement path and the sign.

6. The output means is The knee trajectory information relating to the subject is output to the terminal device. A knee trajectory information generating device according to any one of claims 1 to 5, wherein display information relating to the knee trajectory information is displayed on the screen of the terminal device.

7. Computers We acquire gait data including time-series data of the subject's foot and knee positions. Using the time-series data of foot position included in the walking data, a first movement path connecting the start and end points of the walking cycle is calculated. Using the time-series data of knee position included in the walking data, a second movement path corresponding to the trajectory of the knee position between the start and end points of the walking cycle is calculated. The difference between the first travel path and the second travel path is calculated, Knee trajectory information including visual information corresponding to the calculated difference is generated. Output the generated knee trajectory information, In acquiring the aforementioned walking data, The gait data of the subject is acquired, with consecutive heel strikes as the start and end points of the gait cycle. In calculating the first travel path, The first movement path connecting the start and end points of the walking cycle in the horizontal plane is calculated. In calculating the second travel path, The second movement path corresponding to the trajectory of the knee position between the start and end points of the walking cycle in the horizontal plane is calculated. In the calculation of the difference, The difference in the horizontal plane is calculated in correspondence with the walking phases included in the walking cycle. In generating the knee trajectory information, A method for generating knee trajectory information, which generates knee trajectory information including the visual information, in which the difference is associated with the walking phase, and a sign combining a first sign indicating the height of the knee position and a second sign indicating the direction and magnitude of the difference is superimposed on a frame constituting a video showing the walking state of the subject.

8. A process to acquire gait data including time-series data of the subject's foot position and knee position, A process to calculate a first movement path connecting the start and end points of a walking cycle using the time-series data of foot position included in the walking data, A process to calculate a second movement path corresponding to the trajectory of the knee position between the start and end points of the walking cycle, using the time-series data of the knee position included in the walking data, A process for calculating the difference between the first movement path and the second movement path, A process to generate knee trajectory information including visual information corresponding to the calculated difference, A process to output the generated knee trajectory information, In the process of acquiring the aforementioned walking data, A process for acquiring the gait data of the subject, with consecutive heel strikes as the start and end points of the gait cycle, In the process of calculating the first movement path, A process for calculating the first movement path connecting the start and end points of the walking cycle in a horizontal plane, In the process of calculating the second movement path, A process for calculating the second movement path which corresponds to the trajectory of the knee position between the start and end points of the walking cycle in the horizontal plane, In the process of calculating the difference, A process to calculate the difference in the horizontal plane in correspondence with the walking phases included in the walking cycle, In the process of generating the knee trajectory information, A program that causes a computer to perform the following steps: associate the difference with the walking phase, generate knee trajectory information including the visual information, which is superimposed on a frame constituting a video showing the walking state of the subject, a marker that combines a first marker indicating the height of the knee position and a second marker indicating the direction and magnitude of the difference.

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