WO2005096939A1

WO2005096939A1 - Rehabilitation assisting measurement system and rehabilitation assisting measurement method

Info

Publication number: WO2005096939A1
Application number: PCT/JP2005/006378
Authority: WO
Inventors: Yasushi Chida; Yasuhiro Okada
Original assignee: The New Industry Research Organization
Priority date: 2004-04-07
Filing date: 2005-03-31
Publication date: 2005-10-20
Also published as: JPWO2005096939A1

Abstract

The movements of the left and right acrominons, left and right iliac spines, and head of a patient of hip osteoarthritis in the image captured by a DV camera are acquired. According to the acquired movement data, an image showing the movements of the trunk axis which is the line connecting the left and right acrominons of the patient, the anterior pelvic axis which is the line connecting the left and right anterior superior iliac spines, the posterior pelvic axis which is the line connecting the left and right posterior superior iliac spines, and the head is edited. The edited image is displayed on a display. Thus, the features of when the walk of the patient of hip osteoarthritis is recognized as movements are shown to the patient easily understandably.

Description

Specification

Rehabilitation support measurement system and rehabilitation support measurement method

Technical field

The present invention relates to a rehabilitation support measurement system for improving rehabilitation efficiency and a measurement method therefor.

Background art

[0002] Conventionally, hip osteoarthritis (hereinafter referred to as hip OAfosteoarthrosis) ゃ) Hemiplegic patients often have gait disorders. Conventional methods of analyzing the way of walking these patients include analyzing fragmentary data such as the maximum value of the pelvic rotation angle and the maximum value of lateral displacement of the acromion during walking of the patient by comparing them with the data of the elderly etc. There was a way to do that.

[0003] However, in the conventional analysis method of the patient's gait as described above, since the patient's gait is not analyzed as a motion, the characteristics of the patient's gait are accurately grasped and the characteristics are obtained. It is difficult to show to the patient easily. For this reason, there has been a problem that the patient cannot accurately recognize his / her way of walking and perform efficient rehabilitation (hereinafter abbreviated as rehabilitation).

[0004] Here, the reason why the conventional method of analyzing a patient's gait cannot accurately capture the characteristics of the patient's gait will be described in detail. First, the case of a patient with a crotch A will be described. In recent years, it has been said that it is important to treat joints not only as mechanical organs but also as information organs, and it is important for patients with joint disease to reduce joint function. It is thought that the patient's exercise program was abnormal and that the patient's gait was abnormal. In other words, gait disorders in persons with joint disease have abnormalities in the interrelationships between body parts, and even in hip OA patients who are more likely to develop symptoms, a decrease in hip joint function may occur in the adjacent trunk and pelvis. It is considered that this has a large effect and makes it impossible to respond to the movement of the hip joint in a finely tuned manner. Therefore, in order to accurately grasp the characteristics of the way of walking of the hip OA patient, it is necessary to analyze the way of walking as a movement, paying attention to the interrelation of each part of the body. However, according to the conventional analysis method of the walking style of the hip OA patient, the maximum value of the pelvic rotation angle and the like during walking of the hip OA patient are not known. The analysis of the walking style of the hip 〇A patient using only the fragmentary data did not allow the gait to be evaluated as a series of movements.

[0005] In the case of hemiplegic patients, hemiplegia is a functional disorder based on the loss of cells on one side of the brain due to a stroke. There is a need to.

[0006] As a rehabilitation measuring device, a device for calculating the ratio of the amplitudes of the inflection points included in the waveform of the acceleration pulse wave of the subject and evaluating the motion of the subject before and after the exercise is used. However, this problem cannot be solved by the present invention (see, for example, JP-A-9-135819).

Disclosure of the invention

[0007] The present invention has been made to solve the above-described problem, and it is an object of the present invention to easily show a characteristic of a patient with osteoarthritis or hemiplegia when a person's way of walking is regarded as a motion. To provide a rehabilitation support measurement system and a measurement method that enable a patient to accurately recognize his or her own walking style and perform efficient rehabilitation (hereinafter abbreviated as rehabilitation). Aim.

[0008] In order to achieve the above object, the rehabilitation support measurement system according to the aspect of claim 1 of the present invention improves the efficiency of rehabilitation (hereinafter abbreviated as "rehabilitation") for patients with osteoarthritis or hemiplegia. In a rehabilitation support measurement system for causing the patient to walk, imaging means for imaging a way of walking of the patient, motion capture means for capturing movement of each part of the body of the patient in an image captured by the imaging means, An image editing means for editing an image indicating movement of each part of the patient's body captured by the motion capture means, and a display means for displaying the image edited by the image editing means.

[0009] In the above configuration, the captured image indicating the movement of each part of the patient's body can be edited, and the edited image can be displayed on the display means. This enables patients with hip osteoarthritis or hemiplegia to easily show the characteristics of their own way of walking as movements, so that the patient can accurately recognize his or her own way of walking and improve efficiency. Rehabilitation (hereinafter abbreviated as rehabilitation). Therefore, the rehabilitation of the patient can be hastened. At the same time, medical costs required for patient treatment can be reduced. In addition, as described above, doctors, physiotherapists, and patients confirm images that show the characteristics of the patient's way of walking as movements easily, so that the patient's rehabilitation progress can be objectively determined. Can be evaluated.

[0010] Further, the rehabilitation support measurement system according to the aspect of claim 2 of the present invention is a rehabilitation support measurement system for improving the efficiency of rehabilitation of a patient with osteoarthritis of the hip. Image capturing means for capturing an image of the patient, and motion capturing means for capturing the movement of the left and right acromion and the right and left iliac spine or / and the head of the patient in the image captured by the image capturing means. A line connecting the left and right acromion of the patient based on the movement of the left and right acromion of the patient and the movement of the left and right iliac spines and / or the head movement captured by the motion capture means. Image editing means for editing an image showing movement of a certain trunk axis and movement of the pelvis axis, which is a line connecting the left and right iliac spines, and / or movement of the head, and an image edited by the image editing means Display means for displaying That.

[0011] In the above configuration, based on the captured movement of the left and right acromion of the patient and the movement of the left and right iliac spines, and / or the movement of the head, the line connects the left and right acromion of the patient. The edited image can be displayed by editing the image showing the movement of the trunk axis and the movement of the pelvic axis, which is a line connecting the left and right iliac spines, and / or the movement of the head. Here, walking in patients with hip osteoarthritis often involves abnormal movement of the pelvis and trunk, and as described above, the movement of the patient's trunk axis and pelvic axis, and / or the head By displaying an image showing the movement of the subject, it is possible to easily show the characteristics of the patient with hip osteoarthritis when the user's way of walking is regarded as a movement. This enables patients with hip osteoarthritis to accurately recognize their own walking styles and perform efficient rehabilitation, thereby speeding up the rehabilitation of patients with hip osteoarthritis and improving The medical costs required to treat patients with the disease can be reduced. In addition, as described above, doctors, physiotherapists, and patients can confirm images that clearly show the characteristics of walking of a patient with osteoarthritis as a movement, and the progress of the patient's rehabilitation can be confirmed. Can be evaluated objectively.

[0012] The measurement system for rehabilitation support according to the aspect of claim 4 of the present invention is a measurement system for rehabilitation support for improving the efficiency of rehabilitation of a patient with osteoarthritis of the hip. Imaging means for imaging the way of walking of the patient, and motion capture means for capturing the movement of the left and right acromion and the movement of the left and right iliac spines of the patient in the image captured by the imaging means. Based on the motion of the left and right acromion of the patient captured by the motion capture means and the movement of the left and right iliac spines, a line connecting the left and right acromion of the patient is obtained. The apparatus includes a chart editing means for editing a chart such as a duraf showing a correlation with the movement of the pelvis axis, which is a line connecting the spines, and a display means for displaying the chart edited by the chart editing means.

[0013] In the above configuration, the movement of the torso axis, which is a line connecting the left and right acromion of the patient, and the left and right movements based on the captured movement of the left and right acromion of the patient and the movement of the left and right iliac spines. The edited chart can be displayed by editing a chart such as a graph showing the correlation with the movement of the pelvic axis, which is a line connecting the iliac spines. Here, walking of patients with hip osteoarthritis often involves abnormal movement of the pelvis and trunk, and as described above, the correlation between the movement of the patient's trunk axis and the movement of the pelvis axis is determined. By displaying a chart such as a graph representing the characteristics, it is possible to easily show the characteristics of the patient with hip osteoarthritis when he / she walks as a motion. Thus, in addition to the effects described in claims 2 and 13, the progress of the patient's rehabilitation can be visually and objectively confirmed by the physician, the physiotherapist, and the patient confirming the chart such as the graph. Can be evaluated.

[0014] The measurement system for rehabilitation support according to an aspect of claim 8 of the present invention is the measurement system for rehabilitation support for improving the efficiency of rehabilitation of a patient with hip osteoarthritis. Image capturing means for capturing an image of the patient, and motion capturing means for capturing the movement of the left and right acromion and the right and left iliac spine or / and the head of the patient in the image captured by the image capturing means. Based on the motion of the left and right acromion of the patient and the motion of the left and right iliac spines, and / or the motion of the head captured by the motion capture means, the patient can walk in a healthy person. Determining means for determining whether or not it is different from the way of walking.

[0015] Further, the rehabilitation support measurement system according to an aspect of the ninth aspect of the present invention is the rehabilitation support measurement system for improving the efficiency of rehabilitation of a hemiplegic patient, wherein the patient's walking style is imaged. Imaging means, and the Motion capture means for capturing the vertical movement of each part of the body including the patient's head, and vertical movement of each part of the body including the patient's head captured by the motion capture means. The image processing apparatus includes image editing means for editing an image, and display means for displaying the image edited by the image editing means.

[0016] In the above configuration, it is possible to display an image indicating the vertical movement of each part of the body including the captured patient's head. Here, the degree of rehabilitation of a hemiplegic patient is determined by seeing whether the vertical movement of the patient's head and the vertical movement of each part other than the head are force-synchronized. By displaying images showing the vertical movement of each part of the body, including the patient's head, as described above, doctors, physiotherapists, and patients can help patients with hemiplegia. Rehabilitation progress can be determined. In addition, the image showing the vertical movement of each part of the body related to the patient as described above is shown to the patient by comparing it with the image showing the vertical movement of each part of the body related to a healthy person. The training can be made easier. In addition, doctors, physiotherapists, and patients compare the vertical movement correlation of each part of the patient's body during rehabilitation in a time series to determine whether the rehabilitation method is appropriate. You can know. Therefore, since the patient can rehabilitate efficiently, the rehabilitation of the patient can be expedited and the medical expenses required for the treatment of the patient can be reduced.

[0017] The rehabilitation support measurement system according to an aspect of claim 10 of the present invention is a rehabilitation support measurement system for improving the efficiency of rehabilitation of a hemiplegic patient, in which the patient's way of walking is imaged. Imaging means, motion capture means for capturing vertical movement of each part of the body including the patient's head in an image captured by the imaging means, and the patient's head captured by the motion capture means A waveform (hereinafter referred to as a head waveform) indicating the vertical momentum of the patient's head in time series based on the vertical movement of each part of the body including the part, and a waveform other than the patient's head. Each waveform (hereinafter, referred to as a waveform of each part) indicating the vertical momentum of each part of the body in a time series is obtained, and the degree of the waveform of the head and the waveform of each part is determined. Graph editing means for editing a graph in which values of respective cross-correlation functions indicating interdependence are plotted in time series, and display means for displaying the graph edited by the graph editing means. Is provided.

[0018] Further, a rehabilitation support measurement system according to an aspect of an eleventh aspect of the present invention is the rehabilitation support measurement system for improving the efficiency of rehabilitation of a hemiplegic patient. Imaging means, motion capture means for capturing vertical movement of each part of the body including the patient's head in an image captured by the imaging means, and the patient's head captured by the motion capture means Determining means for determining the degree of rehabilitation of the patient based on whether or not vertical movements of each part of the body including the part are synchronized.

In the above configuration, the degree of rehabilitation of the patient can be automatically determined based on whether or not the vertical movements of the respective parts of the body including the captured patient's head are synchronized. Each time rehabilitation is performed, a physician, physiotherapist, or patient can determine whether the rehabilitation method is appropriate by comparing the above determination results in a time series. Therefore, since the patient can rehabilitate efficiently, the rehabilitation of the patient can be expedited, and the medical expenses required for the treatment of the patient can be reduced.

[0020] Further, the rehabilitation support measurement system according to an aspect of the twelfth aspect of the present invention is the rehabilitation support measurement system for improving the efficiency of rehabilitation of hemiplegic patients. Imaging means, motion capture means for capturing vertical movement of each part of the body including the patient's head in an image captured by the imaging means, and the patient's head captured by the motion capture means A waveform (hereinafter referred to as a head waveform) indicating the vertical momentum of the patient's head in time series based on the vertical movement of each part of the body including the part, and a waveform other than the patient's head. Each waveform (hereinafter, referred to as a waveform of each part) indicating the vertical momentum of each part of the body in a time series is obtained, and the degree of the waveform of the head and the waveform of each part is determined. Calculate the value of each cross-correlation function indicating whether or not they are interdependent, and determine the progress of rehabilitation of the patient based on whether or not there is a variation in the value of these cross-correlation functions. Determining means for determining.

[0021] The measurement system for rehabilitation support according to the aspect of claim 13 of the present invention is a measurement system for rehabilitation support for improving the efficiency of rehabilitation of a patient with hip osteoarthritis. Imaging means for imaging the way of walking of the patient, and motion capture means for capturing vertical movements of the patient's head, neck, shoulders and hands in an image captured by the imaging means. A waveform indicating the vertical momentum of the patient's head in a time series based on the vertical movement of the patient's head, neck, shoulder and hand captured by the motion capture means (hereinafter referred to as a time series). , The waveform of the head) and the respective waveforms (hereinafter referred to as the waveforms of the neck, shoulder, and hand) indicating the vertical momentum of the patient's neck, shoulders, and hands in a time series. The value of the cross-correlation function between the waveform of the head and the waveform of the neck, the value of the cross-correlation function between the waveform of the head and the waveform of the shoulder, and the cross-correlation function of the waveform of the head and the waveform of the hand Is calculated and based on the values of these cross-correlation functions , And a determination means for determining the effect of rehabilitation progress and surgery of the patient.

[0022] Further, the rehabilitation support measurement method according to the aspect of claim 14 of the present invention provides a rehabilitation support measurement method for measuring the walking of a patient with osteoarthritis or hemiplegia in order to improve the efficiency of rehabilitation. In the measurement method for use, an image of the way of walking of the patient is captured, the movement of the patient in the captured image is captured, an image indicating the captured movement of the patient is edited, and the edited image is displayed. I do.

[0023] The measurement method for rehabilitation support according to an embodiment of the present invention is a method for measuring rehabilitation support for measuring the walking of a patient with hip osteoarthritis in order to improve the efficiency of rehabilitation of the patient. Capturing the patient's way of walking, capturing the patient's left and right acromion and left and right iliac spine movements or Z and head movements in the captured image, and capturing the captured left and right shoulders of the patient The movement of the trunk axis, which is the line connecting the left and right acromion of the patient, and the line connecting the left and right iliac spines, based on the movement of the peak and the movement of the left and right iliac spines, and / or the movement of the head The image showing the movement of the pelvic axis and / or the movement of the head is edited, and the edited image is displayed.

[0024] The rehabilitation support measurement method according to an aspect of the present invention is a rehabilitation support measurement method that measures the walking of a patient with osteoarthritis to improve the efficiency of rehabilitation. Capturing the patient's way of walking, capturing the patient's left and right acromion and left and right iliac spine movements in the captured image, and capturing the patient's left and right acromion, Based on the movement of the iliac spine, the left and right acromion of the patient A chart such as a graph showing the correlation between the movement of the trunk axis, which is a connected line, and the movement of the pelvic axis, which is a line connecting the right and left iliac spines, is edited, and the edited chart is displayed.

[0025] The measurement method for rehabilitation support according to an embodiment of claim 17 of the present invention is the measurement method for rehabilitation support for measuring the way of walking of a patient with osteoarthritis in order to improve the efficiency of rehabilitation of the patient. Capturing the patient's way of walking, capturing the patient's left and right acromion and left and right iliac spine movements or Z and head movements in the captured image, and capturing the captured left and right shoulders of the patient Based on the movement of the peak, the movement of the left and right iliac spines, and / or the movement of the head, it is determined whether or not the walking style of the patient is different from the walking style of a healthy person.

[0026] The method for measuring rehabilitation support according to an aspect of the present invention, wherein the method for measuring rehabilitation support for measuring the walking of a hemiplegic patient in order to improve the efficiency of the rehabilitation of the patient, comprises: An image of the patient's walking is captured, and vertical movement of each part of the body including the patient's head in the captured image is captured, and the captured vertical movement of each part of the body including the patient's head is captured. The image showing the motion is edited, and the edited image is displayed.

[0027] In addition, the rehabilitation support measurement method according to an aspect of the present invention is a rehabilitation support measurement method for measuring the walking of a hemiplegic patient in order to improve the rehabilitation efficiency of the patient. An image of the patient's walking is captured, and vertical movement of each part of the body including the patient's head in the captured image is captured, and the captured vertical movement of each part of the body including the patient's head is captured. Based on the motion, a waveform (hereinafter referred to as a head waveform) indicating the vertical motion of the patient's head in time series, and the vertical motion of each part of the body other than the head of the patient are calculated in time series. , And the values of the cross-correlation functions indicating the degree of interdependence between the waveform of the head and the waveform of each part are calculated in time series. Plotted along Edit the graph and display the edited graph.

[0028] In addition, the rehabilitation support measurement method according to the twentieth aspect of the present invention is the rehabilitation support measurement method for measuring the walking of a hemiplegic patient in order to improve the efficiency of rehabilitation. Imaging the way the patient walks, and the patient in the captured image The vertical movement of each part of the body including the head of the patient is captured, and based on whether or not the vertical movement of each part of the body including the captured head of the patient is synchronized, Determine the progress of rehabilitation.

[0029] Further, the rehabilitation support measurement method according to an aspect of the present invention, wherein the rehabilitation support measurement method for measuring the way of walking of a hemiplegic patient in order to improve the efficiency of rehabilitation of the patient, An image of the patient's walking is captured, and vertical movement of each part of the body including the patient's head in the captured image is captured, and the captured vertical movement of each part of the body including the patient's head is captured. Based on the motion, a waveform (hereinafter referred to as a head waveform) indicating the vertical motion of the patient's head in time series, and the vertical motion of each part of the body other than the patient's head in time series. , And calculate the value of each cross-correlation function indicating the degree of interdependence between the waveform of the head and the waveform of each part. , These mutual phases Based on whether there is a variation in the value of the function determines progress of the patient's rehabilitation

[0030] Further, the measuring method for rehabilitation support according to the aspect of claim 22 of the present invention is the measurement method for rehabilitation support for measuring the way of walking of a hemiplegic patient in order to improve the efficiency of rehabilitation of the patient. Capturing the patient's gait, capturing vertical movement of the patient's head, neck, shoulder and hand in the captured image, and capturing the captured patient's head, neck, shoulder and hand vertical Based on the directional movement, a waveform (hereinafter referred to as a head waveform) indicating the vertical movement amount of the patient's head in a time series and a vertical movement amount of the patient's neck, shoulder and hand are calculated. Each waveform shown in time series (hereinafter referred to as neck, shoulder and hand waveforms) is obtained, and the value of a cross-correlation function between the waveform of the head and the waveform of the neck is calculated. The value of the cross-correlation function with the shoulder waveform and the head waveform The value of the cross-correlation function between the shape and the waveform of the aforementioned hand is calculated, and based on the value of the cross-correlation function, the degree of rehabilitation of the patient and the effect of surgery are determined.

Brief Description of Drawings

FIG. 1 is a configuration diagram of a rehabilitation support measurement system according to a first embodiment of the present invention.

FIG. 2 is a configuration diagram of a personal computer in the above system. Garden 3] Illustration of the method of creating image data showing movement of the trunk axis and the like in the above system Garden 4] Illustration of the image showing the characteristics of movement of the trunk axis and the like of the hip A patient created in the above system .

Garden 5] An explanatory view of an image showing characteristics of movement of a healthy person such as a trunk axis created by the above system.

FIG. 6 is a graph showing angles formed by a trunk axis, an anterior pelvic axis, and a posterior pelvic axis with respect to a patient's traveling direction along a time series.

Garden 7] A graph showing the locus of the patient's head marker in time series.

FIG. 8 is a graph showing the angle formed by the trunk axis, anterior pelvic axis, and posterior pelvic axis with respect to the traveling direction of a healthy person in a time series.

Garden 9] A graph showing the locus of the head marker of a healthy person in time series.

FIG. 10 is a graph showing the angle formed by the trunk axis, anterior pelvic axis, and posterior pelvic axis with respect to the advancing direction of a mild patient in a time series.

Garden 11] Graph showing trajectories of head markers of mild patients along time series.

En 12] A graph showing a comparison of the magnitude of the lateral swing width when walking between a healthy person and a patient with crotch OA before and after surgery.

FIGS. 13 (a) and 13 (b) are views of a state of imaging a patient in a rehabilitation support measurement system according to a second embodiment of the present invention viewed from above and from the side.

Garden 14] A diagram showing a gait analysis screen in the rehabilitation support measurement system.

Garden 15] Graph showing correlation waveforms of various parts of the body regarding a healthy person in the rehabilitation support measurement system.

Garden 16] A graph showing the correlation waveform of each part of the body at three months after the start of rehabilitation of the hemiplegic patient in the rehabilitation support measurement system.

Garden 17] A graph showing the correlation waveform of each part of the body at 4 months after the start of rehabilitation of the hemiplegic patient in the rehabilitation support measurement system.

Garden 18] A graph showing the correlation waveform of each part of the body at the time of 6 months after the start of rehabilitation of the hemiplegic patient in the rehabilitation support measurement system. FIG. 19 shows cross-correlation values of the head waveform and the neck, shoulder, and hand waveforms of a healthy person and a patient with hip OA before and after surgery in the rehabilitation support measurement system according to the third embodiment of the present invention. Table to show.

BEST MODE FOR CARRYING OUT THE INVENTION

[0032] The best mode for carrying out the present invention will be described with reference to the drawings. The present invention relates to a rehabilitation support measurement system and a measurement method thereof for improving the efficiency of rehabilitation of a patient with osteoarthritis or hemiplegia, and a method of walking for a patient with osteoarthritis or hemiplegia. The feature is that it is possible to easily show the features when the is considered as a motion. The embodiments described below do not cover the present invention. The present invention is not limited to the following embodiments.

FIG. 1 shows a configuration of a rehabilitation support measurement system according to the first embodiment. The rehabilitation support measurement system 1 according to the first embodiment easily shows the characteristics of a patient with osteoarthritis of the hip (hereinafter referred to as hip OA (osteoarthrosis)) when the way of walking is regarded as a motion. The present invention mainly corresponds to claims 2 to 8, and claims 15 to 17. This rehabilitation support measurement system 1 includes DV (Digital Video) cameras 2a and 2b for photographing the walking of a patient T with a crotch OA, and an IEEE1394 serial bus cable (hereinafter referred to as a bus cable) from these DV cameras 2a and 2b. 4) and a personal computer 3 (hereinafter abbreviated as a personal computer) with a built-in image input board (see Fig. 2) for capturing moving image data in the form of digital video signals. The personal computer 3 includes a display 5 (display means) for displaying an image edited based on images taken from the DV cameras 2a and 2b. In this embodiment, the DV camera 2a arranged mainly above the head of the patient T corresponds to the imaging means in the claims.

FIG. 2 shows the configuration of the personal computer 3. The personal computer 3 includes, in addition to the display 5 and the image input board 32 described above, a CPU 30 for controlling the entire apparatus, and an IEEE 1394 digital interface 31 for inputting and outputting various data via the bus cable 4 (hereinafter, referred to as a personal computer 3). , A digital IF), a memory 33 in which various programs and data are loaded when the device is used, a hard disk 34 in which various programs and data are stored, and a mouse and keyboard for inputting various instructions. Operating section 35. The hard disk 34 includes a digital video capture program (digital video capture PG) 36 for capturing video data in the form of digital video signals from the DV cameras 2a and 2b, A gait analysis program (gait analysis PG) 37 for analyzing features, an analysis result display program (analysis result display PG) 38 for displaying analysis results by the gait analysis program 37, and Data comparison program (data comparison PG) 39 to show the results of analysis of the characteristics of walking in comparison with the results of analysis of the characteristics of past walking, and programs used by these programs. Reference data etc. are stored. The above gait analysis program 37 detects each marker in the video data captured from the DV cameras 2a and 2b, and calculates the moving distance, moving speed, etc. of each marker based on the detected positions of these markers. Create the original data such as graphs showing the correlation between the movement of the trunk axis, which is the line connecting the left and right acromion of the patient T, and the movement of the pelvic axis, which is the line connecting the left and right iliac spines. . In addition, the movement of the left and right acromion and the movement of the left and right iliac spines and / or the movement of the head of the patient T are analyzed from the detected positions of each marker in the moving image data, and based on the analysis results, It is automatically determined whether the walking style of the patient is different from the walking style of a healthy person. The motion capture means in the claims mainly comprises a CPU 30 in the computer 3 and a gait analysis program 37. The image editing means in the claims mainly comprises a CPU 30 in the personal computer 3, a gait analysis program 37, and an analysis result display program 38. Furthermore, the diagram editing means in the claims mainly comprises a CPU 30 in the personal computer 3, a gait analysis program 37, and an analysis result display program 38. The determination means in the claims mainly comprises the CPU 30 in the personal computer 3 and the gait analysis program 37.

Next, with reference to FIG. 3, a description will be given of a method of analyzing the characteristics of how the patient T walks in the rehabilitation support measurement system 1. Patient T head, left acromion, right acromion, upper left anterior iliac spine, upper right anterior iliac spine, upper left posterior iliac spine, and upper right posterior iliac spine, head marker 11, left acromial marker 12, right shoulder The direction of the arrow shown in the figure for patient T with the peak marker 13, upper left anterior iliac spine marker 14, upper right anterior iliac spine marker 15, upper left posterior iliac spine marker 16, and upper right posterior iliac spine marker 17 To walk. Then, the DV camera 2a disposed above the patient T captures an image of the patient T's walking, and the captured video data is stored in the personal computer 3. Embed. The personal computer 3 samples the locus data of the markers 11 to 17 from the captured video data using the gait analysis program 37 described above, and automatically and instantaneously samples the locus data of the sampled locus data. 11 ~: Read the xy axis data of 17 and calculate the trajectory of each marker 11 ~: 17. Then, the movement of the trunk axis 18, which is a line connecting the left and right acromion markers 12, 13 of the patient T, the movement of the anterior pelvic axis 19, which is a line connecting the left and right superior anterior iliac spine markers 14, 15, Image data showing the movement of the posterior pelvic axis 20, which is a line connecting the left and right superior posterior iliac spine markers 16, 17 and the movement of the head marker 11, is created. Next, the computer 3 uses the analysis result display program 38 to determine the movements of the trunk axis 18, the anterior pelvic axis 19, the posterior pelvic axis 20, and the head marker 11 of the patient T based on the above image data. The displayed image is displayed on the display 5.

Note that the left and right superior posterior iliac spine markers 16, 17 indicated by white circles in the figure are both arranged on the back side of the patient T, so that the DV camera 2a is When imaging the front of T, the left and right superior posterior iliac spine markers 16, 17 and posterior pelvic axis 20 are not displayed in the imaging screen. However, since the DV camera 2a is fixed at a fixed position above the patient T's head, when the patient T advances in the direction of travel, the upper anterior iliac spine markers 14, 15 on the left and right and the anterior pelvic axis 19 are eventually overlaid. Disappears from the captured image, and instead, the left and right upper posterior iliac spine markers 16, 17 and the posterior pelvic axis 20 are displayed in the captured image.

Next, with reference to FIG. 4 and FIG. 5, movement characteristics of the trunk axis 18, the anterior pelvic axis 19, the posterior pelvic axis 20, and the head marker 11 of the patient T with hip OA will be described. FIGS. 4 and 5 show the characteristics of the movement of the trunk axis 18 and the like between the patient T of the crotch A and a healthy person. The torso axis 18a and the anterior pelvic axis 19a in the frame 21 indicated by the broken line in FIG. 4 indicate the torso axis 18 and the anterior pelvic axis 19 in the captured image at the same time. The trunk axis 18b and anterior pelvis axis 19b in frame 22 in FIG. 4, the trunk axis 18c and anterior pelvis axis 19c in frame 23 in FIG. 5, and the trunk axis 18d and anterior pelvis in frame 24 in FIG. The same applies to the axis 19d. In addition, 12a, 13a, 14a, and 15a in the frame 21 in FIG. 4 are the left acromion marker 12, the right acromion marker 13, the left upper anterior iliac spine marker 14, and the upper right front in the captured image at the same time, respectively. The position of the iliac spine marker 15 is shown. 12b, 13b, 14b, 15b in a frame 22 in FIG. 4, 12c, 13c, 14c, 15c in a frame 23 in FIG. 5, and 12d, 13d, 14d, 15di in a frame 24 in FIG. Even the same It is. Furthermore, the wavy lines A, B, C, D, and E in FIGS. 4 and 5 indicate the head marker 11, the left acicular marker 12, and the right acicular marker in the image of the patient T or a healthy person, respectively. 13 shows the locus of the upper left anterior iliac spine marker 14 and the upper right anterior iliac spine marker 15. In the case of the patient T of the crotch A shown in FIG. 4, the position of the trunk axis 18a in the frame 21 with respect to the anterior pelvic axis 19a and the position of the trunk axis 18b in the frame 22 with respect to the anterior pelvic axis 19b are: Both are almost parallel. On the other hand, in the case of a healthy person shown in FIG. 5, the position of the trunk axis 18c in the frame 23 with respect to the anterior pelvic axis 19c and the position of the trunk axis 18d in the frame 24 with respect to the anterior pelvic axis 19d are: The shape is a U-shape (hereinafter referred to as a C-shape) or an inverted shape of the U-shape (hereinafter referred to as an inverted-C shape). This is because a healthy person is walking while twisting his body, while a patient T with a crotch OA is walking the whole body in the same horizontal direction. In addition, in the case of the patient T with hip OA shown in FIG. 4, the locus of the head marker 11 (broken line A) is larger than in the healthy person shown in FIG. It can be seen that the head sway of the patient T during walking is large.

The manner of walking of the patient T with hip OA has the characteristics described above, so that the trunk axis 18 of the patient T with hip OA at multiple imaging points as shown in boxes 21 and 22 in FIG. By displaying a moving image composed of images showing the positional relationship with the pelvic axis 19 (or the posterior pelvic axis 20) and the locus of each marker as shown by A to E in FIG. 4 on the display 5, It is possible to easily show the characteristics of the patient's crotch OA when he or she walks as a movement. As a result, the patient T of the crotch 〇A can accurately recognize his / her way of walking and perform efficient rehabilitation (hereinafter abbreviated as “rehabilitation”). This can be expedited and reduce the medical costs needed to treat T patients with hip OA. In addition, as described above, the doctor, the physiotherapist, and the patient T confirm the image that easily shows the characteristics when the way of walking of the patient T of the hip OA is grasped as a movement, so that the patient of the hip OA can be confirmed. It is possible to objectively evaluate the progress of the rehabilitation of Ding. Furthermore, by setting a predetermined threshold value, the trunk axis 18 and the anterior pelvic axis 19 (or the posterior pelvic axis 20) of the patient T of the hip A at a plurality of imaging times as shown in boxes 21 and 22 in FIG. ) And the degree of waving in the trajectory (broken line A) of the head marker 11 in Fig. 4 to automatically determine whether the patient's walking style is different from that of a healthy person. Is also possible. Further, by creating graphs as shown in FIGS. 6 and 7, a doctor, a physiotherapist, and a patient can more objectively evaluate the degree of rehabilitation of the patient T with hip OA. . Fig. 6 is a graph created based on the data of the detection position of each marker in the moving image data captured from the DV camera 2a during walking of the patient T with the crotch OA. 18, the angle formed by the anterior pelvic axis 19 and the posterior pelvic axis 20 is shown in chronological order. The dashed line I in the figure shows the transition of the angle between the direction of travel and the anterior pelvic axis 19 (the line connecting the left and right superior anterior iliac spines). The change in the angle between the direction and the trunk axis 18 (the line connecting the left and right acromion) and the angle between the direction of travel and the posterior pelvic axis 20 (the line connecting the left and right superior posterior iliac spines) And the transition of. FIG. 7 shows the trajectory L of the head marker 11 of the patient T with hip OA in time series.

As shown in FIG. 6, in the case of a patient T with crotch OA, the wave position indicating the transition of the angle between the above-mentioned traveling direction and the trunk axis 18! The peak position of the wavy line I indicating the transition of the angle formed by the axis 19 is synchronized, and the peak position of the wave HJ indicating the transition of the angle formed by the traveling direction and the trunk axis 18, and the traveling direction and the posterior pelvis The peak position of the wavy line K indicating the angle transition formed by the axis 20 is synchronized. In other words, the waves and the dashed lines I and K are approximately in phase. From this, it can be seen that the patient T with the crotch OA walks with the whole body directed in the same direction in the left-right direction. If you walk like this, you will fall easily. Further, since the locus L of the head marker 11 shown in FIG. 7 is largely wavy, it can be seen that, in the case of the patient T with the crotch A, the head shakes during walking.

On the other hand, as shown in FIG. 8, the graph created based on the detection position data of each marker in the moving image data captured from the DV camera 2a when a healthy person walks has completely different characteristics. Having. That is, in the case of a healthy person, the wave and window indicating the transition of the angle formed by the traveling direction and the trunk axis 18 and the wavy line I indicating the transition of the angle formed by the traveling direction and the anterior pelvic axis 19 are substantially similar to each other. The phases are opposite. In addition, the wave and the mouth, and the wavy line K indicating the transition of the angle formed between the traveling direction and the posterior pelvic axis 20 also have substantially opposite phases. This indicates that a healthy person is walking while twisting his body. Walking while twisting your body in this way will help prevent falls. Also, the locus L of the head marker 11 of the healthy subject shown in FIG. 9 is not much wavy as compared with the locus L of the head marker 11 of the patient T with the crotch OA shown in FIG. From the results, it can be seen that the head sway during walking is much smaller in a healthy person than in a patient T with a crotch OA.

Further, as shown in FIG. 10, the wave and the wavy line I, for the patient T of the mild hip 〇A are the cases shown in the graph shown in FIG. 6 (the patient T of the hip OA, which has some severe symptoms). In contrast, the phases are quite different. In addition, as shown in FIG. 11, the degree of undulation with respect to the trajectory L of the patient T with mild hip OA is smaller than the trajectory L of the patient T with a somewhat severe symptom A shown in FIG. , Pretty small.

Therefore, for the patient T of the crotch OA, a graph including the dashed lines I, J, and K as shown in FIGS. 6 and 10 and a graph including the trajectory L as shown in FIGS. 7 and 11 are created. By doing so, doctors, physiotherapists, and patients can more objectively evaluate the progress of rehabilitation of patient T with hip OA.

[0045] Fig. 12 is a graph showing a comparison between the magnitude of the lateral swing width during walking between a healthy person and a patient T with a crotch OA before and after surgery, which is detected based on the locus of the head marker 11. is there . The bar 52 in the figure is the horizontal swing of the patient T with a hip OA before the operation when the magnitude (statistics) of the horizontal swing width during walking of a healthy person shown in the bar 51 is 100 (statistical value). Indicates the size of the width (statistical value). The magnitude of the swing in the left and right direction during walking of a healthy subject was 100 on average and the standard deviation was 3.89. The average amplitude is 144.14 and the standard deviation is 5.12. This indicates that the patient T with the hip OA before the operation has a greater fluctuation in the left-right direction during walking as compared to the healthy person. In addition, the data of the magnitude of the swing width in the left-right direction during walking of the healthy person shown in the bar 51 and the data of the magnitude of the swing width in the left-right direction of the patient T with the crotch OA before the operation shown in the bar 52 are shown in FIG. Is significant difference of ** P <0.01.

Further, a bar 53 in the figure represents a patient T of a post-operative hip OA when the magnitude (statistical value) of the swing width in the left-right direction during walking of a healthy person shown in the bar 51 is 100. Indicates the magnitude (statistical value) of the swing width in the left and right directions. The average amplitude of the lateral swing during walking of the patient T with hip OA before the operation shown in bar 52 was 144.14 and the standard deviation was 5.12. Left and right swing of patient T with OA after surgery shown in Fig. The average width is 119.6 and the standard deviation is 6.2. This indicates that the patient T with hip OA after the surgery has a smaller head movement during walking and less horizontal wobble than the patient T with hip OA before the surgery. Thereby, it is possible to evaluate whether or not the way of walking of the patient T with the crotch OA approaches the healthy person by the operation.

[0047] As described above, according to the rehabilitation support measurement system 1 according to the first embodiment, each marker in the moving image data captured from the DV camera 2a is detected, and at the detection position of one of these markers. Based on the movement of the trunk axis 18, which is a line connecting the left and right acromion markers 12, 13 of the patient T with hip OA, and the anterior pelvic axis, which is a line connecting the left and right superior anterior iliac spine markers 14, 15. Image showing the movement of the head marker 11 (19), the movement of the posterior pelvis axis 20, which is the line connecting the left and right superior posterior iliac spine markers 16 and 17 (the image shown in Fig. 4 and the image shown in Fig. 6). The edited image can be edited and the edited image can be displayed on the display 5. Here, walking of patient T with hip OA often involves abnormal pelvic and trunk dynamics, and as described above, movement of trunk axis 18 and anterior pelvic axis 19 of patient T with hip OA By displaying images on the display 5 showing the movement of the pelvis axis 20, the movement of the posterior pelvis 20 and the movement of the head marker 11, the characteristics of the patient with crotch OA when he or she walks as a movement are identified. It can be easily shown. As a result, the patient T with the hip OA can accurately recognize his / her way of walking and can efficiently perform reno and pyri- tation (hereinafter, abbreviated as “rehabilitation”). And reduce the medical costs required to treat patient T with hip A. In addition, as described above, the doctor, the physiotherapist, and the patient confirm the image showing the characteristics when the walking style of the patient T of the crotch OA is regarded as a movement, and the doctor, the physiotherapist, and the patient confirm the image. It is possible to objectively evaluate the progress of T's rehabilitation.

Next, a rehabilitation support measurement system according to a second embodiment will be described. The rehabilitation support measurement system 1 according to the second embodiment can easily show the characteristics of a hemiplegic patient when he / she views his or her way of walking as movement. It corresponds to claims 9 to 12, and claims 18 to 21. The rehabilitation support measurement system 1 has the same configuration as the rehabilitation support measurement system 1 according to the first embodiment. However, in the second embodiment, the DV camera 2b (see FIG. 1) arranged mainly on the side of the patient T corresponds to the imaging means in the claims. Also in the second embodiment, the personal computer 3 has the same configuration as that of FIG. 2, and the hard disk 34 in the personal computer 3 stores the digital video signal format from the DV cameras 2a and 2b. Digital video capture program 36 for capturing the video data of the patient, gait analysis program 37 for analyzing the characteristics of the gait of patient T, and gait analysis program 37 An analysis result display program 38, a data comparison program 39 for showing the analysis results of the current walking characteristics of patient T in comparison with the analysis results of past walking characteristics, and a program such as these 39 Reference data etc. used in the application are stored. The gait analysis program 37 described above creates bitmap image data at intervals of 60 frames / second based on the video data captured by the DV camera 2b described above, and based on these image data, The coordinate data of each marker in T is sampled. Then, based on these coordinate data, a waveform (head waveform) indicating the vertical momentum of the patient T's head force in a time series based on the force of the patient T, and a waveform of each part of the body other than the patient's head. Each waveform (waveform of each part) indicating the vertical momentum of the marker in time series is obtained, and each cross-correlation indicating how much the waveform of the head and the waveform of each part are mutually dependent is obtained. Create a graph that plots the function values over time. Further, based on the coordinate data, the vertical movement of each part of the body including the captured patient's head is analyzed, and based on the analysis result, the way of walking of the patient is different from the way of walking of a healthy person. It is also possible to automatically determine whether or not this is the case. The motion capture means in claims 9 to 12 mainly includes the CPU 30 in the personal computer 3 and the gait analysis program 37. Further, the image editing means in claim 9 and the graph editing means in claim 10 are mainly composed of the CPU 30 in the personal computer 3 and the gait analysis program 37. Further, the determination means in claims 11 and 12 mainly includes the CPU 30 in the personal computer 3 and the gait analysis program 37.

Next, with reference to FIGS. 13 (a) and 13 (b), a method of analyzing the characteristics of how the hemiplegic patient T walks in the rehabilitation support measurement system 1 will be described. As shown in FIG. 13 (b), the marker 61 is attached to each part of the body including the head of the patient T, and as shown in FIG. 13 (a), the patient T is viewed from the side with the DV camera 2b. Take an image. At this time, the imaging time with the DV camera 2b is about 30 seconds, and the imaging is performed with the distance between the patient T and the DV camera 2b maintained at 2 to 3 m. I do. The marker 61 can be attached to the patient T by applying the marker on the clothes of the patient 服, but it is more desirable to apply it directly to the skin of the patient Τ.

Next, a simple analysis method (first analysis method) of the walking characteristics of the hemiplegic patient Τ will be described with reference to FIG. FIG. 14 shows the gait analysis screen 71 of the patient Τ. The gait analysis screen 71 includes a graph 72 which is an image showing the vertical movement of the marker 61 of each part of the body including the head of the patient と, and a marker 72 of each part of the body including the head of the patient 61. A graph 73 or the like, which is an image indicating the vertical movement acceleration of the image, is displayed. Here, the progress of rehabilitation of hemiplegic patient Τ is determined by whether or not the vertical movement of the patient Τ's head and the vertical movement of each part other than the head are synchronized. By displaying the graph 72 showing the vertical movement of each part of the body including the head of the patient Τ as described above, the doctor, the physiotherapist and the patient Τ 72, the degree of rehabilitation of the hemiplegic patient Τ can be easily determined. Therefore, the physician, the physiotherapist, and the patient Τ can compare the graph 72 of the patient における during rehabilitation in a time-series manner to know whether the rehabilitation method is appropriate. As a result, the patient 効率 can rehabilitate efficiently, so that the patient 復帰 's rehabilitation can be expedited and the medical expenses required for the treatment of the patient 削減 can be reduced. In addition, the graph 72 of the patient ような as described above is shown to the patient て in comparison with the graph 72 showing the vertical movement of each part of the body related to a healthy person, so that the patient Τ can easily perform the image training. it can. Graphs 72 and 73 in the figure are edited based on the data of healthy subjects, and the graph 72 of hemiplegic patient Τ is compared with the graph 72 of healthy subjects shown in FIG. The vertical movement 74 of the marker 61 attached to the patient 頭部 's head and the vertical movement 75 of the marker 61 attached to each part of the body other than the head become more synchronous.

[0052] As described above, the CPU 30 of the personal computer 3 that the doctor, the physiotherapist, and the patient Τ do not judge the rehabilitation progress of the patient Τ by looking at the graph 72 shown in FIG. Based on the data of patient になる, which is the source of graph 72, the vertical movement of the head of patient Τ and the vertical movement of each part other than the head are synchronized, The degree of rehabilitation of the patient Τ may be automatically determined. Next, a detailed analysis method (second analysis method) of the walking characteristics of the hemiplegic patient T will be described. In the second analysis method, a waveform (hereinafter, referred to as a head waveform) indicating the vertical movement amount of the patient Τ's head 61 with respect to the marker 61 in time series (hereinafter referred to as a head waveform) is obtained by The waveforms indicating the vertical momentum of the marker 61 in time series (hereinafter referred to as waveforms of the parts other than the head) are obtained, and the waveform of the head and the waveforms of the parts other than the head are determined. The characteristics of the walking style of patient Τ are analyzed by creating a graph in which the values of each cross-correlation function indicating the degree of interdependence are plotted in a time series.

Here, the above cross-correlation function will be described. The cross-correlation function is a function that indicates how much the two time-series waveforms are interdependent or similar, and is expressed by the following equation.

[Number 1]

[0055] The above function indicates the correlation between the waveform x (At) and the waveform y (At). In this analysis method, the waveform of the head is X (Δt), the waveform of each part other than the head is y (Δt), and the value of the cross-correlation function for these waveforms is By creating a graph plotted along the series, the synchronization and rhythm of the vertical momentum of each part of the patient's T body are compared. Thereby, it is possible to see the characteristics of the movement cycle of the patient T, with the movement characteristics of each part of the body of the patient T as an index, centering on the movement cycle of the head of the patient T.

FIG. 15 shows a waveform (hereinafter abbreviated as a cross-correlation value) of a cross-correlation function between a waveform of a head and a waveform of each part other than the head of a healthy person, which is plotted in time series. A graph consisting of a correlation waveform is shown below. For example, the correlation waveform of the shoulder shown by the thick line in the figure is the waveform of the above-mentioned head (the waveform showing the vertical momentum of the head marker 61 in time series) and the vertical waveform of the shoulder marker 61. Waveforms showing directional momentum along time series Is a curve in which the cross-correlation values of are plotted along a time series. In addition, the correlation waveform of the ankle indicated by the thin line in the figure includes the waveform of the head (a waveform indicating the vertical momentum of the head marker 61 in time series) and the vertical waveform of the ankle marker 61. This is a curve in which the cross-correlation value with the waveform indicating the amount of movement along the time series is plotted along the time series. In the graph of a healthy person shown in this figure, there is a strong correlation, an antiphase waveform, and a correlation between the correlation waveforms of the shoulder, elbow, hand, buttocks, knees, ankles, toes, and heels. There are variations such as waveforms.

[0057] On the other hand, the correlation waveform of each part of the body on the paralyzed side of the hemiplegic patient T shown in FIG. It goes up and down with almost the same rhythm. This means that the gait on the paralyzed side of hemiplegic patient T does not have the complexity and flexibility of the gait of a healthy person. The graph shown in the figure shows the correlation waveform of each part of the body at three months after the start of rehabilitation of hemiplegic patient T.

FIG. 17 is a graph showing a correlation waveform of each part of the body at a time point of four months after the start of rehabilitation of hemiplegic patient T. Even at this time, the correlation waveform of each part of the body on the paralyzed side of the hemiplegic patient T, which has little variation, rises and falls with a rhythm that almost coincides with the movement of the head.

[0059] On the other hand, in the correlation waveform of each part of the body at 6 months after the start of rehabilitation of the hemiplegic patient T shown in Fig. 18, a variation as seen in a healthy person can be seen. More specifically, there are more variations in the correlation waveform of each part of the arm than in the correlation waveform of each part of the foot.

[0060] From Figs. 15 to 18 above, it can be easily determined that the variation of the correlation waveform (cross-correlation value) of each part of the body increases in the process of rehabilitation of the hemiplegic patient T. Therefore, by comparing the correlation waveforms of a certain hemiplegic patient T along a time series, it is possible to evaluate the progress of rehabilitation of the patient T. In addition, based on the degree of change in the correlation waveform of patient T during rehabilitation, it is possible to evaluate whether the rehabilitation method is appropriate or not.

[0061] As described above, in the second analysis method regarding the way of walking of the hemiplegic patient T, the head of the patient T is determined based on the vertical movement of each part of the body including the captured head of the patient T. About the department Waveform showing the vertical momentum along the time series (waveform of the head) and each waveform showing the vertical momentum of each part of the body other than the head of the patient T along the time series (waveform of each part) A graph consisting of correlation waveforms plotting the values of each cross-correlation function indicating the degree of interdependence between the waveform of the head and the waveform of each part in time series (see FIGS. 15 to 15). Edit the graph shown in 18) to display the edited graph. Here, since the characteristics of the way of walking of the patient T with hemiplegia generally appear in the vertical movement of each part of the body, the doctor, the physiotherapist and the patient T The rehabilitation progress of the patient T can be easily determined. In addition, the graph of the patient T as described above is shown to the patient T in comparison with a graph showing the vertical movement of each part of the body related to a healthy person, so that the patient T can easily perform image training. it can. In addition, the physician, physiotherapist, and patient T can compare the graph of patient T during rehabilitation in chronological order to determine whether the rehabilitation method is appropriate. Therefore, since the patient T can rehabilitate efficiently, the reintegration of the patient T into the society can be expedited, and the medical expenses required for the treatment of the patient T can be reduced.

Further, as described above, the doctor, the physiotherapist, and the patient T do not judge the rehabilitation progress of the patient T based on the graphs shown in FIGS. CPU 30 Power Calculate the value of each cross-correlation function indicating the degree of interdependence between the waveform of the head of patient T and the waveform of each part described above, and check if there are variations in the values of these cross-correlation functions. The progress of the rehabilitation of the patient T may be automatically determined based on whether the rehabilitation is performed.

Next, a rehabilitation support measurement system according to a third embodiment will be described. The rehabilitation support measurement system 1 according to the third embodiment is a rehabilitation support measurement system for patients with crotch A, similar to the rehabilitation support measurement system according to the first embodiment. And claim 22. The rehabilitation support measurement system 1 has the same configuration as the rehabilitation support measurement system 1 according to the second embodiment, and requires a DV camera 2b (see FIG. 1) arranged beside the patient T. Corresponds to the imaging means in the section.

[0064] In the rehabilitation support measurement system 1 according to the third embodiment, the crotch is measured using a method similar to the second analysis method in the rehabilitation support measurement system 1 according to the second embodiment. 患者 Evaluate the progress of rehabilitation of T patients and the effects of surgery. Specifically, based on the vertical motion of the patient 頭部 's head, neck, shoulders, and hands captured by the DV camera 2b arranged on the side of the patient Τ, the vertical motion of the patient T's head is calculated. The waveforms (time waveforms of the head) along the time series and the waveforms (neck, shoulder, and hand waveforms) indicating the vertical momentum about the neck, shoulders, and hands of the patient T along the time series were obtained. Calculate the value of each cross-correlation function (cross-correlation value) indicating the degree of interdependence between the waveform of the head and the waveforms of the neck, shoulder and hand, and based on these cross-correlation values, Judge the progress of T rehabilitation and the effect of surgery.

FIG. 19 shows the cross-correlation values of the waveform of the head and the waveforms of the neck, shoulder, and hand for a healthy person and a patient T with hip OA before and after surgery. The subjects were women between the ages of 26 and 55. The number of subjects was 22 healthy subjects, 11 OA patients before surgery, and 10 OA patients after surgery. As shown in the figure, the cross-correlation value between the head waveform and the neck waveform, the cross-correlation value between the head waveform and the shoulder waveform, and the head waveform of the patient T with OA before surgery The cross-correlation value between the waveform and the hand waveform is lower than each cross-correlation value in healthy subjects, but each cross-correlation value in the patient T with hip OA after surgery is close to each cross-correlation value in healthy subjects. Changes to a value. By utilizing this tendency, it is possible to determine the effect of the operation on patient T and the degree of rehabilitation. For the determination of the effect of this operation and the determination of the degree of rehabilitation, the CPU 30 in the personal computer 3 calculates the cross-correlation value between the waveform of the head and the waveform of the neck, shoulder, and hand of the patient T with the above-mentioned hip OA. The determination may be made automatically on the basis of the cross-correlation value between the waveform of the head of the patient T of the crotch A and the waveforms of the neck, shoulder, and hands of the CPU 30 in the personal computer 3. 5 Displayed above, the physician, physiotherapist and patient T may judge based on the displayed cross-correlation value.

The difference between the cross-correlation values between the healthy subject and the patient T with hip 〇A before the operation shown in FIG. 19 is based on the walking style acquired by the patient T with hip 〇A to relieve the pain in the hip joint. This is due to the awkwardness. Patient T with hip OA after surgery gradually approaches the usual walking method because the pain in the hip joint disappears. Specifically, in patients with hip OA after surgery, the vertical swing width of the head is smaller than before surgery, and the correlation between the joints of the neck, shoulder, and hands and the head is higher. Therefore, the movement of weight 'negative weight is improved, and walking becomes easier. Therefore, compared to before surgery It is harder to knock down, and the power is less tired.

[0067] The present invention is not limited to the above embodiment, and various modifications are possible. For example, in the above-described first to third embodiments, an example of the configuration of the simply rehabilitation support measurement system including the DV cameras 2a and 2b and the personal computer 3 has been described. Data may be stored in a server via the Internet or a VPN (Virtual Private Network), and a database of analysis data may be created on the server. Further, in the first embodiment, the images showing the movements of the trunk axis 18, the anterior pelvic axis 19, the posterior pelvic axis 20, and the head marker 11 are displayed on the display 5. Only the image indicating the movement of the trunk axis may be displayed on the display, or only the image indicating the movement of the head marker 11 may be displayed on the display. Furthermore, only a graph showing the angles formed by the trunk axis and the pelvic axis with respect to the patient's advancing direction as shown in FIG. 6 in chronological order may be displayed on the display. Further, in each of the above embodiments, an image showing the movement of the patient's torso axis or the like as shown in FIG. 4, a graph as shown in FIG. 6, or a graph as shown in FIGS. May be printed by a printer instead of being displayed on the display.

[0068] The present application is based on Japanese Patent Application No. 2004-113690, filed in Japan on April 7, 2004, the contents of which are by reference to the specification and drawings of the above patent application. As a result, it should be incorporated into the present invention.

[0069] Although the present invention has been more fully described by the embodiments with reference to the accompanying drawings, it is understood that various changes and modifications are possible for those having ordinary knowledge in this field. It will be obvious. Therefore, such changes and modifications should be construed as included in the scope of the present invention, which does not depart from the scope of the present invention. Industrial applications

[0070] As described above, according to the present invention, it is possible to edit the captured image indicating the movement of each part of the patient's body and display the edited image on the display means. This enables patients with hip osteoarthritis or hemiplegia to easily understand the characteristics of their own way of walking as movements, so that the patient can accurately recognize his or her own way of walking and improve efficiency. Rehabilitation and rehabilitation (hereafter abbreviated as rehabilitation). Therefore, rehabilitation of patients This can be expedited and the medical costs required to treat the patient can be reduced. In addition, as described above, doctors, physiotherapists, and patients confirm images that clearly show the characteristics of how the patient walks as movements, and objectively evaluate the progress of the patient's rehabilitation. can do.

Claims

The scope of the claims

[1] In a rehabilitation support measurement system for improving the efficiency of rehabilitation (hereinafter abbreviated as “rehabilitation”) for patients with hip osteoarthritis or hemiplegia,

Imaging means for imaging how to walk the patient,

Motion capture means for capturing the movement of each part of the patient's body in the image picked up by the image pickup means;

Image editing means for editing an image indicating movement of each part of the patient's body captured by the motion capture means;

A display unit for displaying the image edited by the image editing unit.

[2] In a rehabilitation support measurement system to improve the efficiency of rehabilitation for patients with hip osteoarthritis,

Imaging means for imaging how to walk the patient,

Motion capture means for capturing the movement of the left and right acromion of the patient and the movement of the left and right iliac spines, or / and the movement of the head in the image captured by the imaging means, and the motion captured by the motion capture means. Based on the movement of the patient's left and right acromion, and the movement of the left and right iliac spines, and / or the movement of the head, the movement of the trunk axis, which is the line connecting the left and right acromion of the patient, and the left and right iliac spines are determined. Image editing means for editing an image showing the movement of the pelvis axis, which is the connected line, or the movement of Z and the head,

A display unit for displaying the image edited by the image editing unit.

3. The rehabilitation support measurement system according to claim 2, wherein the pelvic axis is a line connecting left and right upper iliac spines or left and right upper iliac spines of the patient.

[4] In a rehabilitation support measurement system to improve the efficiency of rehabilitation for patients with hip osteoarthritis,

Imaging means for imaging how to walk the patient,

Motion capture means for capturing the movement of the left and right acromion of the patient and the movement of the left and right iliac spines in the image captured by the imaging means; The movement of the trunk axis, which is a line connecting the left and right shoulders of the patient, based on the movement of the left and right shoulders of the patient captured by the motion capture means and the movement of the left and right iliac spines. A chart editing means for editing a chart such as a graph showing a correlation between the movement of the pelvic axis, which is a line connecting the right and left iliac spines,

A display means for displaying the chart edited by the chart editing means.

[5] The chart edited by the chart editing means is a time-series chart representing the angle formed by the trunk axis with respect to the traveling direction of the patient and the angle formed by the trunk axis with respect to the traveling direction of the patient. The rehabilitation support measurement system according to claim 4, wherein the measurement system is a graph represented along columns.

6. The rehabilitation support measurement system according to claim 5, wherein the pelvic axis is a line connecting the left and right upper iliac spines or the left and right upper iliac spines of the patient.

7. The rehabilitation support measurement system according to claim 4, wherein the pelvic axis is a line connecting the left and right upper iliac spine or the left and right upper iliac spine of the patient.

[8] In a rehabilitation support measurement system to improve the efficiency of rehabilitation for patients with hip osteoarthritis,

Imaging means for imaging how to walk the patient,

Motion capture means for capturing the movement of the left and right acromion of the patient and the movement of the left and right iliac spines, or / and the movement of the head in the image captured by the imaging means, and the motion captured by the motion capture means. Determining means for determining, based on the movement of the left and right acromion of the patient, the movement of the left and right iliac spines, and / or the movement of the head, whether or not the way of walking of the patient is different from the way of walking of a healthy person. Measurement system for rehabilitation support.

[9] In a rehabilitation support measurement system to improve the efficiency of rehabilitation for hemiplegic patients,

Imaging means for imaging how to walk the patient,

Motion capture means for capturing vertical movement of each part of the body including the patient's head in the image captured by the image capturing means; Image editing means for editing an image indicating vertical movement of each part of the body including the patient's head captured by the motion capture means;

A display unit for displaying the image edited by the image editing unit.

[10] In a rehabilitation support measurement system for improving the efficiency of rehabilitation of hemiplegic patients,

Imaging means for imaging how to walk the patient,

Motion capture means for capturing vertical movement of each part of the body including the patient's head in the image captured by the image capturing means;

A waveform (hereinafter, referred to as a time series) indicating the vertical momentum about the patient's head based on the vertical movement of each part of the body including the patient's head captured by the motion capture means. The waveform of the head is referred to as the waveform of the head, and the waveform (hereinafter referred to as the waveform of each part) indicating the vertical momentum of each part of the body other than the head of the patient in a time series. Graph editing means for editing a graph in which values of respective cross-correlation functions indicating how much the waveforms of the respective parts are interdependent are plotted in time series.

Display means for displaying a graph edited by the graph editing means. A rehabilitation support measurement system.

[11] In a rehabilitation support measurement system for improving the efficiency of rehabilitation of hemiplegic patients,

Imaging means for imaging how to walk the patient,

Determining means for determining the degree of rehabilitation of the patient based on whether or not vertical movements of various parts of the body including the patient's head captured by the motion capture means are synchronized. Measurement system for rehabilitation support.

[12] In a rehabilitation support measurement system to improve the efficiency of rehabilitation for hemiplegic patients, Imaging means for imaging how to walk the patient,

A waveform indicating the vertical momentum of the patient's head along a time series based on the vertical movement of each part of the body including the patient's head captured by the motion capture means (hereinafter, referred to as a time series). The waveform of the head is referred to as the waveform of the head, and the waveform (hereinafter, referred to as the waveform of each part) indicating the vertical momentum of each part of the body other than the head of the patient in time series. And the value of each cross-correlation function indicating the degree of interdependence between the waveforms of the respective parts and the rehabilitation of the patient based on whether or not the values of these cross-correlation functions have variation power S. And a determination means for determining the degree of progress of the rehabilitation.

[13] In a rehabilitation support measurement system to improve the efficiency of rehabilitation for patients with hip osteoarthritis,

Imaging means for imaging how to walk the patient,

Motion capture means for capturing vertical movements of the patient's head, neck, shoulders and hands in an image captured by the imaging means;

A waveform (hereinafter referred to as a head) indicating the vertical momentum of the patient's head in a time series based on the vertical movement of the patient's head, neck, shoulders and hands captured by the motion capture means. Waveforms indicating the vertical momentum of the patient's neck, shoulders and hands in time series (hereinafter referred to as neck, shoulder and hand waveforms), The value of the cross-correlation function between the waveform and the neck waveform, the value of the cross-correlation function between the head waveform and the shoulder waveform, and the value of the cross-correlation function between the head waveform and the hand waveform And a determination means for determining, based on the values of these cross-correlation functions, the degree of rehabilitation of the patient and the effect of surgery.

[14] In a rehabilitation support measurement method for measuring the way of walking of a patient with osteoarthritis or hemiplegia in order to improve the efficiency of rehabilitation,

Imaging the way the patient walks, Capturing the movement of the patient in the captured image,

Editing an image showing the captured movement of the patient,

A rehabilitation support measurement method, characterized by displaying the edited image.

[15] In a rehabilitation support measurement method of measuring a walking method of a patient with hip osteoarthritis to improve rehabilitation efficiency of the patient,

Imaging the way the patient walks,

Capture the movement of the patient's left and right acromion and left and right iliac spines in the captured image, or / and head movement,

Based on the captured movement of the patient's left and right acromion and the movement of the left and right iliac spines, and / or the movement of the head, the movement of the trunk axis, which is a line connecting the left and right acromion of the patient, and the left Edit the image showing the movement of the pelvic axis, which is the line connecting the right iliac spines, and / or the movement of the head,

[16] In a rehabilitation support measurement method for measuring a patient's walking method to improve the rehabilitation efficiency of a patient with hip osteoarthritis,

Imaging the way the patient walks,

Capturing the movement of the patient's left and right acromion and the movement of the left and right iliac spines in the captured image,

Based on the captured movement of the left and right acromion of the patient and the movement of the left and right iliac spines, a line connecting the trunk axis movement and the left and right iliac spines, which is a line connecting the left and right acromion of the patient, Edit the charts such as graphs showing the correlation with the movement of the pelvic axis,

A rehabilitation support measurement method, characterized by displaying the edited chart.

[17] In a rehabilitation support measurement method of measuring a patient's gait to improve rehabilitation efficiency of a patient with hip osteoarthritis,

Imaging the way the patient walks,

Movement of the captured left and right acromion of the patient, and movement of the left and right iliac spines, or / and A method for measuring rehabilitation support, comprising determining whether or not the way of walking of the patient is different from the way of walking of a healthy person based on head movement.

[18] In a rehabilitation support measurement method for measuring the walking of a hemiplegic patient in order to improve the efficiency of rehabilitation,

Imaging the way the patient walks,

Capturing vertical movement of each part of the body including the patient's head in the captured image;

Compiling an image showing the vertical movement of each part of the body including the captured patient's head,

[19] In a rehabilitation support measurement method for measuring the walking of a hemiplegic patient in order to improve the efficiency of rehabilitation,

Imaging the way the patient walks,

Based on the vertical movement of each part of the body including the captured patient's head, a waveform (hereinafter referred to as a head waveform) indicating a vertical movement amount of the patient's head along a time series, Waveforms (hereinafter referred to as “waveforms of each part”) indicating a vertical movement amount of each part of the body other than the head of the patient in a time series are obtained, and the waveform of the head and the waveform of each of the aforementioned parts are determined. Edit the graph that plots the value of each cross-correlation function indicating the degree of interdependence along the time series,

A measurement method for rehabilitation support, wherein the edited graph is displayed.

[20] In a rehabilitation support measurement method for measuring the walking of a hemiplegic patient in order to improve the efficiency of rehabilitation,

Imaging the way the patient walks,

The vertical movement of each part of the body including the captured patient's head is synchronized. A rehabilitation support measurement method, wherein the degree of rehabilitation of the patient is determined based on whether the patient is rehabilitated.

[21] In a rehabilitation support measurement method for measuring the walking of a hemiplegic patient in order to improve the efficiency of rehabilitation,

Imaging the way the patient walks,

Based on the vertical movement of each part of the body including the captured patient's head, a waveform (hereinafter referred to as a head waveform) indicating a vertical momentum of the patient's head in time series, A waveform (hereinafter, referred to as a waveform of each part) indicating a vertical movement amount of each part of the body other than the head of the patient in a time series is obtained, and the waveform of the head and the waveform of each part are determined. Calculating the value of each cross-correlation function indicating the degree of interdependence, and determining the degree of rehabilitation of the patient based on whether there are variations in the values of the cross-correlation functions. Measurement method for rehabilitation support.

[22] In a rehabilitation support measurement method for measuring the way of walking of a hemiplegic patient in order to improve rehabilitation efficiency,

Imaging the way the patient walks,

Capturing vertical movement of the patient's head, neck, shoulders and hands in the captured image;

A waveform (hereinafter referred to as a head waveform) indicating a vertical movement amount of the patient's head in a time series based on the captured vertical movement of the patient's head, neck, shoulder, and hand. And respective waveforms (hereinafter referred to as neck, shoulder, and hand waveforms) indicating the amount of vertical movement related to the neck, shoulder, and hand of the patient in a time series, are obtained, and the waveforms of the head and the neck are obtained. And the value of the cross-correlation function between the head waveform and the shoulder waveform, and the value of the cross-correlation function between the head waveform and the hand waveform are calculated. A rehabilitation support measurement method, wherein the degree of rehabilitation of the patient and the effect of surgery are determined based on the value of the cross-correlation function.