JP6369811B2 - Gait analysis system and gait analysis program - Google Patents

Description

  The present invention relates to a gait analysis system and a gait analysis program used to analyze a walking motion of a measurement subject.

  Conventionally, a system for analyzing a walking motion of a measurement subject has been developed. In the conventional analysis of walking motion, as disclosed in the following Patent Documents 1 and 2, the motion at the center of the waist, which is the motion near the center of gravity of the body, is observed in order to comprehensively determine the walking motion. To be done.

JP 2011-177278 A JP 2006-177749 A

  According to the techniques disclosed in Patent Documents 1 and 2, the result of analysis of walking motion is displayed on the display unit as a numerical value such as acceleration. Therefore, even if abnormalities in walking motion are pointed out based on numerical values such as acceleration displayed on the display unit, the person to be measured cannot intuitively understand how his / her walking motion is abnormal .

  The present invention has been made in view of the above problems, and an object thereof is to provide a gait analysis system and a gait analysis program capable of intuitively grasping how abnormal walking motion is. It is.

The walking analysis system according to the first aspect of the present invention includes a sensor unit that acquires physical information that can specify a locus of a change in a predetermined position caused by a walking motion of a measurement subject, and the physical that is acquired by the sensor unit. A control unit that determines the presence or absence of a walking abnormality in the walking movement based on information, and a display unit that displays a determination result image capable of recognizing the presence or absence of the walking abnormality determined by the control unit. The control unit obtains time-series data of a position change locus in the walking motion of the measurement subject based on the physical information, and a Lissajous in a predetermined plane based on the time-series data of the position change locus A data creation unit for creating curve data, and predetermined values and values of a plurality of types of elements to be extracted extracted from the Lissajous curve data created by the data creation unit; Each of the plurality of types of determination criteria for presence / absence of abnormality is compared, and for each of the plurality of predetermined body parts, it is determined whether or not the body part is performing an abnormal motion. Based on which timing of the Lissajous curve data the timing at which the body part is determined to be abnormal by the abnormal part determination unit and the abnormal part determination unit is determined in advance. An abnormal phase determination unit that determines in which of the plurality of phases the body part is performing an abnormal movement; and the body part that is determined to be performing an abnormal movement by the abnormal part determination unit; Causing the display unit to display the determination result image associated with the phase determined to be abnormally exercised by the abnormal phase determination unit. A display control unit, wherein the determination result image is a plurality of still images displayed on the display unit, each of which corresponds to the plurality of phases of the walking motion of the measurement subject. In the humanoid image corresponding to the phase that is determined to be abnormally moved by the abnormal phase determination unit of the type image and the plurality of humanoid images, the abnormal part determination unit performs abnormal movement including a pointed image to point out the body part is determined to be.

The walking analysis system according to the second aspect of the present invention includes a sensor unit that acquires physical information that can specify a locus of a change in a predetermined position caused by a walking motion of the measurement subject, and the physical that is acquired by the sensor unit. A control unit that determines the presence or absence of a gait abnormality in the walking movement based on the information; a display unit that displays a determination result image that can recognize the presence or absence of the gait abnormality determined by the control unit; A video capturing unit that captures the walking motion of the measurer, and the control unit acquires time-series data of a locus of a change in position in the walking motion of the measured person based on the physical information, and the position A data creation unit that creates Lissajous curve data in a predetermined plane based on time-series data of a change trajectory, and the Lissajous curve data created by the data creation unit Are compared with a plurality of types of determination criterion values for presence / absence of abnormality, respectively, and thereby a plurality of types of predetermined elements in the walking motion of the measurement subject are compared. An abnormality type determination unit that determines whether or not each of the gait abnormalities is present, and a value of the determined element and the abnormality for each type of the gait abnormality determined by the abnormality type determination unit as having the gait abnormality Based on the difference from the presence / absence determination reference value, an abnormality degree determination unit that determines the degree of the gait abnormality, and the type of the gait abnormality determined by the abnormality type determination unit and the abnormality degree determination unit and a display control unit for displaying the determination result image and the associated degree of the gait abnormalities on the display unit, the determination result image is a moving image shot at the moving image photographing part Recognizing the person image that is al extracted, the plurality kinds plural kinds gait abnormal to be able to recognize each character image, the degree of the abnormal gait specified by each of the plurality of types of character images Graphic images that can be included.

  The walking analysis system according to the third aspect of the present invention includes a sensor unit that acquires physical information that can identify a locus of a change in a predetermined position caused by a walking motion of the measurement subject, and the physical that is acquired by the sensor unit. A control unit that determines the presence or absence of a gait abnormality in the walking movement based on the information; a display unit that displays a determination result image that can recognize the presence or absence of the gait abnormality determined by the control unit; A video capturing unit that captures the walking motion of the measurer, and the control unit acquires time-series data of a locus of a change in position in the walking motion of the measured person based on the physical information, and the position A data creation unit that creates Lissajous curve data in a predetermined plane based on time-series data of a change trajectory, and a series of walking motions of the measurement subject captured by the moving image capturing unit. Compare each of a plurality of actual curvature radius values extracted from the Lissajous curve data created by the data creation unit with a moving image storage unit for storing an image and a criterion value for the curvature radius, thereby An abnormal posture determination unit that determines whether or not the measured person is in an abnormal posture based on whether or not the actual radius of curvature is smaller than a reference value for determining the radius of curvature; and the abnormal posture determination Data of the abnormal posture timing is acquired based on which timing of the actual Lissajous curve data the actual radius of curvature determined to be smaller than the determination reference value by the unit, and thereby the moving image storage The abnormal figure which extracts the still picture of the abnormal posture corresponding to the data of the abnormal posture timing from the continuous image of the walking motion of the measurement subject stored in the section It includes an extraction unit, and a display control unit for displaying on the display unit still images extracted the abnormal posture as the determination result image by the abnormal posture extraction unit.

The walking analysis system according to the fourth aspect of the present invention includes a sensor unit that acquires physical information that can identify a locus of a change in a predetermined position caused by a walking motion of the measurement subject, and the physical that is acquired by the sensor unit. A control unit that determines the presence or absence of a walking abnormality in the walking movement based on information, and a display unit that displays a determination result image capable of recognizing the presence or absence of the walking abnormality determined by the control unit. The control unit obtains time-series data of a position change locus in the walking motion of the measurement subject based on the physical information, and a Lissajous in a predetermined plane based on the time-series data of the position change locus A data creation unit for creating curve data, and predetermined values and values of a plurality of types of elements to be extracted extracted from the Lissajous curve data created by the data creation unit; Are compared with a plurality of types of determination criteria for the presence / absence of abnormalities, whereby an abnormal presence / absence determination unit for determining the presence / absence of abnormalities in the walking movement, and the abnormal walking of the measured person by the abnormal presence / absence determination unit A display control unit that displays a determination result image capable of recognizing the abnormal walking motion on the display unit when it is determined that the user is exercising, and the data creation unit includes the measurement subject The Lissajous curve data for each of a frontal plane, a horizontal plane, and a sagittal plane is created, and the predetermined plural kinds of abnormality determination criteria values are the frontal plane, the horizontal plane, and the sagittal plane, respectively. of which corresponds to each of the Lissajous curve data the plurality of types of the determination target element extracted from the judgment result image to correspond to each of the determined elements of the plurality of types of the determination factors Including a recognizable image of the gait abnormalities.

The walking analysis program according to the first aspect of the present invention includes a sensor unit that acquires physical information that can specify a trajectory of a change in a predetermined position that occurs due to a walking motion of the measurement subject, and the physical that is acquired by the sensor unit. A control unit that determines the presence or absence of a walking abnormality in the walking movement based on information, and a display unit that displays a determination result image capable of recognizing the presence or absence of the walking abnormality determined by the control unit. A gait analysis program used in the gait analysis system, wherein the computer as the control unit obtains time-series data of a locus of a change in position in the walking movement of the measured person based on the physical information, and A data creation unit that creates Lissajous curve data in a predetermined plane based on time-series data of a locus of change in position, and the data creation unit The plurality of types of elements to be determined extracted from the created Lissajous curve data are respectively compared with a plurality of types of determination criteria values for the presence / absence of abnormality, whereby a plurality of predetermined body parts For each of the above, an abnormal part determination unit that determines whether or not the body part is performing an abnormal motion, and a timing at which the abnormal part determination unit determines that the body part is performing an abnormal motion An abnormal phase determination unit that determines which of the plurality of predetermined phases of the walking movement the abnormal movement of the body part is based on which timing of the Lissajous curve data; and The body part that is determined to be performing abnormal exercise by the abnormal part determination unit and the abnormal phase determination unit perform abnormal movement. The determination result image associated with the phase determined to be present is displayed on the display unit, and the determination result image is a plurality of still images displayed on the display unit. A plurality of human-type images respectively corresponding to the plurality of phases of the walking movement of the measured person, and the abnormal phase determination unit of the plurality of human-type images is performing an abnormal movement in the person image corresponding to the determined said phase includes a pointed image to point out the body part is determined to be an abnormal motion by the abnormal condition part determination unit.

The walking analysis system according to the second aspect of the present invention includes a sensor unit that acquires physical information that can specify a locus of a change in a predetermined position caused by a walking motion of the measurement subject, and the physical that is acquired by the sensor unit. a display unit for displaying the determining control unit the presence or absence of abnormal gait, the determination result image capable of recognizing the presence or absence of the abnormal gait, which is determined by the control unit in the walking exercise on the basis of the information, the object A walking analysis program for use in a walking analysis system including a moving image shooting unit that captures a walking motion of a measurer, the computer serving as the control unit, the walking motion of the measured person based on the physical information Time-series data of the position change trajectory at, and the Lissajous curve data in a predetermined plane based on the time-series data of the position change trajectory A data creation unit to be formed, and a plurality of types of determination element values extracted from the Lissajous curve data created by the data creation unit and a predetermined plurality of types of determination criteria values for the presence or absence of abnormalities, respectively, Thereby, it is determined that there is the walking abnormality by the abnormality type determination unit that determines whether or not there are a plurality of types of predetermined walking abnormalities in the walking movement of the measurement subject, and the abnormality type determination unit. For each type of gait abnormality, an abnormality degree determination unit that determines the degree of the gait abnormality based on a difference between the value of the element to be determined and a determination reference value for the presence or absence of abnormality, and the abnormality type determination unit The determination unit displays the determination result image in which the determined type of walking abnormality is associated with the degree of walking abnormality determined by the abnormality determining unit. Display control unit for, to function as the determination result image includes a person image extracted from a moving image shot at the moving image photographing part, a plurality of types capable of recognizing plural kinds of abnormal gait, respectively A character image, and a chart image capable of recognizing the degree of the gait abnormality specified by each of the plurality of types of character images.

  The walking analysis program according to the third aspect of the present invention includes a sensor unit that acquires physical information that can specify a trajectory of a change in a predetermined position caused by a walking motion of the measurement subject, and the physical that is acquired by the sensor unit. A control unit that determines the presence or absence of a gait abnormality in the walking movement based on the information; a display unit that displays a determination result image that can recognize the presence or absence of the gait abnormality determined by the control unit; A walking analysis program for use in a walking analysis system including a moving image shooting unit that captures a walking motion of a measurer, the computer serving as the control unit, the walking motion of the measured person based on the physical information Time-series data of a position change trajectory at the position, and Lissajous curve data on a predetermined plane based on the time-change data of the position change trajectory A data creation unit to be created, a moving image storage unit that stores a continuous image of the walking motion of the measurement subject photographed by the video photographing unit, and a plurality of actual data extracted from the Lissajous curve data created by the data creation unit Each of the curvature radius values is compared with a criterion value for determining the curvature radius, so that depending on whether the actual curvature radius value is smaller than the criterion value for determining the curvature radius, An abnormal posture determination unit that determines whether or not the posture is abnormal, and any timing of the actual Lissajous curve data that is determined to be smaller than the determination reference value by the abnormal posture determination unit Based on whether or not the abnormal posture timing data is acquired, thereby, the continuous image of the walking motion of the measured person stored in the moving image storage unit The abnormal posture extraction unit that extracts a still image of an abnormal posture corresponding to the data of the abnormal posture timing, and the still image of the abnormal posture extracted by the abnormal posture extraction unit as the determination result image on the display unit It functions as a display control unit to be displayed.

The walking analysis program according to the fourth aspect of the present invention includes a sensor unit that acquires physical information that can specify a trajectory of a change in a predetermined position caused by a walking motion of the measurement subject, and the physical that is acquired by the sensor unit. A control unit that determines the presence or absence of a walking abnormality in the walking movement based on information, and a display unit that displays a determination result image capable of recognizing the presence or absence of the walking abnormality determined by the control unit. A computer program used in the walking analysis system, wherein the computer as the control unit obtains time-series data of a locus of a change in position in the walking motion of the measured person based on the physical information, and A data creation unit that creates Lissajous curve data on a predetermined plane based on time-series data of a change locus, created by the data creation unit. In addition, a plurality of types of determination element values extracted from the Lissajous curve data are respectively compared with a plurality of predetermined determination criteria values for the presence / absence of abnormality, thereby determining the presence / absence of abnormality in the walking exercise. When it is determined by the abnormality presence / absence determination unit and the abnormality presence / absence determination unit that the measured person is performing an abnormal walking motion, a determination result image capable of recognizing the abnormal walking motion is displayed on the display unit. And the data creation unit creates the Lissajous curve data for each of the frontal plane, the horizontal plane, and the sagittal plane of the person to be measured, and whether or not there are a plurality of predetermined abnormalities. The determination reference values of the plurality of types of elements to be determined extracted from the Lissajous curve data of the frontal plane, the horizontal plane, and the sagittal plane, respectively. Has response, the judgment result image includes a recognizable image gait abnormalities corresponding to each of the determined elements of the plurality of types of the determination factors.

  According to the present invention, it is possible to intuitively understand how the walking motion is abnormal.

It is a figure for demonstrating the use condition of the walk analysis system of embodiment of this invention. It is a block diagram for demonstrating the function of each part of the walk analysis system of embodiment of this invention. It is a figure which shows an example of the Lissajous curve data of the front face value of the normal walking motion used as the reference | standard for comparison in the walk analysis system of embodiment of this invention. It is a figure which shows an example of the Lissajous curve data of the horizontal surface of the normal walking motion used as the reference | standard for comparison in the walk analysis system of embodiment of this invention. It is a figure which shows an example of the Lissajous surface data of the sagittal surface of the normal walking motion used as the reference | standard for comparison in the walk analysis system of embodiment of this invention. It is a figure which shows an example of the Lissajous curve data of the front face value of the to-be-measured person's walk exercise | movement acquired in the walk analysis system of embodiment of this invention. It is a figure which shows an example of the Lissajous curve data of the horizontal surface of the to-be-measured person's walk motion acquired in the walk analysis system of embodiment of this invention. It is a figure which shows an example of the Lissajous-surface Lissajous surface data of the to-be-measured person's walk motion acquired in the walk analysis system of embodiment of this invention. It is a figure for demonstrating the determination method of the abnormal walk in the case of using the Lissajous curve data of the front face value of the walk movement in the walk analysis system of embodiment of this invention. It is a figure for demonstrating the determination method of the abnormal walk in the case of using the Lissajous curve data of the horizontal surface of the walk movement in the walk analysis system of embodiment of this invention. It is a figure for demonstrating the determination method of the abnormal walk in the case of using the sagittal plane Lissajous curve data of the walk movement in the walk analysis system of embodiment of this invention. It is a 1st figure for demonstrating the display aspect of the determination result of the presence or absence of the abnormality of the walking movement obtained by the walk analysis system of embodiment of this invention. It is a 2nd figure for demonstrating the display mode of the determination result of the presence or absence of abnormality of the walk movement obtained by the walk analysis system of embodiment of this invention. It is a 3rd figure for demonstrating the display mode of the determination result of the presence or absence of abnormality of the walking movement obtained by the walk analysis system of embodiment of this invention.

  Hereinafter, a walking analysis system and a walking analysis program according to an embodiment of the present invention will be described with reference to the drawings.

(Whole analysis system configuration)
As shown in FIG. 1, the walking analysis system 90 according to the present embodiment includes a sensor unit 1 and a tablet terminal 10. The tablet terminal 10 includes a display unit 2 and a control unit 3. Therefore, the walking analysis system 90 includes the sensor unit 1, the display unit 2, and the control unit 3.

  The sensor unit 1 includes an antenna unit and a wireless information transmission unit that transmits wireless information from the antenna unit. The tablet terminal 10 has a communication function as a mobile phone. Therefore, the tablet terminal 10 has an antenna unit that receives wireless information transmitted from the sensor unit 1 and wireless information that can be extracted by the sensor unit 1 from the wireless information received by the antenna unit. And an extraction unit. The tablet terminal 10 is also a kind of personal computer. Therefore, the wireless information can be processed.

  The display unit 2 is composed of a liquid crystal display unit. However, any other display unit can be used as long as it can display a determination result image of walking analysis based on a control command from the control unit 3. May be. The control unit 3 includes a central processing unit (CPU), a read only memory (ROM), and a random access memory (RAM) in order to realize a function as a personal computer.

  The sensor unit 1 is attached to a measurement subject 100 who performs a walking motion, and acquires physical information that can specify a change locus of a predetermined position of the measurement subject 100. In the present embodiment, the sensor unit 1 is a three-axis acceleration sensor. Therefore, the sensor unit 1 is attached to the measurement subject 100 and moves with the measurement subject 100 to detect accelerations in the three axial directions orthogonal to the measurement subject 100.

  The acceleration sensor walks a long distance without being aware of the angle of view (field of view) of the video camera, as compared with the case where the abnormality is analyzed based on the walking motion recorded by the video camera. Can also measure its walking movement. Information about each acceleration in the three-axis directions detected by the acceleration sensor is transmitted from the acceleration sensor to the tablet terminal 10 as wireless information.

  However, the sensor unit 1 may be anything as long as it acquires time-series data of a change in the position of the measurement subject 100 who performs walking motion. In other words, any sensor unit 1 can be used as long as the data creation unit 31 of the control unit 3 to be described later can create Lissajous curve data in a predetermined plane based on time-series data of position changes. It may be.

  In this specification, Lissajous curve data is data obtained by projecting three-dimensional displacement history data onto a two-dimensional plane. The figure drawn by the displacement history data projected on the plane is similar to the Lissajous figure used in mathematics. For this reason, in this specification, two-dimensional displacement history data obtained by projecting three-dimensional displacement history data onto a plane is referred to as Lissajous curve data.

  As shown in FIG. 1, in the present embodiment, the three-axis acceleration sensor as the sensor unit 1 is attached to the back side of the waist that is in the vicinity of the position of the center of gravity of the measurement subject 100.

  The acceleration sensor is affected by gravitational acceleration having a low frequency that is less than half the walking frequency. Therefore, the low frequency component of the acceleration obtained by the acceleration sensor is removed by FFT (Fast Fourier Transform).

  Further, in order to obtain only the displacement at a predetermined position in the walking motion, the acceleration component in the traveling direction is also removed from the acceleration obtained by the acceleration sensor. As a result, in normal walking, the locus of displacement of the frontal plane, sagittal plane, and horizontal plane draws a figure that resembles a Lissajous figure in a mathematical sense.

  The sensor unit 1 moves along with the walking motion of the person 100 to be measured, and transmits information on the respective accelerations of the three axes to the tablet terminal 10 as wireless information. In addition, the tablet terminal 10 includes an antenna unit (not shown) that can receive wireless information transmitted from the sensor unit 10.

  However, any sensor unit 1 can be used as long as it can create Lissajous curve data based on physical information that can specify a locus of a change in a predetermined position caused by the walking motion of the person 100 to be measured. Good. The sensor unit 1 is a sensor provided in the tablet terminal 10 as long as it can acquire information on the displacement of the person 100 to be measured and thereby can create Lissajous curve data from the information on the displacement. May be. For example, the moving image photographing unit 4 or the like provided in the tablet terminal 10 may fulfill the function of the sensor unit.

  In addition, the moving image photographing unit 4 includes, for example, two lens systems and two imaging elements, and the control unit 3 uses a specific mark attached to the measurement subject 100 from images photographed by the two imaging elements. The locus of the change in the position may be calculated. That is, the displacement information of the measurement subject 100 may be calculated based on the continuous images of the two viewpoints captured by the moving image capturing unit 4. Also in this case, Lissajous curve data is created based on the calculated displacement information.

  The display unit 2 is a touch panel type input unit. By clicking an icon for a gait analysis system displayed on the touch panel type display unit 2, a gait analysis program is started and a gait analysis system is configured. The start and end of the gait analysis is also performed by clicking the start icon displayed on the display unit 2 and the end. Further, the determination result display is displayed on the display unit 2 by clicking the determination result display icon. Since the functions of the display unit 2 of these tablet terminals 10 are the same as the functions of the tablet terminal having the functions of a normal mobile phone, detailed description thereof is omitted.

  As shown in FIG. 2, the display unit 2 of the present embodiment has a determination result image X, a determination result image Y, and a determination result image that can recognize the presence / absence of a gait abnormality determined by the control unit 3. Each Z is displayed. It is assumed that the determination result image X, the determination result image Y, and the determination result image Z are simultaneously displayed in the display area 21, the display area 22, and the display area 23, respectively. Details of the determination result image X, the determination result image Y, and the determination result image Z will be described later.

  When the wireless information transmitted from the sensor unit 1 is received by the wireless information receiving unit, the control unit 3 is transmitted to the data creation unit 31 described later. Since the reception function of the wireless information of the tablet terminal 10 is the same as the function of the tablet terminal having a normal mobile phone function, detailed description thereof is omitted. Based on the physical information acquired by the sensor unit 1, the control unit 3 determines whether or not there is a walking abnormality in the walking motion.

(Movie shooting)
As shown in FIG. 1, the walking analysis system 90 according to the present embodiment further includes a moving image photographing unit 4 having an optical system facing outward from a surface opposite to the display unit 2 of the tablet terminal 10. . The moving image photographing unit 4 can photograph an object existing on the back side of the display unit 2. The video captured by the moving image capturing unit 4 is displayed on the display unit 2 in real time.

  Therefore, the measurer 200 can capture the walking motion of the measured person 100 while watching the walking motion of the measured person 100 displayed on the display unit 2. That is, the tablet terminal 10 is a computer having a video camera function for moving image shooting. The moving image photographing unit 4 is used for photographing the walking motion of the measurement subject 100.

  However, the tablet terminal 10 may not have the moving image photographing unit 4. When the tablet terminal 10 does not have the moving image photographing unit 4, it is stored in the character storage unit 38 instead of the walking motion posture image extracted from the continuous walking motion continuous image of the measurement subject 100. A character image that is displayed may be used. This detail will be described later.

  When the moving image shooting unit 4 is used, the moving image shooting unit 4 does not need to be built in the tablet terminal 10. The moving image shooting unit 4 is a video camera independent of the tablet terminal 10 and may transmit the shot moving image of the person 100 to be measured to the tablet terminal 10 as wireless information or wired information. .

(Walk analysis program)
As shown in FIG. 2, the recording medium 50 records a gait analysis program that can be read by a computer. The gait analysis program is for operating the gait analysis system 90. The walking analysis program recorded in the recording medium 50 is read from the recording medium 50 into the program storage unit 5 as a RAM in the tablet terminal 10. The walking analysis program recorded on the recording medium 50 can be read by other tablet terminals or personal computers.

  The recording medium 50 is an example of a computer program product that includes instructions issued by the walking analysis program. The recording medium 50 may be anything such as a CD-ROM (Compact Disc-Read Only Memory), a stick memory, an optical disk, or a server on the Internet. That is, the recording medium 50 may be anything as long as it records the walking analysis program in a computer-readable manner.

  In the case of cloud computing, the storage unit of the server on the Internet is a computer-readable recording medium for the walking analysis program, and the server computer reads and executes the walking analysis program. In the case of the cloud computing, the sensor unit 1 and the display unit 2 exist in the tablet terminal 10, but a part of the control unit 3 exists in a server on the Internet, and the other part of the control unit 3 is a tablet terminal. Present in machine 10.

  The computer as the control unit 30 of the gait analysis system 90 reads the gait analysis program recorded in the recording medium 50 and stores it in the program storage unit 5. The walking analysis program stored in the program storage unit 5 causes the computer as the control unit 30 to function as each unit of the walking analysis system.

  In the present embodiment, the gait analysis program uses the computer as the control unit 3 in the gait analysis system 90 as the data creation unit 31, the abnormal site determination unit 32, the abnormal phase determination unit 33, and the display control unit 39. Make it work. The gait analysis program is used in the gait analysis system 90, and causes the computer as the control unit 3 to function as the data creation unit 31, the abnormality type determination unit 34, the abnormality degree determination unit 35, and the display control unit 39. . The walking analysis program causes the computer as the control unit 3 to function as the data creation unit 31, the moving image storage unit 36, the abnormal posture determination unit 301, the abnormal posture extraction unit 302, and the display control unit 39.

  The gait analysis program is used in the gait analysis system 90 including the sensor unit 1, the control unit 3, and the display unit 2, and the computer as the control unit 3 is replaced with a data creation unit 31, an abnormality presence / absence determination unit 300, And function as the display control unit 39. The abnormality presence / absence determination unit 300 includes an abnormal part determination unit 32, an abnormal phase determination unit 33, an abnormality type determination unit 34, an abnormality degree determination unit 35, an abnormal posture determination unit 301, and an abnormal posture extraction unit 302. These specific functions will be described later.

(Create Lissajous curve data)
As illustrated in FIG. 2, the data creation unit 31 acquires time-series data of a locus of a change in position in the walking motion of the measurement subject 100 based on the physical information acquired by the sensor unit 1. In the present embodiment, the data creation unit 31 calculates the time-series data of the locus of position change by integrating twice the data of each of the three axes transmitted from the three-axis acceleration sensor. . The data creation unit 31 creates Lissajous curve data on a predetermined plane based on the time-series data of the locus of position change. Specifically, in the Lissajous curve data, the time-series data of the trajectory of the three-dimensional position change is projected on each of the two-dimensional three planes (the xy plane, the yz plane, and the zx plane). Created by.

  As shown in FIGS. 3 to 5, Lissajous curve data serving as a reference for determining whether there is an abnormality in walking motion is created in advance. The reference Lissajous curve data is created in advance based on the Lissajous curve data of the measurement subject performing normal walking motion. A criterion value for the presence / absence of abnormality is extracted in advance from normal Lissajous curve data serving as a reference. This extracted reference value for the presence / absence of abnormality is incorporated in the gait analysis program. The determination reference value for the presence / absence of abnormality is extracted from the walking analysis program stored in the program storage unit 5 and used for determination of the presence / absence of abnormality.

  As shown in FIGS. 6 to 8, the Lissajous curve data is actually obtained as time-series data of the locus of the change in the position of the walking motion in a plurality of cycles. The Lissajous curve data shown in FIGS. 6 to 8 is Lissajous curve data of the measurement subject 100 performing normal walking motion. Therefore, it is not greatly different from the Lissajous curve data which is a criterion for determination shown in FIGS. The Lissajous curve data of the measurement subject 100 actually performing an abnormal walking motion is greatly different from the Lissajous curve data shown in FIGS.

(3 types of Lissajous curve data)
In the gait analysis system 90, the data creation unit 31 creates Lissajous curve data for each of the frontal plane, the horizontal plane, and the sagittal plane. Therefore, the plurality of types of determination criterion values for the presence / absence of abnormality respectively correspond to a plurality of determination elements extracted from the Lissajous curve data of the frontal plane, the horizontal plane, and the sagittal plane.

  According to the above configuration, walking abnormalities are detected from various viewpoints in order to detect walking abnormalities using the Lissajous curve data on the walking motion of the person 100 to be measured on the three planes including the frontal plane, the horizontal plane, and the sagittal plane. Abnormalities in movement can be detected.

(Criteria for abnormality)
The criteria for abnormality determination executed in the walking analysis system of the embodiment will be described with reference to FIGS.

  When the walking motion is abnormal, the Lissajous curve data has a characteristic shape on each of the frontal plane, the horizontal plane, and the sagittal plane. The presence / absence of an abnormal part is determined based on whether or not the characteristic shape is detected. In the present embodiment, the determination method described in FIGS. 9 to 11 is used.

  The result of the determination performed based on the method illustrated in FIGS. 9 to 11 is displayed on the display unit 2 as the determination result images X, Y, and Z illustrated in FIGS.

  In this embodiment, as can be seen from FIG. 12 and FIG. 14, the abnormal part and the abnormal phase are displayed on the display unit 2 so as to be intuitively grasped by a plurality of humanoid images H and indication images I. Is done.

  Also, the type of abnormality and the degree of abnormality are displayed on the display unit 2 so as to be intuitively grasped by the chart image G such as a laser chart. In addition, the posture at the timing of the abnormal movement of the person 100 to be measured is displayed on the display unit 2 so that it can be intuitively grasped by the still image K of the abnormal posture.

  Further, as can be seen from FIG. 13, information necessary for the instructor is also displayed on the display unit 2. The image shown in FIG. 12 and the image shown in FIG. 13 are switched and displayed on the display unit 2 by the touch operation of the screen switching icon on the display unit 2 of the user of the tablet terminal 10.

  Further, as shown in FIG. 14, the Lissajous curve data of the forehead plane, the horizontal plane, and the arrow plane in a plurality of measurements may be displayed on the display unit 2. As a result, a leader such as the measurer 200 can state the evaluation of the presence or absence of improvement in the walking abnormality of the measured person 100 while showing the Lissajous curve data displayed on the display unit 2. In this case, the determination result images X, Y, and Z may also be displayed on the display unit 2. However, the display of the Lissajous curve data on the display unit 2 is not essential.

  Hereinafter, a method for determining a gait abnormality in the gait analysis system of the present embodiment will be described. However, the abnormality determination method is not limited to the one described below, and other determination methods can be used as long as it is possible to determine the presence / absence of a gait abnormality using the determination target element extracted from the Lissajous curve data. May be used. The frontal plane is defined as the xy plane, the horizontal plane is defined as the xz plane, and the sagittal plane is defined as the yz plane. The X axis is an axis extending in the left-right direction of the body of the measurement subject 100, the Y axis is an axis extending in the vertical direction of the measurement subject 100, and the Z axis is the front and rear of the measurement subject 100 body. It is an axis extending in the direction.

(A: Judgment of presence or absence of abnormality using Lissajous curve of front face value)
As shown in FIG. 9, when the Lissajous curve data of the front face value is used, the presence or absence of the following three types of abnormalities can be determined.

  The three types of abnormalities are 1) abnormal balance of swing between the left and right parts of the body, 2) abnormal load balance between the left and right parts of the body, and 3) abnormalities in the movable region of the hip joint and knees. It is an abnormality in the movable area of the joint.

  1) The abnormality in the balance of the shake between the left part and the right part of the body is an abnormality in the function of balancing the left and right sides of the body. Balance function training is recommended for the person to be measured 100 determined to have this abnormality.

  2) An abnormality in the load balance between the left part and the right part of the body is an abnormal load. The measured person 100 determined to have this abnormality has a biased load applied to the left and right feet, so one-sided load training and lower limb strength training are recommended.

  3) The abnormality of the movable region of the hip joint and the abnormality of the movable region of the knee joint are an abnormality in which the extension function of the hip joint is lowered and an abnormality in which the knee joint is in an excessively bent state, respectively.

In FIG. 9, the distance from the Y axis to the upper left inflection point III _L is X _L, and the distance from the Y axis to the upper right inflection point III _R is X _R. In FIG. 9, X _f = X _L + X _R. Further, in FIG. 9, the distance in the direction parallel to the Y axis between the inflection point I _L inflection point III _L and the lower left side of the left upper and Y _L, and the inflection point III _R in the upper right side _Let Y _R be the distance in the direction parallel to the Y axis between the upper right inflection point IR. Further, in FIG. 9, the intersection _{II LR} Lissajous curve data, the inflection point III _L, and the area of a region surrounded by the inflection point _{I L} and _{S L,} Lissajous intersection of curve data _{II LR,} the inflection point III _R, and the area of a region surrounded by the inflection point _{I R} and _{S R.}

<1) Abnormal balance of shake between left and right body parts>
a) In FIG. 9, in the case of max (Y _R , Y _L ) / X _f > 0.5, if X _f = X _L + X _R <4.5 cm, the subject 100 is in a normal walking motion It is determined that you are doing. max (Y _R , Y _L ) means a larger value of the distance Y _R and the distance Y _L. On the other hand, in the case of max (Y _R , Y _L ) / X _f > 0.5, if X _f = X _L + X _R ≧ 4.5 cm, the person 100 to be measured can move the left and right parts of the body. It is determined that the walking movement has an abnormal balance with the part. max (Y _R , Y _L ) / X _f and X _f = X _L + X _R are the elements to be determined, and 0.5, 4.5 cm, and 7 cm are the determination reference values for the presence or absence of abnormality, respectively.

  The term “abnormality of the balance between the left part and the right part of the body” is displayed as a character image A capable of recognizing a gait abnormality. The character image A is displayed in a display area 22 (see FIG. 2) outside one of a plurality of axes of the radar chart of the determination result image Y described later with reference to FIG.

Further, depending on how much the value of X _f = X _L + X _R is larger than 4.5 cm, which is an example of the reference value, an abnormality in the balance of shake between the left part and the right part of the body of the person 100 to be measured It is determined to what extent. The degree of abnormality in the balance of the shake between the left and right parts of the body as the judgment result is the axis specified by the term “abnormality in the balance of the shake of the left and right parts of the body” on the left and right of the radar chart. It is displayed at the position of the point (or intersection line) plotted at. The radar chart and the points (or lines) plotted on the radar chart are a chart image G that can recognize the degree of abnormality.

b) In FIG. 9, when max (Y _R , Y _L ) / X _f ≦ 0.5, it is determined that the person to be measured 100 is walking on a wide base. However, in general, many elderly people walk in what is called wide-base walking. Therefore, when the person 100 to be measured is performing a wide base walking of 7 cm ≧ X _f = X _L + X _R ≧ 4.5 cm, it is not determined that the person 100 is performing an abnormal walking motion.

In the wide-based gait, if the _{7cm ≧ X f = X L +} X R ≧ 4.5cm, if _{(X L -X R) / 2} (X L + X R) × 100% is a positive value, the body The movement on the left side is greater than the movement on the right side of the body. On the other _hand, if _{(X L -X R) / 2} (X L + X R) a × 100% is a negative value, right motion of the body is larger in comparison to the left of the motion of the body. In this case, max (Y _R , Y _L ) / X _f , X _f = X _L + X _R , and (X _L −X _R ) / 2 (X _L + X _R ) × 100% are the values of the elements to be determined, respectively. 0.5, 4.5 cm, and 7 cm are judgment reference values for the presence or absence of abnormality, respectively.

In this case, the value of (X _L −X _R ) / 2 (X _L + X _R ) × 100%, which is the element to be determined, is compared with the corresponding determination criterion value for the presence or absence of abnormality. As a result of the comparison, if (X _L −X _R ) / 2 (X _L + X _R ) × 100%> reference value, it is determined whether or not there is an abnormality in the balance between the left part and the right part of the body Is done. Further, according to the comparison result, the degree of abnormality in the balance of shake between the left part and the right part of the body is classified into one of a plurality of stages.

  The types of abnormalities of the shake balance between the left part and the right part of the body and the degree of the abnormalities are displayed by the radar chart as the determination result image Y shown in FIGS.

<2) Abnormal load balance between the left and right parts of the body>
In FIG. 9, if the difference between the area S _L and the area S _R that is the determination target element is larger than 10% of the sum of the area S _L and the area S _R that is the determination criterion value of abnormality, It is determined that there is an abnormality in the load balance between the portion and the right portion. That is, it is determined that there is a bias in how to apply weight to the left foot and the right foot. Further, depending on how much the difference between the area S _L and the area S _R is, the degree of abnormality of the load balance between the left part and the right part of the body is classified into one of a plurality of stages. .

The area S _L and the area S _R may be strictly calculated by integration, but may be calculated by a simplified method of product of orthogonal representative lengths.

  The type of load balance abnormality between the left and right parts of the body and the degree of load balance abnormality between the left and right parts of the body are also displayed by the radar chart as the determination result image Y. However, the character image “abnormal load balance between the left and right parts of the body” is not shown in FIGS. 2 and 12 for the sake of simplicity. In the radar chart, a character image “abnormality of load balance between the left and right parts of the body” is displayed as a character image capable of recognizing abnormal walking. The radar chart and the points (or lines) plotted on the radar chart are a chart image G that can recognize the degree of abnormality.

<3) Abnormality of movable area of hip joint and abnormal area of movable area of knee joint>
9 compares the standard moving distance Ystd = 3cm a criterion value for each and abnormal absence of the movable distance Y _R of the movable distance Y _L and right body left the body is the value of the determination factors. Thereby, each of the movable distance Y _L and the movable distance Y _R is larger than the standard moving distance Ystd = 3cm, they are determined to be normal moving distance. The degree of abnormality of the movable region of the hip joint, in accordance with the difference between respectively the reference distance Ystd movable distance Y _L and the movable distance Y _R of the person to be measured 100, is classified into any stage of the multiple stages .

The value of the difference between the movable distance Y _L and the moving distance Y _R is movable distance Y _L and the moving distance Y is greater than 10% of the value of the sum of the _R, right and left hip joints of the movable region and the left and right knee It is determined that the balance of the movable area of the joint is poor.

When the balance of the movable region of the movable area and the left and right knee joints of the right and left hip joints is poor, either the position of the inflection point I _R inflection point I _L and the lower right side of the lower left side, Y-axis direction May be on the upper side. In this case, it is determined that there is an abnormality in the decrease in extension of the hip joint of the foot corresponding to the upper inflection point. That is, compared with the distance from the distance and the X-axis from the X axis to the inflection point I _L on the lower left side to the inflection point I _R of the lower right side, thereby varying more distance from the X-axis is small It is determined that there is an abnormality in the extension of the hip joint corresponding to the inflection point.

When the balance of the movable region of the movable area and the left and right knee joints of the right and left hip joints is poor, either the position of the inflection point III _R inflection point of the upper left III _L and right upper side, the lower side in the Y-axis direction There may be. In this case, it is determined that the knee joint of the foot corresponding to the lower inflection point has an abnormality in overflexion. That is, the distance from the X axis to the upper left inflection point III _L is compared with the distance from the X axis to the upper right inflection point III _R , so that the inflection with the smaller distance from the X axis is made. It is determined that there is an abnormality in the knee joint hyperflexion corresponding to the point.

  The abnormality of the movable area of the hip joint and the abnormality of the movable area of the knee joint are respectively displayed as items of one axis of the radar chart of the determination result image Y shown in FIGS. The degree of abnormality of the movable region of the hip joint and the degree of abnormality of the movable region of the knee joint are displayed by the positions of points (or lines) plotted on the radar chart. In the radar chart, a character image “abnormality of the movable region of the hip joint” and a character image “abnormality of the movable region of the knee joint” can recognize the walking abnormality, respectively. Displayed as D. Further, this radar chart and the points (or lines) plotted on the radar chart are a chart image G in which the degree of abnormality can be recognized.

Further, regarding the abnormality of the movable region of the hip joint and the abnormality of the movable region of the knee joint, the hip and knee as a body part having an abnormality in walking are indicated by the indication image I in the determination result image X, respectively. Also, whether the pointed image I in any of the person image of the plurality of person image H is displayed, Lissajous curve data in a period corresponding to each of the movable distance Y _L and the movable distance Y _R is acquired Determined based on timing. Therefore, in any one of the plurality of humanoid images H displayed in the display area 21 shown in FIG. Thereby, the person to be measured 100 can easily understand which part is abnormal in which phase of the walking motion.

(B: Determination of the presence or absence of abnormality using a Lissajous curve on the horizontal plane)
As shown in FIG. 10, when using the Lissajous curve data on the horizontal plane, 4) it is possible to determine the presence or absence of an ankle joint abnormality. Further, when the Lissajous curve data on the horizontal plane is used, it is possible to determine the presence or absence of abnormalities in hip flexion and ankle joint (ankle joint). When using the Lissajous curve data on the horizontal plane, 6) it is possible to determine whether there is an abnormality in the entire foot on the ground contact side.

In FIG. 10, the left three inflection points are IV _L , VI _L , and VII _L , respectively, and the right three inflection points are IV _R , VI _R , and VII _R , respectively. 10, a _{V LR} an intersection Lissajous curve data. Depending on the position in each of the Z-axis direction of the inflection point IV _R and right inflection points VI _L on the left, it is possible to determine the presence or absence of abnormality of the movable region of the foot articulation. In FIG. 10, the radius of curvature at the coordinates (x, z) of the graph having the xz coordinate axis indicating the Lissajous curve data on the horizontal plane is set as r. <4) Abnormality of the dorsiflexion movable range of the foot (ankle) joint >
When the z-coordinate of the left inflection point IV _L or the right inflection point IV _R > 0, the left inflection point IV _R or the right inflection point IV _L is in front of the intersection V _LR . In this case, if the x-coordinate> 3 mm inflection point IV _R, there are abnormalities in the back屈可dynamic range of the left foot joint, if the x-coordinate <-3 mm inflection point IV _L, back屈可movement of the right foot joint It is determined that there is a region abnormality. Z-coordinate of the inflection point IV _L of the left, z coordinates of the right inflection point IV _R, x-coordinate of the inflexion point IV _R of the left, and the x coordinate of the inflection point IV _L, respectively, of the decision element 0, 3 mm, and -3 mm are judgment reference values for the presence or absence of abnormality.

  The normal dorsiflexion range of motion of the left ankle joint and the abnormal dorsiflexion range of motion of the right foot joint are displayed as items on one axis of the radar chart of the determination result image Y shown in FIGS. Further, the degree of abnormality of the dorsiflexion range of motion of the left ankle joint and the degree of abnormality of the dorsiflexion range of motion of the right ankle joint depend on the difference between the aforementioned determination target element and 3 mm or -3 mm which is the determination reference value of abnormality And classified into one of a plurality of stages. The degree of dorsiflexion abnormality of the left ankle joint and the degree of dorsiflexion abnormality of the right ankle joint are respectively displayed by the positions of points (or lines) plotted on the radar chart.

  In the radar chart, the character image “abnormal dorsiflexion range of motion of the left ankle joint” and the character image “abnormality of dorsiflexion range of motion of the right ankle joint” are characters that can recognize the gait abnormality, respectively. It is displayed as one of images A, B, C, D, and E. However, in FIG. 2 and FIG. 12, for the sake of simplification, the character image “abnormality of the dorsiflexion range of the left ankle joint” and the character image “abnormality of the dorsiflexion range of the right ankle joint” are described. It has not been. Further, this radar chart and the points (or lines) plotted on the radar chart are a chart image G in which the degree of abnormality can be recognized.

<5) Abnormal hip rotation and anomalies in plantar flexion of the foot (ankle) joint>
10, the angle between the line segment _IV L _{-V LR} and X axis connecting the inflection point IV _L and the intersection _{V LR} of the left and theta _L. Further, in FIG. 10, the line IV _R connecting the right inflection point IV _R and the intersection _{V LR} - the intersection _{V LR} and X-axis and the angle formed by the theta _R. Each angle theta _R angle theta _L and the right hip rotation of the pivoting of the left hip in FIG. 10, whether too large is determined.

When the angle θ _L > 0 of the left hip swing, that is, when the inflection point IV _L is in front of the intersection V _{LR in} the direction along the Z axis, the left side if the angle θ _L > 10 degrees It is determined that the hip turn is insufficient. In this case, it is determined that it is necessary to train the right middle psoas muscle. When the angle θ _R > 0 of the right hip swing, that is, when the inflection point IV _R is in front of the intersection V _{LR in} the direction along the Z axis, if the angle θ _R > 10 degrees, the right side It is determined that the hip turn is insufficient. In this case, it is determined that it is necessary to train the left middle waist muscle.

When the left hip turning angle θ _L <0, that is, when the inflection point IV _L is behind the intersection V _{LR in} the direction along the Z axis, the left hip turning angle θ _L < If it is −10 degrees, it is determined that the bottom flexion force of the right ankle joint is insufficient. In this case, it is determined that it is necessary to train the right leg muscle. When the angle θ _R <0 of the right hip swing, that is, when the inflection point IV _R is behind the intersection V _{LR in} the direction along the Z axis, the angle θ _R <−10 degrees. It is determined that the bottom flexion force of the left ankle joint is insufficient. In this case, it is determined that it is necessary to train the left leg muscle.

In the above case, the angle θ _L and the angle θ _R are the values of the elements to be determined, respectively, and 10 degrees and −10 degrees are the determination reference values for the presence / absence of abnormality.

The abnormality of the rotation of the hips and the abnormality of the plantar flexion force of the foot (ankle) joint are displayed as items of one axis of the radar chart of the determination result image Y shown in FIGS. In addition, the degree of abnormality of the hip rotation (or the degree of abnormality of the ankle plantar flexion force) is the angle θ _L (or angle θ _R ) and 10 degrees (or −10 degrees) which is a criterion value for the presence or absence of abnormality. Depending on the difference between the two, it is classified into one of a plurality of stages.

  The degree of abnormality of the hip rotation and the degree of abnormality of the bottom flexion force of the ankle joint are respectively displayed by the positions of the points plotted on the radar chart. In the radar chart, a character image “abnormal rotation of the hips” and a character image “abnormality of plantar flexion of the ankle joint” are displayed as character images capable of recognizing abnormal walking. . For example, in FIG. 12, a character image C “abnormality of ankle plantar flexion force” is displayed. Further, the radar chart and the lines (or lines and points) plotted on the radar chart are the chart image G that can recognize the degree of abnormality.

In addition, regarding the abnormality in the rotation of the hips and the abnormality in the plantar flexion force of the ankle joint, the hips and feet (ankles) as body parts having an abnormal walking are pointed out by the indication image I in the determination result image X. Also, whether the pointed image I in any of the person image of the plurality of human-type image H is displayed, respective data of the angle theta _L and the angle theta _R is determined from the timing of the acquired Lissajous curve data were The In this case, in any one of the humanoid images H shown in FIGS. 2 and 12, a body part having an abnormality among the waist, the left foot, and the right foot is pointed out by the pointing image I. Thereby, the person to be measured 100 can easily understand the abnormal body part.

<6) Abnormalities in the entire grounded foot>
In FIG. 10, when the radius of curvature r <1 mm, it is determined that there is an abnormal motion of the entire grounded foot. The entire foot that is in contact with the ground is the entire foot opposite to the entire foot that is floating in the air. The timing at which the abnormality has occurred is grasped from the coordinates of the radius of curvature r, and a still image K having an abnormal posture corresponding to the timing is extracted from the continuous images captured by the moving image capturing unit 4. The still image K having an abnormal posture is displayed as the determination result image Z in the display area 23 of the display unit 2. In this case, the value of the radius of curvature r is the element to be determined, and 1 mm is the determination reference value for the presence or absence of abnormality.

According to this, for example, a curvature radius r <1 at the inflection point IV _L of the left, and, when close to the maximum value the value of x-coordinate of the inflexion point IV _L on the left side can be taken by the x-coordinate, left It is determined that there is a gait abnormality at the middle of the stance, at approximately the middle point of the period when the left foot is in contact with the ground.

(C: Determination of presence or absence of abnormality using Lissajous surface Lissajous curve)
As shown in FIG. 11, when using the sagittal Lissajous curve data, 7) it is possible to determine the presence or absence of an abnormal foot kick. In general, Lissajous curve data drawn on a sagittal plane (yz plane) in one walking cycle is a figure that can be approximated by two ellipses. Ellipses drawn by solid lines shown in FIG. 11 is a ellipse angle is phi _R formed by the Y-axis of the major axis and graphs Lissajous curve data when the right foot is arrived at ground oval Is approximated by The ellipse drawn by the alternate long and short dash line in FIG. 11 is an ellipse (φ _L = 0) in which the long axis and the Y axis of the graph overlap, and the Lissajous curve data when the left foot is on the ground is It is approximated to an ellipse. According to the figure approximated to the two ellipses shown in FIG. 11, the angle is φ _R > the determination criterion value of the presence / absence of abnormality, so that the walking abnormality occurs when the right foot is on the ground. It is determined.
<7) Abnormal foot kick>
An approximate ellipse is created from the sagittal Lissajous curve data, and the presence or absence of abnormal foot kick is determined using the magnitude of the angle φ formed by the major axis of the approximate ellipse and the Y axis. For example, when the angle φ is greater than 5 degrees, it is determined that the kick of the foot opposite to the foot that is in contact with the ground at the timing when the angle φ is acquired is weak. That is, of the right angle phi _R when the left angle phi _L and the right foot when the left foot is contact with the ground is contact with the ground, if the left side of the angle phi _L> 5 degrees, the right foot If it is determined that the kick is weak and the right angle φ _R > 5 degrees, it is determined that the kick of the left foot is weak. In this case, the left angle phi _L and right angle phi _R is, it it is the value of the determination factors, 5 degrees, which is the determination reference value of the abnormality presence or absence.

  The abnormal foot kick is displayed as an item on one axis of the radar chart of the determination result image Y shown in FIGS. Further, the degree of abnormal foot kick is determined according to the difference between the angle φ and the reference value of 5 degrees, and is displayed by the position of the point (or line) plotted on the radar chart. In the radar chart, a character image “abnormality of kicking right foot” and a character image “abnormality of kicking left foot” are displayed as a character image capable of recognizing a walking abnormality. In FIG. 12, for example, a character image E “abnormal kicking of the right foot” is described. Further, the radar chart and the line (or point) plotted on the radar chart are a chart image G in which the degree of abnormality can be recognized.

<8) Abnormalities in the entire grounded foot>
Also in FIG. 11, as in FIG. 10, when the curvature radius r <1 mm of the Lissajous curve, it is determined that there is an abnormal operation of the entire grounded foot. In this case, the value of the radius of curvature r is the element to be determined, and 1 mm is the determination reference value for the presence or absence of abnormality. The timing at which the abnormality occurs is grasped from the coordinates of the radius of curvature r, and a still image K having an abnormal posture corresponding to the timing is extracted from the continuous images captured by the moving image capturing unit 4. The still image K having an abnormal posture is displayed as the determination result image Z in the display area 23 of the display unit 2.
(Configuration for abnormality determination)
The walking analysis system of the embodiment has a configuration as shown in FIG. 2 as a configuration for using the above-described abnormality determination method.
(Configuration for determining abnormal sites and determining abnormal phases)
As shown in FIG. 2, the control unit 3 includes a data creation unit 31, an abnormal site determination unit 32, an abnormal phase determination unit 33, and a display control unit 39 for determining an abnormal site and determining an abnormal phase. It is out.

  The abnormal part determination unit 32 compares a plurality of types of determination element values extracted from the Lissajous curve data created by the data creation unit 31 with a plurality of types of determination criterion values for presence / absence of abnormality. Thereby, the abnormal part determination part 32 determines whether the body part is carrying out the abnormal exercise | movement for each of several predetermined body parts. In the present embodiment, the body parts are the waist, the legs (ankles), the knees, and the crotch, but the presence / absence of abnormality of other body parts may be determined.

An example of the above-described determination target element is the left body part movable distance Y _L described in the section <3) Abnormal hip joint movable area and abnormal knee joint area> and the right body part. a movable distance _{Y R.} Another example of the above-described elements to be judged is the left angle θ _L and the right angle described in the above item <5) Abnormal hip rotation and abnormal ankle plantar flexion force>. it is θ _R.

  The abnormal phase determination unit 33 determines in which of a plurality of predetermined phases of the walking movement the body part determined to be performing abnormal exercise by the abnormal part determination unit 32. judge. This determination is made based on which timing of the Lissajous curve data the timing at which the abnormal part determination unit 32 determines that the body part is in an abnormal motion. The timing at which the body part is determined to be abnormally moving by the abnormal part determination unit 32 means the timing at which the body part is actually performing an abnormal motion. The timing of the Lissajous curve data is the timing at which time-series data of the position change locus for creating the Lissajous curve data is acquired.

  The display control unit 39 determines that the body part determined to be performing abnormal exercise by the abnormal part determination unit 32 and the phase determined to be abnormal movement by the abnormal phase determination unit 33 are associated with each other. The result image X is displayed on the display unit 2.

(Judgment result image X)
As shown in FIG. 2, the determination result image X is displayed in the display area 21 of the display unit 2. The determination result image X includes a plurality of humanoid images H and indication images I. Specifically, an image as shown in FIG. 12 is displayed.

  The plurality of human-type images H are a plurality of still images displayed on the display unit 2 at the same time, and correspond to a plurality of phases of the walking motion of the measurement subject 100, respectively. However, the plurality of human-type images H may be displayed on the display unit 2 at the same time, or may be sequentially displayed according to the order of walking as a slide show by switching the screen. For each touch operation of the display unit 2 of the tablet terminal 10 of the user, the display may be sequentially performed according to the order of walking.

  The pointing image I is an abnormal movement determined by the abnormal part determination unit 32 in the humanoid image corresponding to the phase determined to be abnormal by the abnormal phase determination unit 33 among the plurality of humanoid images H. Point out the determined body part. The indication image I is not limited to a circle as shown in FIG. 12, but may be another symbol such as an arrow, an index finger type image, or the like. In addition, the indication image I may be configured by an image of a body part having a color different from the color of the main part of the plurality of humanoid images. For example, an abnormal part may be pointed out by changing the color of only the abnormal part of the white humanoid image H to red.

  If it is determined by the abnormal part determination unit 32 that none of the body parts is moving abnormally, only the plurality of humanoid images H are displayed on the display unit 2 and the indication image I is not displayed. Thereby, the to-be-measured person 100 can confirm that any body part of the self is not performing an abnormal walking motion.

  According to the above configuration, it is possible to visually display which part is performing an abnormal movement in which phase. Therefore, the person to be measured 100 can intuitively understand how his / her walking motion is abnormal.

(Judgment result image X when using the moving image of the actual walking motion of the person being measured)
The walking analysis system 90 according to the present embodiment includes a moving image capturing unit 4, a moving image storage unit 36, and an image extraction unit 37. The moving image photographing unit 4 photographs the walking motion of the person 100 to be measured. The moving image storage unit 36 stores continuous images of the walking motion of the measurement subject 100 captured by the moving image capturing unit 4. The image extraction unit 37 extracts still images of a plurality of types of postures of the measurement subject 100 respectively corresponding to a plurality of phases from continuous images of the walking motion of the measurement subject 100 stored in the moving image storage unit 36. In this case, the plurality of humanoid images H are still images of a plurality of types of postures of the measurement subject 100 extracted by the image extraction unit 37, respectively.

  In the present embodiment, the plurality of phases are assumed to consist of six phases. That is, one walking cycle is divided into six phases, and still images of the postures of the measurement subject 100 in each of the six phases are extracted. However, the number of the plurality of phases may be any number as long as the measured person 100 can understand the gait abnormality.

For indication of abnormal physical site, there is a case where the movable distance Y _L and the movable distance Y _R described above is used. In this case, the movable distance Y _L and the movable distance Y _R still image in the attitude of the person to be measured 100 in a phase corresponding to the timing of the Lissajous curve data specified by the crotch or lap has been pointed out as abnormal body part The Moreover, because of the indication of abnormal body part, there is a case where the angle theta _L and the angle theta _R described above is used for the indication of abnormalities. In this case, the angle theta _L and the angle theta _R still image in the attitude of the person to be measured 100 in a phase corresponding to the timing of the Lissajous curve data specified by the waist or legs are pointed out as abnormal body sites. Note that the timing of the Lissajous curve data is the timing at which the time-series data of the position change locus for creating the Lissajous curve data is acquired.

  According to the above configuration, the person being measured 100 can intuitively recognize which part is performing an abnormal motion in any phase by looking at the postures of a plurality of phases in his / her walking motion. it can. Therefore, the person under measurement 100 can more easily correct his / her abnormal posture.

(Determination result image X when character image is used)
The walking analysis system 90 of the present embodiment may not include the moving image capturing unit 4, the moving image storage unit 36, and the image extracting unit 37. In that case, the walking analysis system 90 includes a character storage unit 38 that stores still images of a plurality of types of postures of characters respectively corresponding to a plurality of phases. In this case, the plurality of humanoid images H are still images of a plurality of types of postures of the character read from the character storage unit 38, respectively.

  In the present specification, the character includes a predetermined real person other than the person to be measured 100, a person drawn by an animation-like or painting-like drawing method, a diagram showing the outline of the person, and the like. In the present specification, the character means anything that can be recognized as having a posture in a human walking motion. In the present specification, the character may be any character as long as it can identify an abnormal phase and an abnormal part in the walking motion of the person 100 to be measured.

  In the present embodiment, since the plurality of phases are composed of six phases, still images of the postures of the respective characters in the six phases are extracted. However, any number of posture images of the character may be used as long as the measurement subject 100 can understand the abnormal walking.

For indication of abnormal physical site, there is a case where the movable distance Y _L and the movable distance Y _R described above is used. In this case, the still image of the character position in the phase corresponding to the timing of the Lissajous curve data specified by the movable distance Y _L and the movable distance Y _R, hip or knee is pointed out as abnormal body sites. Moreover, because of the indication of abnormal body part, there is a case where the angle theta _L and the angle theta _R described above is used for the indication of abnormalities. In this case, the still image of the character position in the phase corresponding to the timing of the Lissajous curve data specified by the angle theta _L and the angle theta _R, hips or feet are pointed out as abnormal body sites. Note that the timing of the Lissajous curve data is the timing at which the time-series data of the position change locus for creating the Lissajous curve data is acquired.

  According to this configuration, the person to be measured 100 can intuitively recognize which part is performing an abnormal motion in any phase by viewing images of a plurality of characters. Even when the walking analysis system 90 does not have the moving image photographing unit 4, the walking analysis can be performed.

(Determination of abnormality type and degree of abnormality)
As shown in FIG. 2, the control unit 3 includes a data creation unit 31, an abnormality type determination unit 34, and an abnormality degree determination unit 35.

  The abnormality type determination unit 34 compares the values of a plurality of types of elements to be extracted extracted from the Lissajous curve data created by the data creation unit 31 with predetermined types of determination reference values for the presence or absence of abnormality. Thereby, the abnormality type determination unit 34 determines whether or not each of a plurality of types of walking abnormalities determined in advance in the walking motion of the measurement subject 100 exists.

In the case of <1) an abnormal balance of shake between the left part and the right part of the body>, the first to-be-determined element is a distance Y _R , a distance Y _L , a distance X _f = X _L + X _R , and a value ( X _L -X _R ) / 2 (X _L + X _R ) × 100%. In the case of <2) an abnormality in the load balance between the left part and the right part of the body>, the second element to be determined is the area S _L and the area S _R. The third of the determination factors is the case of <3) abnormality in the movable area of the abnormalities and knee joints of the movable region of the hip>, the distance Y _R and the distance Y _L.

The determination factors of the fourth in the case of <4) abnormality of the back屈可dynamic range of ankle> a z-coordinate and x-coordinate of the inflection point IV _L or IV _R. In the case of <5) abnormality in hip rotation and ankle plantar flexion force>, the fifth judged element is the left angle θ _L and the right inflection point IV for the left inflection point VI _L. is a right of the angle θ _R for _R. The sixth determination element is the case of <7) abnormal foot kick> and the left angle φ _L and angle φ _R formed by the major axis of the approximate ellipse of the Lissajous curve data and the Y axis.

  However, the element to be determined and the type of abnormality are not limited to those described above. As long as it is possible to determine the presence / absence of walking abnormality using the determination target element extracted from the Lissajous curve data, other determination elements may be used and the presence / absence of other types of abnormality may be determined.

  The degree-of-abnormality determination unit 35 determines, for each type of walking abnormality determined by the abnormality type determination unit 34 that there is a walking abnormality, based on the difference between the value of the element to be determined and the determination reference value for the presence or absence of abnormality. Determine the degree. The extent of the difference between the value of the element to be judged and the judgment reference value for the presence or absence of abnormality is determined from the results of prior experiments for each type of abnormality. . Thereby, the determination reference value for determining the degree of abnormality is written in the gait analysis program for each type of abnormality.

  The display control unit 39 causes the display unit 2 to display the determination result image Y in which the type of walking abnormality determined by the abnormality type determination unit 34 and the degree of walking abnormality determined by the abnormality degree determination unit 35 are associated with each other.

(Judgment result image Y)
As shown in FIG. 2, the determination result image Y is displayed in the display area 22 of the display unit 2. Specifically, a determination result image as shown in FIG. 12 is displayed.

  The determination result image Y includes a plurality of types of character images A, B, C, D, E and a plurality of types of character images A, B, C, D, E that can recognize a plurality of types of walking abnormalities. And a chart image G capable of recognizing the degree of gait abnormality identified by each.

  In the present embodiment, the following seven items described above can be considered for the plurality of types of character images A, B, C, D, and E that can respectively recognize a plurality of types of walking abnormalities.

1) Abnormal swing balance between the left and right parts of the body 2) Abnormal load balance between the left and right parts of the body 3) Abnormalities in the movable area of the hip joint and abnormalities in the movable area of the knee joint 4) Feet Abnormalities in the range of dorsiflexion of the joint 5) Abnormalities in the rotation of the hips and abnormalities in the bottom flexion force of the ankle joints 7) Abnormalities in kicking the foot In the present embodiment, the above-mentioned seven types of walking Although an abnormality is illustrated, the presence or absence of other types of gait abnormalities may be determined.

  In FIG. 12, only a plurality of types of character images A, B, C, D, and E capable of recognizing a plurality of types of gait abnormalities are shown for easy understanding of the drawing. In the second display area 22, all of the above-described walking abnormalities are displayed. Therefore, the number of axes of the radar chart is not limited to five. The radar chart has a number of axes that are determined to be abnormal. If seven items are described in the radar chart, the radar chart needs to have a heptagon shape. However, from the viewpoint of making the drawings easier to see, the radar charts of FIGS. 2 and 12 have a regular pentagonal shape. The shape of the radar chart is not limited to a specific shape as long as a plurality of types of walking abnormalities can be specified. Further, any item may be displayed on the radar chart as long as it is a character image that can recognize a walking abnormality.

  In the present embodiment, the chart image G is a radar chart having a plurality of axes, and each of the plurality of axes corresponds to a plurality of types of walking abnormalities. However, the chart image G may be a bar graph or a line graph showing the type of abnormality and the degree of abnormality as long as the type of abnormality in walking and the degree of abnormality in walking can be recognized. In the present specification, the chart image includes a table indicating the degree of walking abnormality of each type of walking abnormality by a number, a color, or a symbol. The degree of abnormality may be indicated by numbers, colors, or symbols. For example, the chart image G may be an image in which a numerical value or a color indicating the type of abnormality and the degree of abnormality is written in a frame constituting the table.

  When the abnormality type determination unit 34 determines that there is no walking abnormality of any type in the walking movement, the display unit 2 displays the radar chart as the chart image G, and only one point is at the center point of the radar chart. Plotted. Thereby, the to-be-measured person 100 can confirm that there is no kind of walking abnormality in his / her walking motion.

(Extraction of abnormal posture)
The abnormal posture determination unit 301 compares each of a plurality of actual curvature radius values r extracted from the Lissajous curve data created by the data creation unit 31 with a determination reference value for the curvature radius. Accordingly, the abnormal posture determination unit 301 determines whether or not the measurement subject is in an abnormal posture depending on whether or not the actual value of the curvature radius r is smaller than the determination reference value of the curvature radius.

  In the present embodiment, as shown in FIGS. 10 and 11, when the radius of curvature of the Lissajous curve data on each of the horizontal plane and the arrow top is smaller than 1 mm, the measurement subject 100 takes an abnormal posture in the walking motion. It is determined that

  According to the above configuration, it is possible to determine the walking abnormality using the value of the curvature radius only on the surface where it is effective to determine the walking abnormality based on the value of the curvature radius.

  The abnormal posture extraction unit 302 acquires abnormal posture timing data based on which of the Lissajous curve data the actual curvature radius timing determined to be smaller than the determination reference value by the abnormal posture determination unit 301. To do. The actual timing of the radius of curvature in this case is the timing at which time-series data of the change in position serving as a basis for drawing a graph portion of the Lissajous curve data having a radius of curvature smaller than the criterion value is acquired. . The timing of the curvature radius smaller than the determination reference value corresponds to the timing when the actual person to be measured 100 takes an abnormal posture. The abnormal posture extraction unit 302 extracts a still image K having an abnormal posture corresponding to the data of the abnormal posture timing from the continuous images of the walking motion of the measurement subject 100 stored in the moving image storage unit 36. The display control unit 39 displays the abnormal posture still image K extracted by the abnormal posture extraction unit 302 in the display area 23 of the display unit 2 as the determination result image Z.

(Judgment result image Z)
As shown in FIG. 2 and FIG. 12, a still image K with an abnormal posture is displayed as the determination result image Z in the display area 23 of the display unit 2. Thereby, the to-be-measured person 100 can see a still image of his / her posture at an abnormal posture timing. Therefore, the person to be measured 100 can grasp the state of his / her abnormal gait very intuitively. According to said structure, the abnormality of a walking movement state can be determined by the presence or absence of the extreme change of a walking movement state. Therefore, it is possible to improve the accuracy of determining whether there is an abnormality.

  If the abnormal posture determination unit 301 determines that the measured person 100 is not in an abnormal posture at any timing, no image of any abnormal posture is displayed on the display unit 2. Thereby, it is possible to confirm that the measurement subject 100 is not in an abnormal posture at any timing of the walking motion.

(Determining whether there is an abnormality)
The abnormality presence / absence determination unit 300 includes an abnormal part determination unit 32, an abnormal phase determination unit 33, an abnormality type determination unit 34, an abnormality degree determination unit 35, an abnormal posture determination unit 301, and an abnormal posture extraction unit 302. The abnormality presence / absence determination unit 300 compares the values of a plurality of types of elements to be extracted extracted from the Lissajous curve data created by the data creation unit 31 with predetermined types of determination criteria values for the presence / absence of abnormality. Thereby, the abnormality presence / absence determination unit 300 determines the presence / absence of abnormality in the walking motion. The display control unit 39 displays, on the display unit 2, determination result images X and Y that can recognize an abnormal motion when the abnormality presence determination unit 300 determines that the person 100 to be measured is performing an abnormal walking motion. Display.

  In the present embodiment, as described above, the data creation unit 31 creates Lissajous curve data for each of the frontal plane, horizontal plane, and sagittal plane of the person 100 to be measured. Further, as can be seen from the above description of the determination direction, a plurality of predetermined determination criteria values for the presence or absence of abnormality are extracted from the Lissajous curve data of the frontal plane, the horizontal plane, and the sagittal plane, respectively. It corresponds to the type of element to be judged.

  According to said structure, in order to analyze the Lissajous curve data about walking motion of the to-be-measured person 100 in three surfaces consisting of a frontal plane, a horizontal plane, and a sagittal plane, the abnormality in walking motion is detected from various viewpoints. can do. Therefore, it becomes easy for the measurement subject 100 to intuitively understand how his / her walking motion is abnormal from various viewpoints.

  For example, according to the walking analysis system 90 as described above, the display unit 2 can display the determination result images X and Y. Each of the determination result images X and Y is an image capable of recognizing a gait abnormality corresponding to each of a plurality of types of determination target elements. The determination result images X and Y are an example of an image that can specify which body part is abnormal in walking and in which phase, and an image that can specify what kind of walking abnormality is to what extent, respectively. is there. In the walking analysis system 90, only one of the determination result images X and Y may be displayed on the display unit 2. Such determination result images X and Y can be displayed by determining a gait abnormality from various viewpoints by creating Lissajous curve data on the front face, horizontal plane, and sagittal plane. Because it can.

(Characteristic composition and effect)
Hereinafter, a characteristic configuration of the walking analysis system and the walking analysis program according to the embodiment and effects produced thereby will be described.

  (1) The walking analysis system 90 includes a sensor unit 1, a control unit 3, and a display unit 2. The sensor unit 1 acquires physical information that can specify a locus of a change in a predetermined position caused by the walking motion of the measurement subject 100. The control unit 3 determines the presence or absence of a walking abnormality in the walking motion based on the physical information acquired by the sensor unit 1. The display unit 2 displays a determination result image X capable of recognizing the presence or absence of a gait abnormality determined by the control unit 3.

  The control unit 3 includes a data creation unit 31, an abnormal part determination unit 32, an abnormal phase determination unit 33, and a display control unit 39. The data creation unit 31 acquires time-series data of the locus of the position change in the walking motion of the measurement subject 100 based on the physical information. The data creation unit 31 creates Lissajous curve data on a predetermined plane based on the time-series data of the locus of position change. The abnormal part determination unit 32 compares a plurality of types of determination element values extracted from the Lissajous curve data created by the data creation unit 31 with a plurality of types of determination criterion values for presence / absence of abnormality. Thereby, the abnormal part determination part 32 determines whether the body part is carrying out the abnormal exercise | movement for each of several predetermined body parts.

  The abnormal phase determination unit 33 determines which of a plurality of predetermined phases of the walking exercise the body part is performing abnormal exercise. This determination is based on which timing of the Lissajous curve data is determined when the abnormal part determination unit 32 determines that the body part is moving abnormally. The display control unit 39 determines that the body part determined to be performing abnormal exercise by the abnormal part determination unit 32 and the phase determined to be abnormal movement by the abnormal phase determination unit 33 are associated with each other. The result image X is displayed on the display unit 2.

  The determination result image X includes a plurality of humanoid images H and indication images I. The plurality of humanoid images H are a plurality of still images displayed on the display unit 2, and correspond to a plurality of phases of the walking motion of the measurement subject 100, respectively. The pointing image I is an abnormal movement determined by the abnormal part determination unit 32 in the humanoid image corresponding to the phase determined to be abnormal by the abnormal phase determination unit 33 among the plurality of humanoid images H. Point out the determined body part.

  According to the above configuration, it is possible to visually display what abnormal walking movement is being performed. Therefore, the person to be measured 100 can intuitively understand how his / her walking motion is abnormal.

  (2) It is preferable that the walking analysis system 90 further includes the moving image capturing unit 4, and the control unit 3 includes the moving image storage unit 36 and the image extraction unit 37. The moving image photographing unit 4 photographs the walking motion of the person 100 to be measured. The moving image storage unit 36 stores continuous images of the walking motion of the measurement subject 100 captured by the moving image capturing unit 4. The image extraction unit 37 extracts still images of a plurality of types of postures of the measurement subject 100 respectively corresponding to a plurality of phases from continuous images of the walking motion of the measurement subject 100 stored in the moving image storage unit 36. In this case, it is preferable that the plurality of human-type images H are still images of a plurality of types of postures of the measurement subject 100 extracted by the image extraction unit 37, respectively.

  According to the above configuration, the person being measured 100 can intuitively recognize which part is performing an abnormal motion in any phase by looking at the postures of a plurality of phases in his / her walking motion. it can. Therefore, the person under measurement 100 can more easily correct his / her abnormal posture.

  (3) The walking analysis system 90 may include a character storage unit 38 that stores still images of a plurality of types of postures of characters corresponding to a plurality of phases, respectively. The plurality of humanoid images H may be still images of a plurality of types of postures of the character read from the character storage unit 38, respectively.

  According to said structure, the to-be-measured person 100 can recognize intuitively what part is performing the abnormal exercise | movement in what phase by seeing the image of a some character. Even when the walking analysis system 90 does not have the moving image photographing unit 4, the walking analysis can be performed.

  (4) The walking analysis system 90 includes a sensor unit 1, a control unit 3, and a display unit 2. The sensor unit 1 acquires physical information that can specify a locus of a change in a predetermined position caused by the walking motion of the measurement subject 100. The control unit 3 determines the presence or absence of a walking abnormality in the walking motion based on the physical information acquired by the sensor unit 1. The display unit 2 displays a determination result image Y capable of recognizing the presence or absence of a gait abnormality determined by the control unit 3.

  The control unit 3 includes a data creation unit 31, an abnormality type determination unit 34, and an abnormality degree determination unit 35. The data creation unit 31 acquires time-series data of the locus of the position change in the walking motion of the measurement subject 100 based on the physical information. The data creation unit 31 creates Lissajous curve data on a predetermined plane based on the time-series data of the locus of position change.

  The abnormality type determination unit 34 compares the values of a plurality of types of elements to be extracted extracted from the Lissajous curve data created by the data creation unit 31 with predetermined types of determination reference values for the presence or absence of abnormality. Thereby, the abnormality type determination unit 34 determines whether or not each of a plurality of types of walking abnormalities determined in advance in the walking motion of the measurement subject 100 exists.

  The degree-of-abnormality determination unit 35 determines, for each type of walking abnormality determined by the abnormality type determination unit 34 that there is a walking abnormality, based on the difference between the value of the element to be determined and the determination reference value for the presence or absence of abnormality. Determine the degree.

  The display control unit 39 causes the display unit 2 to display the determination result image Y in which the type of walking abnormality determined by the abnormality type determination unit 34 and the degree of walking abnormality determined by the abnormality degree determination unit 35 are associated with each other.

  The determination result image Y includes a plurality of types of character images A, B, C, D, E and a plurality of types of character images A, B, C, D, E that can recognize a plurality of types of walking abnormalities. And a chart image G capable of recognizing the degree of gait abnormality identified by each.

  According to the above configuration, it is possible to visually display what kind of abnormal walking movement is being performed. Therefore, the person to be measured 100 can intuitively understand how his / her walking motion is abnormal.

  (5) The chart image G is a radar chart having a plurality of axes, and each of the plurality of axes may correspond to a plurality of types of walking abnormalities. The chart image may be a bar graph or a line graph. In the present specification, the chart image includes a table indicating the degree of walking abnormality of each type of walking abnormality by a number or a color.

  (6) The walking analysis system 90 includes a sensor unit 1, a control unit 3, a display unit 2, and a moving image shooting unit 4. The sensor unit 1 acquires physical information that can specify a locus of a change in a predetermined position caused by the walking motion of the measurement subject 100. The control unit 3 determines the presence or absence of a walking abnormality in the walking motion based on the physical information acquired by the sensor unit 1. The display unit 2 displays a determination result image Z capable of recognizing the presence or absence of a gait abnormality determined by the control unit 3. The moving image photographing unit 4 photographs the walking motion of the person 100 to be measured.

  The control unit 3 includes a data creation unit 31, a moving image storage unit 36, an abnormal posture determination unit 301, an abnormal posture extraction unit 302, and a display control unit 39.

  The data creation unit 31 acquires time-series data of a locus of a change in position in the walking motion of the measurement subject 100 based on the physical information. The data creation unit 31 creates Lissajous curve data on a predetermined plane based on the time-series data of the locus of position change. The moving image storage unit 36 stores continuous images of the walking motion of the measurement subject 100 captured by the moving image capturing unit 4.

  The abnormal posture determination unit 301 compares each of a plurality of actual curvature radius values extracted from the Lissajous curve data created by the data creation unit 31 with a judgment reference value for the curvature radius. Thereby, the abnormal posture determination unit 301 determines whether or not the measurement subject is in an abnormal posture depending on whether or not the actual value of the curvature radius is smaller than the determination reference value of the curvature radius.

  The abnormal posture extraction unit 302 acquires abnormal posture timing data based on which of the Lissajous curve data the actual curvature radius timing determined to be smaller than the determination reference value by the abnormal posture determination unit 301. To do. Thereby, the abnormal posture extraction unit 302 extracts a still image K of the abnormal posture corresponding to the data of the abnormal posture timing from the continuous image of the walking motion of the measurement subject 100 stored in the moving image storage unit 36. The display control unit 39 causes the display unit 2 to display the still image K of the abnormal posture extracted by the abnormal posture extraction unit 302 as the determination result image Z.

  According to the above configuration, it is possible to visually display what kind of abnormal walking movement is being performed. Therefore, the person to be measured 100 can intuitively understand how his / her walking motion is abnormal.

  (7) It is preferable that the data creation unit 31 creates the Lissajous curve data of at least one of the horizontal plane and the sagittal plane. In this case, it is preferable that the plurality of actual radii of curvature are extracted from the Lissajous curve data of at least one of the horizontal plane and the sagittal plane.

  Generally, the Lissajous curve data of the front face value inherently has a portion with a small radius of curvature, and thus is not suitable for using the curvature radius of the Lissajous curve data of the front face value as an element to be determined. On the other hand, since the Lissajous curve data of the horizontal plane and the sagittal plane does not inherently have a portion with a small curvature radius, the curvature radius of the Lissajous curve data of the horizontal plane and the sagittal plane can be used as a determination target element. Therefore, according to the above configuration, it is possible to determine the presence / absence of a gait abnormality using the value of the curvature radius only for the Lissajous curve data of the surface where it is effective to determine the gait abnormality by the value of the curvature radius.

  (8) The walking analysis system 90 includes a sensor unit 1, a control unit 3, and a display unit 2. The sensor unit 1 acquires physical information that can specify a locus of a change in a predetermined position caused by the walking motion of the measurement subject 100. The control unit 3 determines the presence or absence of a walking abnormality in the walking motion based on the physical information acquired by the sensor unit 1. The display unit 2 displays determination result images X, Y, and Z that can recognize the presence / absence of a gait abnormality determined by the control unit 3.

  The control unit 3 includes a data creation unit 31, an abnormality presence / absence determination unit 300 (32, 33, 34, 35, 301, 302), and a display control unit 39. The data creation unit 31 acquires time-series data of the locus of the position change in the walking motion of the measurement subject 100 based on the physical information. The data creation unit 31 creates Lissajous curve data on a predetermined plane based on the time-series data of the locus of position change.

  The abnormality presence / absence determination unit 300 compares the values of a plurality of types of elements to be extracted extracted from the Lissajous curve data created by the data creation unit 31 with predetermined types of determination criteria values for the presence / absence of abnormality. Thereby, the abnormality presence / absence determination unit 300 determines the presence / absence of abnormality in the walking motion.

  The display control unit 39 displays, on the display unit 2, determination result images X and Z that can recognize the abnormal movement when the abnormality presence / absence determination unit 300 determines that the person 100 to be measured is performing an abnormal walking movement. Display.

  The data creation unit 31 creates Lissajous curve data for each of the forehead, horizontal, and sagittal planes of the person 100 to be measured. In this case, the plurality of types of determination criteria for the presence / absence of abnormality respectively correspond to a plurality of types of determination target elements extracted from the Lissajous curve data of the frontal plane, the horizontal plane, and the sagittal plane, respectively. . The determination result images X and Y include images capable of recognizing a gait abnormality corresponding to each of a plurality of types of determination target elements.

  According to said structure, in order to analyze the Lissajous curve data about walking motion of the to-be-measured person 100 in three surfaces consisting of a frontal plane, a horizontal plane, and a sagittal plane, the abnormality in walking motion is detected from various viewpoints. can do. Therefore, it becomes easy for the measurement subject 100 to intuitively understand how his / her walking motion is abnormal from various viewpoints.

  (9) The determination result images X and Y are at least an image that can specify what body part is abnormal in walking and in what phase, and an image that can specify what kind of abnormal walking is what level. It is preferable that either one is included.

  According to this, the person under measurement 100 can intuitively understand how his / her walking motion is abnormal.

  (10) The gait analysis program is used in the gait analysis system 90 including the sensor unit 1, the control unit 3, and the display unit 2. The gait analysis program causes the computer as the control unit 3 to function as the data creation unit 31, the abnormal site determination unit 32, the abnormal phase determination unit, and the display control unit 39.

  (11) The gait analysis program is used in the gait analysis system 90 including the sensor unit 1, the control unit 3, and the display unit 2. The gait analysis program causes the computer serving as the control unit 3 to function as the data creation unit 31, the abnormality type determination unit 34, the abnormality degree determination unit 35, and the display control unit 39.

  (12) The walking analysis program is used in the walking analysis system 90 including the sensor unit 1, the control unit 3, the display unit 2, and the moving image shooting unit 4. The gait analysis program causes the computer as the control unit 3 to function as the data creation unit 31, the moving image storage unit 36, the abnormal posture determination unit 301, the abnormal posture extraction unit 302, and the display control unit 39 based on physical information.

  (13) The gait analysis program is used in the gait analysis system 90 including the sensor unit 1, the control unit 3, and the display unit 2. The gait analysis program causes the computer as the control unit 3 to function as the data creation unit 31, the abnormality presence / absence determination unit 300 (32, 33, 34, 35, 301, 302, 39), and the display control unit 39.

DESCRIPTION OF SYMBOLS 1 Sensor part 2 Display part 3 Control part 4 Movie imaging part 31 Data preparation part 32 Abnormal part determination part 33 Abnormal phase determination part 34 Abnormality type determination part 35 Abnormality degree determination part 36 Movie storage part 37 Image extraction part 38 Character storage part 39 Display control unit 50 Recording medium 90 Gait analysis system 100 Person to be measured 300 Abnormality presence / absence determination unit 301 Abnormal posture determination unit 302 Abnormal posture extraction unit A, B, C, D, E Character image X Determination result image Y Determination result image H Type image I Pointed image G Chart image

Claims (13)

A sensor unit for acquiring physical information capable of specifying a trajectory of a change in a predetermined position caused by a walking motion of the measurement subject;
A control unit for determining the presence or absence of a walking abnormality in the walking movement based on the physical information acquired by the sensor unit;
A display unit that displays a determination result image capable of recognizing the presence or absence of the walking abnormality determined by the control unit,
The controller is
Data creation for acquiring time-series data of a locus of position change in the walking movement of the measurement subject based on the physical information and creating Lissajous curve data in a predetermined plane based on the time-series data of the locus of position change And
A plurality of types of judged element values extracted from the Lissajous curve data created by the data creation unit are respectively compared with a plurality of types of judgment criteria values for presence / absence of a predetermined abnormality. For each of a plurality of body parts, an abnormal part determination unit that determines whether or not the body part is performing an abnormal movement;
Based on which timing of the Lissajous curve data the timing at which the body part is determined to be in an abnormal motion by the abnormal part determination unit, a plurality of predetermined phases of the walking motion are determined. An abnormal phase determination unit for determining in which the body part is performing an abnormal exercise;
The determination result image in which the body part determined to be performing abnormal exercise by the abnormal part determination unit and the phase determined to be abnormal movement by the abnormal phase determination unit are associated with each other. A display control unit for displaying on the display unit,
The determination result image is
A plurality of still images displayed on the display unit, and a plurality of human-type images respectively corresponding to the plurality of phases of the walking motion of the measurement subject;
In the person image corresponding to the abnormality phase determination unit said phase is determined to be an abnormal motion by one of the plurality of person image and has an abnormal motion by the abnormal condition part determination unit A gait analysis system including an indication image indicating the determined body part. It further includes a moving image photographing unit for photographing the walking movement of the measurement subject,
The controller is
A moving image storage unit that stores a continuous image of the walking motion of the measurement subject imaged by the moving image capturing unit;
An image extraction unit that extracts still images of a plurality of types of postures of the measurement subject respectively corresponding to the plurality of phases from continuous images of the walking motion of the measurement subject stored in the moving image storage unit;
The gait analysis system according to claim 1, wherein each of the plurality of human-type images is a still image of a plurality of types of postures of the measurement subject extracted by the image extraction unit. A character storage unit that stores still images of a plurality of types of postures of the character respectively corresponding to the plurality of phases;
The walking analysis system according to claim 1, wherein each of the plurality of humanoid images is a still image of a plurality of types of postures of the character read from the character storage unit. A sensor unit for acquiring physical information capable of specifying a trajectory of a change in a predetermined position caused by a walking motion of the measurement subject;
A control unit for determining the presence or absence of a walking abnormality in the walking movement based on the physical information acquired by the sensor unit;
A display unit that displays a determination result image capable of recognizing the presence or absence of the gait abnormality determined by the control unit;
A video shooting unit for shooting the walking movement of the measurement subject,
The controller is
Data creation for acquiring time-series data of a locus of position change in the walking movement of the measurement subject based on the physical information and creating Lissajous curve data in a predetermined plane based on the time-series data of the locus of position change And
A plurality of types of determination element values extracted from the Lissajous curve data generated by the data generation unit are respectively compared with a plurality of types of determination criteria values for presence / absence of abnormalities, whereby the measurement target An abnormality type determination unit for determining whether or not there are each of a plurality of types of walking abnormalities determined in advance in a person's walking movement;
For each type of gait abnormality determined by the abnormality type determination unit to have the gait abnormality, the degree of the gait abnormality is determined based on the difference between the value of the element to be determined and the determination reference value for the presence or absence of the abnormality. An abnormality degree determination unit for determining;
A display control unit that causes the display unit to display the determination result image in which the type of the gait abnormality determined by the abnormality type determination unit and the degree of the gait abnormality determined by the abnormality degree determination unit are associated with each other; With
The determination result image is
A humanoid image extracted from the video shot in the video shooting unit;
A plurality of types of character images each capable of recognizing the plurality of types of walking abnormalities;
A gait analysis system comprising: a chart image capable of recognizing the degree of the gait abnormality identified by each of the plurality of types of character images. The chart image is a radar chart having a plurality of axes;
The gait analysis system according to claim 4, wherein each of the plurality of axes corresponds to the plurality of types of gait abnormalities. A sensor unit for acquiring physical information capable of specifying a trajectory of a change in a predetermined position caused by a walking motion of the measurement subject;
A control unit for determining the presence or absence of a walking abnormality in the walking movement based on the physical information acquired by the sensor unit;
A display unit that displays a determination result image capable of recognizing the presence or absence of the gait abnormality determined by the control unit;
A video shooting unit for shooting the walking movement of the measurement subject,
The controller is
Data for acquiring time-series data of the position change trajectory in the walking movement of the measurement subject based on the physical information, and creating Lissajous curve data in a predetermined plane based on the time-series data of the position change trajectory The creation department;
A moving image storage unit that stores a continuous image of the walking motion of the measurement subject imaged by the moving image capturing unit;
Each of a plurality of actual curvature radius values extracted from the Lissajous curve data created by the data creation unit is compared with a criterion value of curvature radius, whereby the actual curvature radius value is An abnormal posture determination unit that determines whether or not the measured person is in an abnormal posture depending on whether or not it is smaller than a criterion value of curvature radius;
Abnormal posture timing data is acquired based on which timing of the actual Lissajous curve data the actual curvature radius determined to be smaller than the determination reference value by the abnormal posture determination unit, thereby An abnormal posture extraction unit that extracts a still image of an abnormal posture corresponding to the data of the abnormal posture timing from a continuous image of the walking motion of the measurement subject stored in the moving image storage unit;
And a display control unit that causes the display unit to display a still image of the abnormal posture extracted by the abnormal posture extraction unit as the determination result image. The data creation unit creates the Lissajous curve data of at least one of a horizontal plane and a sagittal plane,
The gait analysis system according to claim 6, wherein the plurality of actual radii of curvature are extracted from the Lissajous curve data of at least one of the horizontal plane and the sagittal plane. A sensor unit for acquiring physical information capable of specifying a trajectory of a change in a predetermined position caused by a walking motion of the measurement subject;
A control unit for determining the presence or absence of a walking abnormality in the walking movement based on the physical information acquired by the sensor unit;
A display unit that displays a determination result image capable of recognizing the presence or absence of the walking abnormality determined by the control unit,
The controller is
Data for acquiring time-series data of the position change trajectory in the walking movement of the measurement subject based on the physical information, and creating Lissajous curve data in a predetermined plane based on the time-series data of the position change trajectory The creation department;
A plurality of types of determination element values extracted from the Lissajous curve data generated by the data generation unit are respectively compared with a plurality of predetermined determination criteria values for the presence / absence of abnormality, whereby the walking motion An abnormality presence / absence determination unit for determining the presence / absence of an abnormality in
A display control unit that causes the display unit to display a determination result image capable of recognizing the abnormal walking motion when the abnormality determination unit determines that the measured person is performing an abnormal walking motion; With
The data creation unit creates the Lissajous curve data for each of the forehead surface, the horizontal plane, and the sagittal plane of the measurement subject,
The predetermined plural kinds of abnormality determination reference values correspond to the plural kinds of judged elements extracted from the Lissajous curve data of the frontal plane, the horizontal plane, and the sagittal plane, respectively. And
The gait analysis system, wherein the determination result image includes an image capable of recognizing a gait abnormality corresponding to each determined element of the plurality of types of determined elements.   The determination result image includes at least one of an image capable of specifying which body part is abnormal in walking and in what phase, and an image capable of specifying what type of abnormal walking is what level. The gait analysis system according to claim 8. A sensor unit for acquiring physical information capable of specifying a trajectory of a change in a predetermined position caused by a walking motion of the measurement subject;
A control unit for determining the presence or absence of a walking abnormality in the walking movement based on the physical information acquired by the sensor unit;
A display unit that displays a determination result image capable of recognizing the presence or absence of the gait abnormality determined by the control unit, and a gait analysis program used in a gait analysis system comprising:
A computer as the control unit,
Data for acquiring time-series data of the position change trajectory in the walking movement of the measurement subject based on the physical information, and creating Lissajous curve data in a predetermined plane based on the time-series data of the position change trajectory Creation department,
A plurality of types of judged element values extracted from the Lissajous curve data created by the data creation unit are respectively compared with a plurality of types of judgment criteria values for presence / absence of a predetermined abnormality. An abnormal part determination unit that determines whether or not the body part is performing an abnormal exercise for each of the plurality of body parts;
Based on which timing of the Lissajous curve data the timing at which the body part is determined to be in an abnormal motion by the abnormal part determination unit, a plurality of predetermined phases of the walking motion are determined. An abnormal phase determination unit for determining in which the body part is performing an abnormal movement; and
The determination result image in which the body part determined to be performing abnormal exercise by the abnormal part determination unit and the phase determined to be abnormal movement by the abnormal phase determination unit are associated with each other. Function as a display control unit to be displayed on the display unit,
The determination result image is
A plurality of still images displayed on the display unit, and a plurality of human-type images respectively corresponding to the plurality of phases of the walking motion of the measurement subject;
In the person image corresponding to the abnormality phase determination unit said phase is determined to be an abnormal motion by one of the plurality of person image and has an abnormal motion by the abnormal condition part determination unit A gait analysis program including an indication image indicating the determined body part. A sensor unit for acquiring physical information capable of specifying a trajectory of a change in a predetermined position caused by a walking motion of the measurement subject;
A control unit for determining the presence or absence of a walking abnormality in the walking movement based on the physical information acquired by the sensor unit;
A display unit that displays a determination result image capable of recognizing the presence or absence of the gait abnormality determined by the control unit;
A gait analysis program used in a gait analysis system provided with a video shooting unit that shoots the walking movement of the measurement subject ,
A computer as the control unit,
Data for acquiring time-series data of the position change trajectory in the walking movement of the measurement subject based on the physical information, and creating Lissajous curve data in a predetermined plane based on the time-series data of the position change trajectory Creation department,
A plurality of types of determination element values extracted from the Lissajous curve data generated by the data generation unit are respectively compared with a plurality of types of determination criteria values for presence / absence of abnormalities, whereby the measurement target An abnormal type determination unit that determines whether or not there are a plurality of types of predetermined walking abnormalities in the walking movement of the person,
For each type of gait abnormality determined by the abnormality type determination unit to have the gait abnormality, the degree of the gait abnormality is determined based on the difference between the value of the element to be determined and the determination reference value for the presence or absence of the abnormality. An abnormality degree determination unit for determining, and
As a display control unit that displays the determination result image in which the type of the gait abnormality determined by the abnormality type determination unit and the degree of the gait abnormality determined by the abnormality level determination unit are associated with each other on the display unit Make it work
The determination result image is
A humanoid image extracted from the video shot in the video shooting unit;
A plurality of types of character images each capable of recognizing the plurality of types of walking abnormalities;
A gait analysis program comprising: a chart image capable of recognizing the degree of gait abnormality identified by each of the plurality of types of character images. A sensor unit for acquiring physical information capable of specifying a trajectory of a change in a predetermined position caused by a walking motion of the measurement subject;
A control unit for determining the presence or absence of a walking abnormality in the walking movement based on the physical information acquired by the sensor unit;
A display unit that displays a determination result image capable of recognizing the presence or absence of the gait abnormality determined by the control unit;
A gait analysis program used in a gait analysis system provided with a video shooting unit that shoots the walking movement of the measurement subject,
A computer as the control unit,
Data for acquiring time-series data of the position change trajectory in the walking movement of the measurement subject based on the physical information, and creating Lissajous curve data in a predetermined plane based on the time-series data of the position change trajectory Creation department,
A moving image storage unit for storing a continuous image of the walking movement of the measurement subject imaged by the moving image capturing unit;
Each of a plurality of actual curvature radius values extracted from the Lissajous curve data created by the data creation unit is compared with a criterion value of curvature radius, whereby the actual curvature radius value is An abnormal posture determination unit that determines whether or not the measurement subject is in an abnormal posture depending on whether or not it is smaller than a determination reference value of a curvature radius;
Abnormal posture timing data is acquired based on which timing of the actual Lissajous curve data the actual curvature radius determined to be smaller than the determination reference value by the abnormal posture determination unit, thereby An abnormal posture extraction unit that extracts a still image of an abnormal posture corresponding to the data of the abnormal posture timing from a continuous image of the walking motion of the measurement subject stored in the moving image storage unit; and
A gait analysis program that causes a display control unit to display a still image of the abnormal posture extracted by the abnormal posture extraction unit on the display unit as the determination result image. A sensor unit for acquiring physical information capable of specifying a trajectory of a change in a predetermined position caused by a walking motion of the measurement subject;
A control unit for determining the presence or absence of a walking abnormality in the walking movement based on the physical information acquired by the sensor unit;
A display unit displaying a determination result image capable of recognizing the presence or absence of the walking abnormality determined by the control unit, and a program used in a walking analysis system comprising:
A computer as the control unit,
Data for acquiring time-series data of the position change trajectory in the walking movement of the measurement subject based on the physical information, and creating Lissajous curve data in a predetermined plane based on the time-series data of the position change trajectory Creation department,
A plurality of types of determination element values extracted from the Lissajous curve data generated by the data generation unit are respectively compared with a plurality of predetermined determination criteria values for the presence / absence of abnormality, whereby the walking motion An abnormality presence / absence determination unit for determining the presence / absence of abnormality in
A display control unit that causes the display unit to display a determination result image capable of recognizing the abnormal walking motion when the abnormality determination unit determines that the measured person is performing an abnormal walking motion; Function as
The data creation unit creates the Lissajous curve data for each of the forehead surface, the horizontal plane, and the sagittal plane of the measurement subject,
The predetermined plural kinds of abnormality determination reference values correspond to the plural kinds of judged elements extracted from the Lissajous curve data of the frontal plane, the horizontal plane, and the sagittal plane, respectively. And
The determination result image is a walking analysis program including an image capable of recognizing a gait abnormality corresponding to each determined element of the plurality of types of determined elements.