JP2018069035A - Walking analysis system and method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a walking analysis system capable of calculating a walking age commensurate with walking ability.SOLUTION: A walking analysis system 100 includes a three-dimensional measuring device 1 for measuring three-dimensional coordinates of a plurality of predetermined body feature points of a subject H in association with walking of the subject sequentially, and an analysis device 2 for calculating a speed age, a balance age, and a posture age of the subject using the three-dimensional coordinates of the plurality of body feature points of the subject, and a first correspondence stored beforehand, and calculating a walking age of the subject, using each of the calculated ages of the subject and a second correspondence stored beforehand. The first correspondence is the correspondence between a plurality of walking parameters calculated using the three-dimensional coordinates of the body feature points and each age such as the speed age, and the plurality of walking parameters include at least the walking speed, a right and left difference in a walking rhythm, and bending of the waist.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a gait analysis system and a gait analysis method for calculating evaluation criteria (gait age, appearance age, beauty posture evaluation value) related to walking of a subject.

  In recent years, with the increase in the elderly population, awareness of the ability to walk that affects healthy life expectancy, especially the range of living behavior, has increased. For this reason, there is a high need for elderly people, particularly elderly people, who want to know objective evaluation criteria for the average level (walking age) of their own walking ability.

  Elderly people often have a desire to be seen younger than their actual age. For this reason, the subjective age of what kind of age the person's walking posture is seen from around (appearance age) and how beautiful his / her walking posture is thought to be (beautiful posture evaluation value) There is a high need to know the evaluation criteria.

As a method for evaluating walking age, which is an objective evaluation criterion, for example, a method described in Patent Document 1 has been proposed.
The method described in Patent Document 1 analyzes a pressure distribution image detected when a subject walks on a seat-type pressure sensor, and as walking parameters, left and right walking angles, walking cycles, and both-leg support period time. And the stride is calculated, and the walking age is evaluated using these walking parameters.

  In the method described in Patent Document 1, since the walking parameter is only calculated using the detection result of the pressure sensor, that is, the movement of the sole, the walking state is comprehensively evaluated over the whole body of the subject. There is a problem that it is impossible to calculate the walking age that matches the walking ability.

No particularly effective method has been proposed as a method for evaluating the apparent age, which is a subjective evaluation criterion.
Further, as a method for evaluating a beauty posture evaluation value that is a subjective evaluation criterion, for example, a method described in Patent Document 2 has been proposed.
The method described in Patent Document 2 measures the pedestrian's foot pressure distribution as an operating state, classifies the foot pressure distribution into each part of the sole, and uses the classified load value for each foot part in spatiotemporal walking characteristics. This is a method of calculating as a quantity and quantitatively analyzing the beauty of walking from the space-time walking feature quantity.

  In the method described in Patent Document 2, since the foot pressure distribution is only used as a walking parameter (a spatiotemporal walking feature amount), the walking state cannot be comprehensively evaluated over the whole body of the subject, and the walking posture There is a problem that it is not possible to calculate a beauty posture evaluation value that matches the above.

JP 2014-94070 A JP 2001-218754 A

  The present invention has been made to solve the above-mentioned problems of the prior art, and by making it possible to comprehensively evaluate the walking state of the whole body, a walking analysis system capable of calculating the walking age that matches the walking ability and It is an object to provide a walking analysis method. Similarly, an object of the present invention is to provide a walking analysis system and a walking analysis method capable of calculating an appearance age that matches a walking posture. Furthermore, an object of the present invention is to provide a walking analysis system and a walking analysis method that can calculate a beauty posture evaluation value that matches a walking posture.

  In order to solve the above-mentioned problems, the present invention provides a three-dimensional measuring apparatus that sequentially measures three-dimensional coordinates of a plurality of predetermined body feature points of a subject as the subject walks, and three-dimensional coordinates of the body feature points. A first correspondence relationship between a plurality of gait parameters calculated using the above or other methods and speed age, balance age and posture age, and the speed age, balance age and posture age The second correspondence relationship with the walking age is stored in advance and is calculated using the three-dimensional coordinates of the plurality of body feature points of the subject measured by the three-dimensional measuring device or calculated using another method. The velocity age, balance age and posture age of the subject are calculated using the plurality of walking parameters of the subject and the first correspondence relationship stored in advance, and the calculated velocity age, And an analysis device for calculating the walking age of the subject using the pre-stored second correspondence relationship, and the plurality of walking parameters include at least walking speed, walking The first correspondence relationship includes a first regression equation having the walking speed as an independent variable and the speed age as a dependent variable, and at least left and right of the walking rhythm. A gait analysis system including a second regression equation having a difference as an independent variable and the balance age as a dependent variable, and a third regression equation having at least the waist bending as an independent variable and the posture age as a dependent variable I will provide a.

  According to the walking analysis system according to the present invention, in addition to the walking speed related to the speed age and the left-right difference of the walking rhythm related to the balance age, the waist of the posture age that cannot be evaluated by the method described in Patent Literature 1. The walking age is calculated using the bend as a walking parameter. For this reason, compared with the method described in Patent Document 1, the walking state can be comprehensively evaluated, and the walking age that matches the walking ability can be calculated.

  Each of the first regression equation, the second regression equation, and the third regression equation performs regression analysis with the dependent variable as the actual age of a plurality of humans and the independent variable as each gait parameter calculated for the plurality of humans. It is possible to calculate by this.

  For example, the second correspondence relationship may be a relationship in which the walking age is represented by a linear sum of the speed age, the balance age, and the posture age.

  Preferably, the plurality of body feature points include at least a thoracolumbar and a center of the pelvis, and the walking speed is calculated using a three-dimensional coordinate of the thoracolumbar or other methods. The left-right difference of the walking rhythm is calculated using the three-dimensional coordinates of the thoracolumbar, and the bending of the waist is calculated using the three-dimensional coordinates of the thorax and the center of the pelvis. .

  The center of the thoracolumbar and the pelvis of the body feature points used in the above preferred configuration can measure three-dimensional coordinates without using markers, for example, by using Kinect (registered trademark) manufactured by Microsoft Corporation in the United States. Therefore, there is an advantage that measurement is easy.

  Preferably, the plurality of body feature points further includes left and right pelvises and left and right knees, further includes left and right knees and left and right ankles, or further includes left and right ankles and left and right toes. The plurality of walking parameters may be calculated using three-dimensional coordinates of the thoracolumbar, the left and right pelvis, and the left and right knees, or may be calculated using the thoracolumbar, the left and right knees, and the left and right ankles. A left-right difference in walking angle calculated using three-dimensional coordinates or calculated using three-dimensional coordinates of the thoracolumbar, the left and right ankles, and the left and right toes; The second regression equation included in is a multiple regression equation in which at least the left-right difference of the walking rhythm and the left-right difference of the walking angle are independent variables and the balance age is a dependent variable.

According to a study by the present inventors, in the regression analysis for calculating the second regression equation using the balance age as a dependent variable, when various walking parameters are used as independent variables, the left-right difference in walking rhythm is Although the contribution was the highest, it was found that the difference between the left and right walking angles was relatively high.
According to the above preferred configuration, the second regression equation uses the left-right difference of the walking rhythm with the highest contribution as an independent variable, and also uses the left-right difference of the walking angle with a relatively high contribution as the independent variable. Therefore, it is possible to calculate a walking age that more closely matches the walking ability.

  Preferably, the plurality of body feature points further include left and right pelvises and left and right knees, and the plurality of walking parameters include three-dimensional measurements of the thoracolumbar, the left and right pelvises, and the left and right knees. Further, a left-right difference in thigh rise calculated using coordinates is further included, and the second regression equation included in the first correspondence relationship includes at least a left-right difference in the walking rhythm and a left-right difference in the thigh rise. Is an independent variable, and the multiple regression equation with the balance age as a dependent variable.

According to a study by the present inventors, in the regression analysis for calculating the second regression equation using the balance age as a dependent variable, when various walking parameters are used as independent variables, the left-right difference in walking rhythm is Although the highest contribution, the difference between the left and right thighs was also found to be relatively high.
According to the above preferred configuration, the second regression equation uses the left-right difference of the walking rhythm with the highest contribution as an independent variable, and the multiple regression using the left-right difference of the rise of the thigh with a higher contribution as an independent variable. Since the expression is used, it is possible to calculate a walking age that more closely matches the walking ability.

  Preferably, the plurality of body feature points further include left and right shoulders, and the plurality of walking parameters include shoulder horizontal angles calculated using three-dimensional coordinates of the thoracolumbar and the left and right shoulders. In addition, the second regression equation included in the first correspondence relationship includes, at least, a left-right difference of the walking rhythm and the shoulder horizontal angle as independent variables, and a multiple regression equation with the balance age as a dependent variable. It is.

According to a study by the present inventors, in the regression analysis for calculating the second regression equation using the balance age as a dependent variable, when various walking parameters are used as independent variables, the left-right difference in walking rhythm is Although the most significant contribution, the shoulder horizontal angle was found to be relatively high.
According to the above preferred configuration, the second regression equation is a multiple regression equation in which the left-right difference of the walking rhythm with the highest contribution is an independent variable and the shoulder horizontal angle with a relatively high contribution is also an independent variable. Therefore, it is possible to calculate a walking age that more closely matches the walking ability.

  Preferably, the plurality of body feature points further includes left and right pelvises and left and right knees, further includes left and right knees and left and right ankles, or further includes left and right ankles and left and right toes. The plurality of walking parameters may be calculated using three-dimensional coordinates of the thoracolumbar, the left and right pelvis, and the left and right knees, or may be calculated using the thoracolumbar, the left and right knees, and the left and right ankles. A walking angle calculated using three-dimensional coordinates or calculated using three-dimensional coordinates of the thoracolumbar, the left and right ankles, and the left and right toes is further included in the first correspondence relationship. The third regression equation is a multiple regression equation in which at least the hip bending and the walking angle are independent variables and the posture age is a dependent variable.

According to a study by the present inventors, in the regression analysis for calculating the third regression equation with posture age as a dependent variable, when various walking parameters were used as independent variables, the bending of the waist contributed most. Although the degree is high, it was found that the walking angle also has a relatively high contribution.
According to the above preferred configuration, the third regression equation is a multiple regression equation in which the hip bending with the highest contribution is an independent variable and the walking angle with a relatively high contribution is also an independent variable. It is possible to calculate a walking age that more closely matches the walking ability.

  Preferably, the plurality of body feature points further include left and right toes, and the plurality of walking parameters include toe lifts calculated using three-dimensional coordinates of the thoracolumbar and the left and right toes. Further, the third regression equation included in the first correspondence relationship is a multiple regression equation in which at least the bending of the waist and the rise of the toes are independent variables and the posture age is a dependent variable. .

According to a study by the present inventors, in the regression analysis for calculating the third regression equation with posture age as a dependent variable, when various walking parameters were used as independent variables, the bending of the waist contributed most. Although the degree was high, it was found that the contribution of the toe lift was relatively high.
According to the above preferred configuration, the third regression equation is a multiple regression equation in which the hip bending with the highest contribution is an independent variable and the toe rise with a relatively high contribution is also an independent variable. It is possible to calculate a walking age that more closely matches the walking ability.

  Preferably, the plurality of body feature points further include left and right elbows and left and right wrists, and the plurality of walking parameters include three-dimensional measurements of the thoracolumbar, the left and right elbows, and the left and right wrists. The elbow swing calculated using coordinates is further included, and the third regression equation included in the first correspondence relation includes at least the hip bending and the elbow swing as independent variables, and the posture It is a multiple regression equation with age as a dependent variable.

According to a study by the present inventors, in the regression analysis for calculating the third regression equation with posture age as a dependent variable, when various walking parameters were used as independent variables, the bending of the waist contributed most. Although the degree was high, it was found that the elbow swing contributed relatively well.
According to the above preferred configuration, the third regression equation is a multiple regression equation in which the hip bending with the highest contribution is an independent variable and the elbow swing with a relatively high contribution is also an independent variable. It is possible to calculate a walking age that more closely matches the walking ability.

  Preferably, the analysis device includes a speed age correction formula for correcting the speed age, a balance age correction formula for correcting the balance age, and a posture age correction formula for correcting the posture age. Is stored in advance, and the velocity age correction formula divides the actual age of a plurality of humans into a younger age group and an older age group that is older than the younger age group, , The independent variable is the actual age of the human belonging to the younger generation, and the dependent variable is the actual age determined by the difference from the regression line calculated by regression analysis as the velocity age calculated for the human belonging to the younger generation. A speed age correction formula for young people to calculate a correction term with age as a variable, the actual age of a human belonging to the elderly, the independent variable as the actual age of a human belonging to the elderly, and the dependent variable as To the elderly It is composed of a velocity age correction formula for the elderly for calculating a correction term with the actual age as a variable, which is obtained by the difference from the regression line calculated by regression analysis as the velocity age calculated for the human being The balance age correction formula divides the actual age of a plurality of humans into a younger age group and an older age group that is older than the young age group, and the actual age of the human belonging to the young age group and the independent variable are The actual age of a human belonging to a young group is used, and the dependent age is corrected as a variable, which is determined by the difference from the regression line calculated by performing a regression analysis as the balance age calculated for the human belonging to the young group. Balance age correction formula for young people to calculate the term, the actual age of the human belonging to the older age, the independent variable as the actual age of the human belonging to the older age, and the dependent variable as the older age Consists of a balance age correction formula for the elderly to calculate a correction term using the actual age as a variable, which is obtained by the difference from the regression line calculated by performing a regression analysis as the balance age calculated for the person to which it belongs The posture age correction formula divides the real age of a plurality of humans into a younger age group and an older age group that is older than the young age group, and the actual age of the human belonging to the young age group and the independent variable are The actual age of a human belonging to a young group is used, and the dependent variable is corrected as a variable calculated by the difference from the regression line calculated by performing regression analysis as the posture age calculated for the human belonging to the young group. The posture age correction formula for young people to calculate the term, the actual age of the human belonging to the older age, the independent variable as the actual age of the human belonging to the older age, and the dependent variable to the older age Genus It is composed of a posture age correction formula for elderly people for calculating a correction term using the actual age as a variable, which is obtained by the difference from the regression line calculated by performing regression analysis as the posture age calculated for the human being The analysis device selects one of the correction age formulas according to the input subject's actual age among the young age velocity age correction formula and the senior age velocity age correction formula, By adding the correction term obtained by substituting the actual age of the subject into the selected correction formula to the calculated speed age of the subject, the speed age of the subject is corrected, and the balance age correction formula for the younger generation And any one of the balance age correction formulas for seniors according to the input actual age of the subject, and the actual age of the subject is substituted into the selected correction formula. Complement By adding the term to the calculated balance age of the subject, the balance age of the subject is corrected and the posture age correction formula for the younger group and the posture age correction formula for the older group are input. By selecting one of the correction formulas according to the actual age of the subject and adding the correction term obtained by substituting the actual age of the subject into the selected correction formula to the calculated posture age of the subject The posture age of the subject is corrected, the corrected velocity age of the subject, the balance age of the subject after correction, and the posture age of the subject after correction, and the second correspondence relationship stored in advance. Are used to calculate the walking age of the subject.

According to the study by the present inventors, the correlation between the actual age of a plurality of humans and each age of the speed age, balance age and posture age is as follows: the younger age group, the older age group than the younger age group. It turned out that it becomes a different tendency with a stratum. Therefore, when correcting the average speed age, balance age, and posture age of multiple humans so that they approximate the actual age, the speed age, balance age, and posture age calculated by the walking parameters are uniformly set. Rather than correcting, it is preferable to divide into a younger age group and an older age group and correct each separately.
According to the preferred configuration described above, the analysis device selects either the speed age correction formula for the younger age group or the speed age correction formula for the older age group according to the inputted actual age of the subject. The velocity age of the subject is corrected by adding a correction term obtained by substituting the actual age of the subject to the selected correction formula to the calculated velocity age of the subject. The same applies to the balance age and posture age of the subject. For this reason, it is possible to correct the average speed age, balance age, and posture age of a plurality of humans for both younger and older people so that they are closer to the actual age. The walking age of the subject calculated by the speed age, the balance age and the posture age becomes more consistent with the walking ability.

  Preferably, in the analysis device, a score calculation reference formula and a score calculation deviation for calculating a score, which is an index indicating superiority or inferiority of the plurality of walking parameters, are stored in advance for each walking parameter, and the score The reference formula for calculation is the walking parameter reference value with the actual age as a variable, which is calculated by regression analysis with the independent variable as the actual age of a plurality of people and the dependent variable as the walking parameter calculated for the plurality of people. The score calculation deviation is a value obtained by multiplying a standard deviation of the walking parameters calculated for the plurality of humans by a predetermined coefficient, and the analysis apparatus is configured to input the subject. Is calculated by substituting the actual age of the above into the reference formula for calculating the score, and using the three-dimensional coordinates of the body feature points of the subject. The difference between the walking parameter reference value and walking parameter of the subject issued, compared to the score calculation deviation, calculates a preset score in accordance with the magnitude as a score of the walking parameter of the subject.

  According to said preferable structure, the reference formula for score calculation for calculating the value (walking parameter reference value) of each average walking parameter according to the real age of several persons, and each walking about several persons Using the value related to the standard deviation of the parameter (deviation for score calculation), the level of each walking parameter value of the subject is at an average level for each walking parameter according to the actual age of the subject. Therefore, it can be expected that this leads to improvement in the consciousness of the subject with respect to improvement in walking ability.

The present invention is also provided as a configuration in which the analysis device calculates only the walking parameter score without calculating the walking age.
That is, the present invention uses a three-dimensional measuring apparatus that sequentially measures three-dimensional coordinates of a plurality of predetermined body feature points of a subject as the subject walks, and the three-dimensional coordinates of the body feature points, An analysis device that calculates a plurality of walking parameters of a subject, and the analysis device has a score calculation reference formula and a score calculation deviation for calculating a score that is an index indicating superiority or inferiority of the plurality of walking parameters. Preliminarily stored for each walking parameter, the analysis device calculates a walking parameter reference value by substituting the input actual age of the subject into the reference formula for score calculation, and the physical feature points of the subject The difference between the walking parameter of the subject calculated using the three-dimensional coordinates and the walking parameter reference value is compared with the deviation for score calculation, and is set in advance according to the magnitude thereof. Calculating the core as a score of the walking parameter of the subject, it is also provided as walking analysis system, characterized in that.

  Furthermore, the present invention is calculated using a three-dimensional measurement step of sequentially measuring three-dimensional coordinates of a plurality of predetermined body feature points of the subject as the subject walks, and the three-dimensional coordinates of the body feature points. Or a first correspondence relationship between a plurality of walking parameters and speed age, balance age, and posture age calculated using other methods, and a first correspondence relationship between the speed age, the balance age, the posture age, and the walking age. 2 correspondence relations are stored in advance, and calculated using the three-dimensional coordinates of a plurality of body feature points of the subject measured by the three-dimensional measurement process or calculated using another method. The speed age, balance age and posture age of the subject are calculated using a plurality of walking parameters and the first correspondence relationship stored in advance, and the calculated speed age, balance age and appearance of the subject are calculated. An analysis step of calculating the walking age of the subject using the age and the second correspondence relationship stored in advance, and the plurality of walking parameters include at least a walking speed and a left-right difference in walking rhythm. The first correspondence relationship includes a first regression equation having the walking speed as an independent variable and the speed age as a dependent variable, and at least a left-right difference in the walking rhythm as an independent variable. A gait analysis method comprising: a second regression equation having the balance age as a dependent variable; and a third regression equation having at least the hip bending as an independent variable and the posture age as a dependent variable. Also provided as

  In order to solve the above-mentioned problem, the present invention provides a three-dimensional measuring apparatus that sequentially measures three-dimensional coordinates of a plurality of predetermined body feature points of a subject as the subject walks, and 3 of the body feature points. Correspondences between a plurality of walking parameters calculated using dimensional coordinates or using other techniques and appearance ages are stored in advance, and a plurality of bodies of the subject measured by the three-dimensional measuring device The apparent age of the subject is calculated using the plurality of walking parameters of the subject calculated using the three-dimensional coordinates of the feature points or calculated using another method and the correspondence relationship stored in advance. The plurality of walking parameters include at least walking speed, hip bending, and hip rotation, and the correspondence relationship includes at least the walking speed and the hip bending. When, the rotation of the waist as independent variables, the represented the appearance age multiple regression equation as the dependent variable, to provide a gait analysis system, characterized in that.

According to the walking analysis system according to the present invention, the apparent age is calculated using walking speed, hip bending and hip rotation as walking parameters. For this reason, the walking state can be comprehensively evaluated, and the appearance age that matches the walking posture can be calculated.
The multiple regression equation can be calculated by performing regression analysis with the dependent variable as the appearance age determined by a third party for a plurality of humans and the independent variable as each walking parameter calculated for the plurality of humans. .

  Preferably, the plurality of body feature points include at least thoracolumbar, the center of the pelvis, and the left and right pelvises, and whether the walking speed is calculated using the three-dimensional coordinates of the thoracolumbar Alternatively, the hip bend is calculated using the center three-dimensional coordinates of the thoracolumbar and the pelvis, and the hip rotation is calculated using the three of the thoracolumbar and the left and right pelvis. Calculated using dimensional coordinates.

  The body feature point thoracolumbar, the center of the pelvis, and the left and right pelvis used in the above preferred configuration are, for example, a markerless three-dimensional coordinate system by using Kinect (registered trademark) manufactured by Microsoft Corporation in the United States. Can be measured, and thus has an advantage of easy measurement.

  Preferably, the plurality of body feature points further include left and right knees, left and right ankles, left and right toes, and a head, and the plurality of walking parameters include a left-right difference in walking angle and a head. At least one of a back-and-forth swing, a walking angle, and a lateral shaking of the head is further included, and the left-right difference in the walking angle is the thoracolumbar, the left and right pelvis, and the left and right Calculated using the three-dimensional coordinates of the knee, calculated using the three-dimensional coordinates of the thoracolumbar, the left and right knees and the left and right ankles, or the thoracolumbar, the left and right ankles and the It is calculated using the three-dimensional coordinates of the left and right toes, and the shaking of the head in the front-rear direction is calculated using the three-dimensional coordinates of the thoracolumbar, the center of the pelvis and the head, and the walking angle is calculated using the chest Calculated using the three-dimensional coordinates of the waist, the left and right pelvis and the left and right knees, Calculated using the three-dimensional coordinates of the chest and waist, the left and right knees and the left and right ankles, or calculated using the three-dimensional coordinates of the chest and waist, the left and right ankles and the left and right toes, The lateral shaking of the head is calculated using the three-dimensional coordinates of the thoracolumbar, the center of the pelvis and the head, and the correspondence relationship includes the walking speed, the bending of the hips and the rotation of the hips. A multiple regression equation in which at least one of the left-right difference of the walking angle, the shaking of the head in the longitudinal direction, the walking angle and the shaking of the head in the lateral direction is an independent variable, and the apparent age is a dependent variable. expressed.

According to the study by the present inventors, in the regression analysis for calculating the multiple regression equation with the apparent age as the dependent variable, various walking parameters were used as independent variables, and the walking speed, hip bending and hip Next, it was found that although the contribution of rotation of the head is high, the difference in the walking angle, the head shaking in the front-rear direction, the walking angle and the shaking in the lateral direction of the head are also relatively high.
According to the above preferred configuration, the multiple regression equation makes the walking speed with high contribution, the bending of the hips and the rotation of the hips as independent variables, the left-right difference of the walking angle with relatively high contribution, and the front-rear direction of the head. Since it is a multiple regression equation in which at least one of shaking, walking angle, and lateral shaking of the head is an independent variable, it is possible to calculate a visual age that more closely matches the walking posture.

  Further, the present invention is calculated using a three-dimensional measurement step of sequentially measuring three-dimensional coordinates of a plurality of predetermined body feature points of the subject as the subject walks, and the three-dimensional coordinates of the body feature points. Or the three-dimensional coordinates of the plurality of body feature points of the subject measured in the three-dimensional measurement step, in which correspondence relationships between the plurality of walking parameters calculated using other methods and the apparent age are stored in advance. A plurality of gait parameters of the subject calculated using or using the other method, and an analysis step of calculating the apparent age of the subject using the correspondence stored in advance, The plurality of walking parameters include at least walking speed, hip bending, and hip rotation, and the correspondence relationship includes at least the walking speed, hip bending, and hip rotation. Germany A variable, represented by the above multiple regression equation the look age as the dependent variable, are provided as a walking analysis wherein the.

  In order to solve the above-mentioned problem, the present invention provides a three-dimensional measuring apparatus that sequentially measures three-dimensional coordinates of a plurality of predetermined body feature points of a subject as the subject walks, and 3 of the body feature points. Correspondences between a plurality of walking parameters calculated using dimensional coordinates or calculated using other methods and beauty posture evaluation values, which are indices representing the beauty of the walking posture, are stored in advance. The plurality of walking parameters of the subject calculated using the three-dimensional coordinates of the plurality of body feature points of the subject measured by the dimension measuring device or calculated using other methods, and the correspondence stored in advance An analysis device that calculates a beauty posture evaluation value of the subject using a relationship, and the plurality of walking parameters include at least a forward tilt posture, a walking speed, and an elbow swing, The relationship is small Both of the forward leaning posture, the walking speed, and the elbow swing are independent variables, and the walking analysis system is represented by a multiple regression equation with the beautiful posture evaluation value as a dependent variable. Is also provided.

According to the walking analysis system of the present invention, the beauty posture evaluation value is calculated using the forward tilt posture, the walking speed, and the elbow swing as the walking parameters. Therefore, the walking state can be comprehensively evaluated, and the beautiful posture evaluation value that matches the walking posture can be calculated.
The multiple regression equation can be calculated by performing a regression analysis as a pose evaluation value determined by a third party for a plurality of persons as a dependent variable, and as each walking parameter calculated for the plurality of persons as an independent variable. It is.

  Preferably, the plurality of body feature points include at least thoracolumbar, pelvic center, head, left and right elbows, and left and right wrists. Calculated using the three-dimensional coordinates of the center of the pelvis, or calculated using the three-dimensional coordinates of the thoracolumbar, the center of the pelvis and the head, and the walking speed is calculated using the three-dimensional coordinates of the thorax The elbow swing is calculated using the three-dimensional coordinates of the chest and hips, the left and right elbows, and the left and right wrists.

  For example, Kinect (registered trademark) manufactured by Microsoft Corporation of the United States, which is one of commercially available devices, is used for thoracolumbar, the center of the pelvis, the head, the left and right elbows, and the left and right wrists used in the above preferred configuration. Since the three-dimensional coordinates can be measured without a marker, there is an advantage that the measurement is easy.

  Preferably, the plurality of body feature points further include left and right pelvis, left and right knees, left and right ankles, left and right toes, and left and right shoulders, and the plurality of walking parameters include walking Left / right difference in angle, walking angle, left / right difference in walking rhythm, lateral shaking of the head, hip rotation, lateral tilt of the head, shin fall, thigh lift, and toe At least any one of a rise, a step, and a frontal face angle is further included, and the left-right difference of the walking angle and the walking angle are measured on the thoracolumbar, the left and right pelvis, and the left and right knees. Calculated using three-dimensional coordinates, calculated using the three-dimensional coordinates of the thoracolumbar, the left and right knees and the left and right ankles, or the thoracolumbar, the left and right ankles and the left and right It is calculated using the three-dimensional coordinates of the toes, and the left-right difference of the walking rhythm is the three-dimensional seat of the thoracolumbar The lateral shaking of the head is calculated using the three-dimensional coordinates of the thoracolumbar, the center of the pelvis and the head, and the rotation of the hips is calculated using the thoracolumbar and the left and right pelvis The lateral inclination of the head is calculated using the three-dimensional coordinates of the thoracolumbar, the center of the pelvis and the head, and the shin fall is calculated using the thoracolumbar, The three-dimensional coordinates of the left and right knees and the left and right ankles are calculated, and the rise of the thigh is calculated using the three-dimensional coordinates of the thoracolumbar, the left and right pelvis and the left and right knees, and the toes The ascending is calculated using the three-dimensional coordinates of the thoracolumbar and the left and right toes, and the step is calculated using the three-dimensional coordinates of the thoracolumbar and the left and right ankles, Uses the three-dimensional coordinates of the chest and waist, the left and right shoulders and the left and right elbows The correspondence relationship is calculated as follows: the forward tilt posture, the walking speed and the swing of the elbow, the left-right difference of the walking angle, the walking angle, the left-right difference of the walking rhythm, the lateral shaking of the head, Rotation of the hips, lateral tilt of the head, tilting of the shin, raising of the thighs, raising of the toes, the step and the frontal face angle are defined as independent variables, and the beauty It is expressed by a multiple regression equation with the posture evaluation value as a dependent variable.

According to a study by the present inventors, in the regression analysis for calculating a multiple regression equation using the beauty posture evaluation value as a dependent variable, various walking parameters were used as independent variables. Although the contribution of speed and elbow swing is high, then the difference in walking angle, walking angle, difference in walking rhythm, lateral shaking of the head, rotation of the hips, lateral tilt of the head, shin fall It was also found that the thigh lift, toe lift, step distance and frontal face value were also relatively high.
According to the preferred configuration described above, the multiple regression equation makes the forward leaning posture with high contribution, walking speed and elbow swing as independent variables, and the difference between left and right walking angles, walking angle, walking with relatively high contribution. At least one of rhythmic left / right difference, horizontal shaking of the head, hip rotation, horizontal tilting of the head, tilting of the shin, rising of the thigh, rising of the toe, step distance and frontal face angle of the shoulder Is also a multiple regression equation with independent variables, so that it is possible to calculate a beauty posture evaluation value that more closely matches the walking posture.

  Further, the present invention is calculated using a three-dimensional measurement step of sequentially measuring three-dimensional coordinates of a plurality of predetermined body feature points of the subject as the subject walks, and the three-dimensional coordinates of the body feature points. Or a correspondence relationship between a plurality of walking parameters calculated using other methods and a beauty posture evaluation value that is an index representing the beauty of the walking posture is stored in advance and measured by the three-dimensional measurement process. The subject using the plurality of walking parameters of the subject calculated using the three-dimensional coordinates of the plurality of body feature points of the subject or using other methods and the correspondence relationship stored in advance. And a plurality of walking parameters including at least a forward tilt posture, a walking speed, and an elbow swing, and the correspondence relationship includes at least the front Leaning posture, Serial and walking speed, and swing as independent variables of the elbow, the beauty represented posture evaluation value in multiple regression equation as the dependent variable, are provided as a walking analysis wherein the.

  According to the present invention, by making it possible to comprehensively evaluate the walking state of the whole body, it is possible to calculate the walking age that matches the walking ability. Further, according to the present invention, it is possible to calculate the appearance age that matches the walking posture. Furthermore, according to the present invention, it is possible to calculate a beauty posture evaluation value that matches the walking posture.

It is a figure showing a schematic structure of a walk analysis system concerning a 1st embodiment of the present invention. It is a flowchart which shows schematic operation | movement of the walk analysis system which concerns on 1st Embodiment. It is explanatory drawing for demonstrating derivation | leading-out of the correction formula in 1st Embodiment. It is explanatory drawing for demonstrating the score calculation procedure of the walking speed which is one of the walking parameters in 1st Embodiment. It is a figure which shows an example of the result of having calculated the apparent age by the walk analysis system which concerns on 2nd Embodiment. It is a figure which shows an example of the result of having calculated the beauty posture evaluation value by the walk analysis system which concerns on 3rd Embodiment.

[First Embodiment]
Hereinafter, a walking analysis system according to a first embodiment of the present invention will be described with reference to the accompanying drawings as appropriate.
FIG. 1 is a diagram showing a schematic configuration of a gait analysis system according to the first embodiment of the present invention. FIG. 1A is a diagram showing a schematic configuration, FIG. 1B is a diagram illustrating a coordinate system used in the walking analysis system according to the first embodiment, and FIG. 1C is the first embodiment. It is a figure explaining the example of the body feature point measured with the gait analysis system concerning.
As shown in FIG. 1A, the gait analysis system 100 according to the first embodiment includes a three-dimensional measurement device 1 and an analysis device 2. First, a schematic configuration of the walking analysis system 100 will be described.

<Schematic configuration of walking analysis system 100>
The three-dimensional measuring apparatus 1 includes an optical system 11 including an infrared irradiation unit, a camera, and the like, and a program for processing a signal obtained by the optical system (a program installed in the analysis apparatus 2). Is a device that sequentially measures the three-dimensional coordinates of a plurality of predetermined body feature points as the subject H walks. As the three-dimensional measuring apparatus 1, an optical three-dimensional measuring apparatus that measures the three-dimensional coordinates of the body feature point without using the marker, and the body feature based on the triangulation using the optical system 11 and the time of flight as the measurement principle. Various commercially available devices such as an optical three-dimensional measuring device that calculates a three-dimensional coordinate of a body feature point by attaching a marker to the point and measuring the three-dimensional coordinate of the marker can be applied. Use of Kinect (registered trademark) manufactured by Microsoft Corporation, one of the commercially available devices, as the three-dimensional measuring device 1 is advantageous in that the measurement is easy because it is possible to measure three-dimensional coordinates without a marker. Is preferred.
Note that various known procedures can be applied to the specific procedure for calculating the three-dimensional coordinates, and therefore the description of the specific content is omitted in this specification. In the first embodiment, an example in which a program for calculating three-dimensional coordinates of a body feature point is installed in the analysis apparatus 2 will be described as an example. However, the present invention is not limited to this, and three-dimensional An apparatus (such as a personal computer) for installing a program for calculating coordinates and the analysis apparatus 2 may be separated.

  As shown in FIG. 1 (c), the body feature points in the present invention are the four-legged joint, the center of the head, shoulder, trunk, pelvis, foot, heel, rib, upper anterior iliac spine, and toe of the foot. Means. However, the body feature points measured by the three-dimensional measuring apparatus 1 of the first embodiment need not be all of these parts, and may be a plurality of predetermined body feature points. For example, it is preferable that the plurality of body feature points measured by the three-dimensional measurement apparatus 1 according to the first embodiment include at least the thoracolumbar (center of the trunk) and the center of the pelvis.

  The analysis device 2 of the first embodiment calculates the walking age of the subject H using the three-dimensional coordinates of the plurality of body feature points of the subject H measured by the three-dimensional measurement device 1. Specifically, the analysis device 2 is configured by, for example, a general-purpose personal computer in which a program for calculating a walking age using three-dimensional coordinates of a plurality of body feature points is installed.

<Operation of walking analysis system 100>
Hereinafter, the operation (walking analysis method) of the walking analysis system 100 having the above-described schematic configuration will be described with reference to FIGS. 2 to 4 as appropriate.
FIG. 2 is a flowchart showing a schematic operation of the gait analysis system 100 according to the first embodiment.
As shown in FIG. 2, when performing the walking analysis of the subject H, first, information such as the actual age of the subject H is input to the analysis device 2 (S1 in FIG. 2). The input information of the subject H is stored in a storage device such as a semiconductor memory or a hard disk drive mounted on the analysis device 2. Or you may make it preserve | save the information of the test subject H in a place different from the analysis apparatus 2 using a cloud storage service etc.

  Next, when the subject H starts walking (S2 in FIG. 2), the three-dimensional measuring apparatus 1 sequentially measures the three-dimensional coordinates of a plurality of predetermined body feature points of the subject H as the subject H walks. A three-dimensional measurement process is executed (S3 in FIG. 2). When the subject H finishes walking a predetermined distance (S4 in FIG. 2), the measurement is completed, and the measurement result is stored in the analysis device 2.

  Next, the analysis apparatus 2 executes the analysis process using the stored measurement results, that is, the three-dimensional coordinates of a plurality of body feature points sequentially measured for the subject H (S5 in FIG. 2). Hereinafter, specific contents of the analysis step S5 will be sequentially described.

  In the analysis step S5, the analysis device 2 according to the first embodiment first uses, as walking parameters, at least a walking speed and a left-right difference in walking rhythm using the three-dimensional coordinates of a plurality of body feature points of the subject H. The hip bending is calculated (S51 in FIG. 2).

The walking speed means a speed when the subject H walks, and is calculated from, for example, a value obtained by dividing a predetermined distance by a time required to walk in a predetermined direction. In the first embodiment, an average value in one walking cycle of a value obtained by dividing the forward displacement of one body feature point for each measurement cycle of the three-dimensional measuring apparatus 1 by the measurement cycle is calculated as the walking speed. For example, when this one body feature point is the chest and waist, the walking speed is an average value obtained by dividing the forward displacement of the chest and waist in one walking cycle by the measurement cycle, and the chest and waist measured by the three-dimensional measuring device 1. It is possible to calculate using the three-dimensional coordinates. Note that the measurement cycle of the three-dimensional measuring apparatus 1 is, for example, the reciprocal of the frame rate when Kinect (registered trademark) is used as the three-dimensional measuring apparatus 1, and is about 1/30 second.
“One walking cycle” means a time interval from the first minimum value to the third minimum value of the vertical displacement of one body feature point. When this one body feature point is chest and waist, one walking cycle is a time interval from the first minimum value to the third minimum value of the vertical displacement of the chest and waist. “Forward” may be determined in advance, for example, by uniquely determining in advance the direction in which the subject H should walk toward the three-dimensional measuring apparatus 1 (see FIG. 1B). In the above example, the forward displacement of one body feature point for calculating the walking speed is the forward displacement of the chest and hips, but the present invention is not limited to this, the forward displacement of the center of the pelvis, It may be a forward displacement at the center of the foot (described as “right foot” and “left foot” in FIG. 1C). In the above example, the minimum value of the vertical displacement of one body feature point for calculating one walking cycle is the minimum value of the vertical displacement of the thoracolumbar, but the present invention is not limited to this. Also, the minimum value of the vertical displacement at the center of the foot, the minimum value of the vertical displacement of the ankle, the minimum value of the vertical displacement at the center of the pelvis, the minimum value of the vertical displacement of the heel, etc. can be used. The three-dimensional coordinates of the thoracolumbar, the center of the pelvis, the center of the foot, and the ankle can be measured without markers using Kinect (registered trademark). The three-dimensional coordinates of the heel are obtained by using an optical motion capture system (for example, Vicon (registered trademark) manufactured by VICON) using the marker as the three-dimensional measuring apparatus 1 and attaching the marker to the heel. It can be measured by measuring dimensional coordinates.

  The left / right difference in walking rhythm means the left / right difference in the grounding timing of walking. For example, the time interval between the left foot touching the ground and the right foot touching (hereinafter referred to as the “left and right grounding time interval”) and the right foot Defined by the absolute value of the difference from the time interval until the left foot touches the ground (hereinafter referred to as the “right-left contact time interval”), using the three-dimensional coordinates of one body feature point measured by the three-dimensional measuring device 1 Can be calculated. For example, when this one body feature point is the chest and waist, when the vertical displacement of the chest and waist (a positive value in the vertical direction) is a minimum value, the left and right feet alternately touch the floor. Thinking, either left or right grounding time interval or right and left grounding time interval is calculated by the time interval from the first minimum value to the second minimum value from the start of measurement, left and right grounding time interval and right and left grounding time interval Any one of these may be calculated by the time interval from the second minimum value to the third minimum value. In the above example, the minimum value of the vertical displacement of the chest and hips is used to determine that the left and right feet are in contact with the floor, but the present invention is not limited to this, and the vertical center of the feet is not limited to this. It is also possible to set the minimum value of the directional displacement, the minimum value of the vertical displacement of the ankle, the minimum value of the vertical displacement at the center of the pelvis, the minimum value of the vertical displacement of the heel, or the like.

  The curvature of the waist means the degree of bending of the waist during walking, for example, the average value of the angle formed by the vertical axis and the straight line connecting the thoraco-lumbar projected on the sagittal plane and the center of the pelvis in one walking cycle, Or, it is defined by the average value of the angle formed between the straight axis connecting the center of the rib projected onto the sagittal plane and the center of the superior anterior iliac spine and the vertical axis, and the thoracolumbar and pelvis measured by the three-dimensional measuring apparatus 1 It can be calculated using the center three-dimensional coordinates or the center of the ribs and the center of the superior anterior iliac spine. As shown in FIG. 1B, the sagittal plane means a plane including a front-rear axis (an axis extending forward and rearward) and a vertical axis. Note that the three-dimensional coordinates of the center of the rib are, for example, Vicon (registered trademark) as the three-dimensional measuring device 1, and markers are attached to the lower left and right edges of the rib, as shown in FIG. Measurement (calculation) is possible by measuring the three-dimensional coordinates of the marker. Similarly, for the three-dimensional coordinates of the center of the upper anterior iliac spine, for example, Vicon (registered trademark) is used as the three-dimensional measuring apparatus 1, and as shown in FIG. Can be measured (calculated) by measuring the three-dimensional coordinates of each marker.

In the above description, the case where walking parameters (walking speed, walking rhythm difference, hip bending) are calculated using the 3D coordinates of the body feature points measured by the 3D measuring apparatus 1 has been described as an example. However, the present invention is not limited to this, and the walking parameters can be calculated using other methods.
For example, in order to calculate the walking speed, the time required for the subject H to walk a predetermined distance in a predetermined direction is manually measured with a stopwatch, or photoelectrics installed at the start and end points of walking. Automatic measurement may be performed based on the timing of crossing the switch. It is also possible to calculate the walking speed by inputting the time measured manually or automatically to the analyzer 2 and dividing the predetermined distance by the input time.
In addition, for example, a portable information terminal such as a smartphone is carried by the subject H, and the moving distance and moving time of the subject H measured using a GPS tracking application activated on the portable information terminal are input to the analyzing apparatus 2, and the analyzing apparatus It is also possible to calculate the walking speed by dividing the movement distance input by 2 by the movement time.
Further, for example, the subject H carries or attaches a sensor capable of measuring acceleration, such as a motion sensor, inputs the acceleration measured by the sensor to the analysis device 2, and the analysis device 2 integrates the input acceleration to walk. It is also possible to calculate the speed.

  The analysis apparatus 2 according to the first embodiment includes, as walking parameters, the above-described three parameters of walking speed, walking rhythm left-right difference and hip bending, walking angle left-right difference, thigh rise left-right difference, shoulder horizontal angle. Further, the walking angle, the toe lift and the elbow swing are further calculated (S51 in FIG. 2).

The left-right difference in walking angle means the left-right difference in the direction of the leg during walking, and is expressed by, for example, any one of the left-right difference in the walking angle knee, the left-right difference in the walking angle shin, and the left-right difference in the walking angle toe. The
The left-right difference in the walking angle knee means the left-right difference in the orientation of the knee during walking. For example, in one walking cycle, a straight line connecting the left pelvis and the left knee projected on the horizontal plane when the left foot is grounded and the front-rear axis The absolute value of the difference between the angle formed by and the angle formed by the anteroposterior axis and the straight line connecting the right pelvis and the right knee projected on the horizontal plane when the right foot touches the ground (however, each angle is relative to the anteroposterior axis) It can be calculated using the three-dimensional coordinates of the chest and hips, the left and right pelvises, and the left and right knees measured by the three-dimensional measuring apparatus 1. As shown in FIG. 1B, the horizontal plane means a plane that includes the front-rear axis and is orthogonal to the vertical axis. In addition, the three-dimensional coordinates of the left and right pelvis and the left and right knees can be measured without markers using Kinect (registered trademark).
The left-right difference in the walking angle shin means the left-right difference in the direction of the shin during walking. For example, in one walking cycle, the straight line connecting the left knee and the left ankle projected on the horizontal plane when the left foot touches down, and the front-rear axis The absolute value of the difference between the angle formed by and the angle formed by the straight axis connecting the right knee and the right ankle projected on the horizontal plane when the right foot touches the ground and the front and rear axes (however, each angle is relative to the front and rear axes) It is defined by a positive value when the ankle side is inclined outward, and can be calculated using the three-dimensional coordinates of the chest and waist, the left and right knees, and the left and right ankles measured by the three-dimensional measuring apparatus 1.
The left-right difference of the walking toe means the left-right difference in the direction of the toe of the foot during walking. For example, in one walking cycle, the straight line connecting the left ankle and the left toe projected on the horizontal plane when the left foot is grounded Absolute value of the difference between the angle formed by the front and rear axes and the angle formed by the front and rear axes and the straight line connecting the right ankle and the right toe projected on the horizontal plane when the right foot touches the ground (however, each angle is On the other hand, it is defined as a positive value when the toe side is inclined outward), and can be calculated using the three-dimensional coordinates of the chest and waist, the left and right ankles, and the left and right toes measured by the three-dimensional measuring apparatus 1. Note that the three-dimensional coordinates of the left and right toes can be measured without markers using Kinect (registered trademark).

  The left-right difference in thigh lift means the left-right difference in thigh lift during walking. For example, in one walking cycle, the straight axis connecting the left pelvis projected on the sagittal plane and the left knee and the vertical axis Of the angle formed by the angle (difference between the maximum and minimum values) and the angle of rotation formed by the vertical axis and the straight line connecting the right pelvis and the right knee projected on the sagittal plane (maximum and minimum) The absolute value of the difference between the two values (however, each angle is defined as a positive value when the knee side of the straight line connecting the pelvis and the knee is inclined forward), and the three-dimensional measuring device 1 It can be calculated using the three-dimensional coordinates of the chest and waist, the left and right pelvis, and the left and right knees measured in step (1).

  The horizontal shoulder angle means how the left and right shoulders fall during walking. For example, in one walking cycle, the absolute value of the average value of the angle formed by the straight line connecting the left and right shoulders projected on the frontal plane and the left and right axes ( However, the angle is defined as a positive value when the right shoulder side of the straight line connecting the left and right shoulders is tilted vertically downward with respect to the left and right axis), and the thoracolumbar and the left and right sides measured with the three-dimensional measuring apparatus 1 are defined. It can be calculated using the three-dimensional coordinates of the shoulder. As shown in FIG. 1B, the left-right axis means an axis that is included in the horizontal plane and is orthogonal to the front-rear axis. As shown in FIG. 1B, the front face means a plane including the front and rear axes and the vertical axis. Note that the three-dimensional coordinates of the left and right shoulders can be measured without markers using Kinect (registered trademark).

The walking angle means the direction of the leg during walking, and is expressed by any one of a walking angle knee, a walking angle shin, and a walking angle toe, for example.
The walking angle knee means the direction of the knee during walking, for example, in one walking cycle, the angle formed by the straight line connecting the left pelvis and the left knee projected on the horizontal plane at the time of ground contact with the left foot and the anteroposterior axis, The average value of the angle formed by the straight line connecting the right pelvis and the right knee projected on the horizontal plane when the right foot is touched, and the anteroposterior axis. The case is defined as a positive value) and can be calculated using the three-dimensional coordinates of the thoracolumbar, the left and right pelvis, and the left and right knees measured by the three-dimensional measuring apparatus 1.
The walking angle shin means the direction of the shin during walking, for example, in one walking cycle, the angle formed by the straight line connecting the left knee and the left ankle projected on the horizontal plane at the time of ground contact with the left foot and the front and rear axes, The average value of the angle formed by the straight axis connecting the right knee and the right ankle projected on the horizontal plane when the right foot touches the ground and the front and rear axes (however, each angle is tilted outward from the front and rear axes) The case is defined as a positive value) and can be calculated using the three-dimensional coordinates of the chest, waist, left and right knees, and left and right ankles measured by the three-dimensional measuring apparatus 1.
The walking angle toe means the direction of the toe of the foot during walking. For example, in one walking cycle, the angle formed by the straight line connecting the left ankle and the left toe projected on the horizontal plane when the left foot is touched and the front and rear axes And the angle formed by the straight line connecting the right ankle and the right toe projected on the horizontal plane when the right foot is in contact with the front and rear axes (however, each toe side is inclined outward with respect to the front and rear axes) And can be calculated using the three-dimensional coordinates of the chest and hips, the left and right ankles, and the left and right toes measured by the three-dimensional measuring apparatus 1.

  The rise of the toe means the degree of the rise of the toe during walking. For example, in one walking cycle, the maximum value of the height (vertical distance) of the left toe located in front of the floor and the front It is defined by the average value of the height of the right toe from the floor surface and can be calculated using the three-dimensional coordinates of the chest and waist and the left and right toes measured by the three-dimensional measuring apparatus 1. Note that the floor is a plane parallel to the horizontal plane, and the position in the vertical direction may be stored in the analyzer 2 in advance.

The swing of the elbow means how the arm swings during walking, and is expressed by one of an elbow sagittal plane angle and an elbow frontal plane angle, for example.
The elbow sagittal plane angle is, for example, the swing width of the angle formed by the vertical axis and the straight line connecting the left elbow and the left wrist projected on the sagittal plane in one walking cycle (the difference between the maximum value and the minimum value). ) And the angle swing (difference between the maximum and minimum values) formed by the straight axis connecting the right elbow and the right wrist projected on the sagittal plane and the vertical axis (however, each angle is , Defined as a positive value when the wrist side of the straight line connecting the elbow and the wrist is inclined forward), and the three-dimensional coordinates of the chest, waist, left and right elbows, and left and right wrists measured by the three-dimensional measuring device 1 And can be calculated.
The elbow front face angle is, for example, the swing width (difference between the maximum and minimum values) of the angle formed by the straight line connecting the left elbow and the left wrist projected on the front face and the vertical axis in one walking cycle. The average value of the angle swing (difference between the maximum value and the minimum value) formed by the straight axis connecting the right elbow and the right wrist projected on the front face and the vertical axis (however, each angle is the Calculated by using the three-dimensional coordinates of the chest, hips, left and right elbows, and left and right wrists measured by the three-dimensional measuring device 1. Is possible.
Note that the three-dimensional coordinates of the left and right elbows and the left and right wrists can be measured without markers using Kinect (registered trademark).

Next, in the analysis step S5, the analysis device 2 of the first embodiment uses at least the walking speed, which is a walking parameter, the left-right difference of the walking rhythm and the hip bending, and the first correspondence relationship stored in advance. The speed age, balance age, and posture age of H are calculated (S52 in FIG. 2).
Here, the “first correspondence relationship” is a correspondence relationship between a plurality of walking parameters, speed age, balance age, and posture age. The “speed age” is one evaluation index of walking ability that indicates how many years it corresponds to when evaluating the speed during walking. “Balance age” is an evaluation index of walking ability that represents how many years old corresponds to when the left and right balance during walking is evaluated. “Posture age” is an evaluation index of walking ability that indicates how many years of age it corresponds to when evaluating posture during walking.
The first correspondence relationship includes a first regression equation in which walking speed is an independent variable and speed age is a dependent variable, and a second regression equation in which at least a left-right difference in walking rhythm is an independent variable and balance age is a dependent variable. And a third regression equation in which at least the hip bending is an independent variable and the posture age is a dependent variable. Then, the analysis device 2 calculates the speed age using the walking speed and the first regression equation, calculates the balance age using at least the left-right difference of the walking rhythm and the second regression equation, and at least the waist bending. Posture age is calculated using the third regression equation.

The first regression equation of the first embodiment is a linear regression equation with the walking speed as an independent variable. That is, when the walking speed as an independent variable is X and the speed age as a dependent variable is Y, the first regression equation is expressed as Y = aX + b (a and b are predetermined constants). The constants a and b of the first regression equation can be calculated by performing regression analysis with the dependent variables as the actual ages of a plurality of persons and the independent variable as the walking speed calculated for the plurality of persons. The plurality of humans (populations) used in the regression analysis for calculating the first regression equation are preferably selected from men and women over a wide range of ages, such as men and women in their 10s and 90s. In the first embodiment, measurement is performed on 100 or more people using the walking analysis system 100, and the first regression equation is calculated.
In the first embodiment, the first regression equation is a linear regression equation. However, the present invention is not limited to this, and a multi-linear regression equation such as a quadratic regression equation or a cubic regression equation is adopted. Is also possible.

The second regression equation of the first embodiment is a linear regression equation having at least a left-right difference in walking rhythm as an independent variable. More specifically, the second regression equation of the first embodiment includes a left-right difference in walking rhythm, a left-right difference in walking angle (specifically, a left-right difference in walking toe), and a left-right difference in thigh lift. In addition, it is a linear regression equation with four parameters of the shoulder horizontal angle as independent variables. In other words, the left and right difference of walking rhythm, the left and right difference of walking angle (walking toe left and right difference), the right and left difference of thigh rise and the shoulder horizontal angle which are independent variables are X1, X2, X3 and X4, respectively. When a certain balance age is Y, the second regression equation is expressed as Y = a1X1 + a2X2 + a3X3 + a4X4 + b (a1 to a4, b are predetermined constants). The constants a1 to a4 and b of the second regression equation are the same as the first regression equation, the dependent variables are the real ages of a plurality of humans, the independent variable is the left-right difference of the walking rhythm calculated for the plurality of humans, the walking It can be calculated by regression analysis as a left-right difference in corners (a difference between left-right differences in walking angle toes), a left-right difference in thigh lift, and a shoulder horizontal angle.
In the first embodiment, the second regression equation is a linear regression equation. However, the present invention is not limited to this, and a multi-linear regression equation such as a quadratic regression equation or a cubic regression equation is adopted. Is also possible.

The third regression equation of the first embodiment is a linear regression equation with at least the waist bend as an independent variable. More specifically, the third regression equation of the first embodiment includes the walking angle (specifically, the walking angle toe), the raising of the toe, and the swing of the elbow (specifically, the elbow) in addition to the bending of the waist. It is a linear regression equation with a total of four parameters (sagittal angle) as independent variables. That is, the independent variables of hip bending, walking angle (walking angle toe), toe lift and elbow swing (elbow sagittal angle) are X1, X2, X3 and X4, respectively, and the posture age as a dependent variable is Assuming Y, the third regression equation is expressed as Y = a1X1 + a2X2 + a3X3 + a4X4 + b (a1 to a4, b are predetermined constants). The constants a1 to a4 and b of the third regression equation are the same as in the first regression equation and the second regression equation, the dependent variable is the actual age of a plurality of humans, and the independent variable is the waist height calculated for the plurality of humans. It can be calculated by regression analysis as bending, walking angle (walking angle toe), ascending toe, and elbow swing (elbow sagittal plane angle).
In the first embodiment, the third regression equation is a linear regression equation. However, the present invention is not limited to this, and a multi-linear regression equation such as a quadratic regression equation or a cubic regression equation is adopted. Is also possible.

  Next, in the analysis step S5, the analysis device 2 of the first embodiment corrects the calculated speed age, balance age, and posture age as a preferred configuration (S53 in FIG. 2). Hereinafter, the correction of the speed age, the balance age, and the posture age will be specifically described.

The analysis device 2 of the first embodiment includes a speed age correction formula for correcting the speed age, a balance age correction formula for correcting the balance age, and a posture age correction formula for correcting the posture age. Stored in advance.
The derivation of these correction equations will be described with reference to FIG. FIG. 3A is a diagram illustrating an example of a correspondence relationship between the actual age and the speed age before correction. FIG. 3B is a diagram illustrating an example of a correspondence relationship between the actual age and the corrected speed age. FIG. 3C is a diagram illustrating an example of a correspondence relationship between the actual age and the walking age calculated using the corrected speed age, the corrected balance age, and the corrected posture age.
As shown in FIG. 3 (a), on the basis of a predetermined age, the actual age of a plurality of humans is represented by a younger age group (corresponding to the data plotted with “◯” in FIG. 3) and a higher age than the younger age group. It is divided into year groups (corresponding to the data plotted with “Δ” in FIG. 3). The regression line calculated by regression analysis using the real age (X) of a human belonging to the younger group as an independent variable and the velocity age (Y) calculated for the human belonging to the younger group as a dependent variable is represented by Y = a1X + b1 (a1 And b1 are predetermined constants). Then, the speed age correction for young people for calculating the correction term using the real age (X) as a variable based on the difference between the real age (Y = X) of the human belonging to the young people and the regression line (Y = a1X + b1). The equation (ΔY1 (X) = X− (a1X + b1)) is obtained. On the other hand, a regression line calculated by regression analysis using the real age (X) of a human belonging to the elderly as an independent variable and the velocity age (Y) calculated for a human belonging to the elderly as a dependent variable is represented by Y = A2X + b2 (a2 and b2 are predetermined constants). Then, the speed for the elderly for calculating the correction term using the actual age (X) as a variable based on the difference between the actual age of the human belonging to the elderly (Y = X) and the regression line (Y = a2X + b2). An age correction formula (ΔY2 (X) = X− (a2X + b2)) is obtained. The speed age correction formula is composed of the above-mentioned speed age correction formula for the younger age group and the speed age correction formula for the upper age group, and is stored in the analysis device 2 in advance.

  The analysis apparatus 2 selects one of the correction age formulas according to the actual age of the subject H input in S1 of FIG. 2 among the young age velocity age correction formula and the senior age velocity age correction formula, The speed age of the subject H is corrected by adding the correction term obtained by substituting the actual age of the subject H to the selected correction formula to the speed age of the subject H calculated in S52 of FIG. For example, if the actual age of the subject H is X1 (for example, 30 years old) and the velocity age of the subject H calculated in S52 of FIG. 2 is Y1, the analysis device 2 uses the velocity age correction formula for young people. Then, Y1 + ΔY1 (X1) = Y1 + X1− (a1X1 + b1) obtained by adding the correction term ΔY1 (X1) = X1− (a1X1 + b1) to the speed age Y1 of the subject H is set as the speed age of the subject H after correction. On the other hand, for example, if the actual age of the subject H is X2 (for example, 60 years old) and the velocity age of the subject H calculated in S52 of FIG. The correction formula is selected, and Y2 + ΔY2 (X2) = Y2 + X2− (a2X2 + b2) obtained by adding the correction term ΔY2 (X2) = X2− (a2X2 + b2) to the speed age Y2 of the subject H is the speed age of the subject H after correction.

  Although the speed age has been described above, the same applies to the balance age and the posture age. That is, the balance age correction formula is composed of a balance age correction formula for young people and a balance age correction formula for seniors, and the analysis device 2 has a balance age correction formula for young people and a balance age correction formula for old people. The correction term obtained by selecting one of the correction formulas according to the actual age of the subject H input in S1 of FIG. 2 and substituting the correction formula for selecting the actual age of the subject H is shown in FIG. The balance age of the subject H is corrected by adding to the balance age of the subject H calculated in S52 of 2. Similarly, the posture age correction formula is composed of a posture age correction formula for young people and a posture age correction formula for senior people, and the analysis device 2 uses the posture age correction formula for young people and the posture age correction for senior people. Among the equations, a correction term obtained by selecting any one of the correction equations corresponding to the actual age of the subject H input in S1 of FIG. 2 and substituting the actual age of the subject H into the selected correction equation, The posture age of the subject H is corrected by adding to the posture age of the subject H calculated in S52 of FIG.

  As shown in FIG. 3 (a), an example of speed age, according to the present inventors, the correlation between the actual age of a plurality of humans and each age of speed age, balance age, and posture age is It was found that young people and older people tend to have different trends. Therefore, as in the first embodiment, when correcting the average speed age, balance age, and posture age of a plurality of humans so as to approach the actual age, the speed age, balance age, and Instead of correcting each age of posture age uniformly, it is preferable to divide it into a younger age group and an older age group and correct each separately. According to the correction of the first embodiment, it is possible to correct the average speed age, the balance age, and the posture age of a plurality of humans so as to approach the actual age for both the young and the elderly. (See FIG. 3B). As a result, as will be described later, the average walking age of the subject H calculated based on the corrected speed age, balance age, and posture age is also close to the actual age (see FIG. 3C).

  In the first embodiment, the classification of the younger generation and the older generation is performed as follows. That is, the velocity age was calculated by regression analysis using the actual age (X) of a plurality of humans before classification as an independent variable and the velocity age (Y) calculated for the plurality of humans as a dependent variable. Let the regression line be Y = a0X + b0 (a0 and b0 are predetermined constants). The actual age (X coordinate) at the intersection of this regression line and the speed age = actual age line (Y = X) is defined as the reference age Xc. The younger group is X <Xc, and the older group is X ≧ Xc. The same applies to the balance age and posture age. The reference age Xc is a predetermined age of 40 to 60 years old, for example. However, the present invention is not limited to this, and the younger age group and the older age group may be classified according to the magnitude of a predetermined fixed actual age regardless of the regression line Y = a0X + b0.

Next, in the analysis step S5, the analysis apparatus 2 of the first embodiment stores the corrected age of the subject H, the corrected age of the subject H, the corrected age of the subject H, and the pre-corrected posture age of the subject H. 2 is used to calculate the walking age of the subject H as shown in FIG. 3C (S54 in FIG. 2). Here, the second correspondence relationship is a correspondence relationship between each age of speed age, balance age and posture age, and walking age.
The second correspondence relationship of the first embodiment is a relationship in which the walking age is represented by a linear sum of speed age, balance age, and posture age. That is, if the speed age is Y1, the balance age is Y2, the posture age is Y3, and the walking age is Z, the second correspondence relationship is represented by Z = n1X1 + n2X2 + n3X3 + n4 (n1 to n4 are predetermined constants). However, the present invention is not limited to this, and the walking age is represented by a non-linear sum of each age, such as a sum of quadratic expressions of speed age, balance age and posture age, or a sum of cubic expressions. It can also be a relationship.

  Finally, in the analysis step S5, the analysis device 2 of the first embodiment calculates a score, which is an index indicating superiority or inferiority of a plurality of walking parameters, as a preferred configuration (S55 in FIG. 2). Hereinafter, the score calculation procedure will be described in detail.

The analysis apparatus 2 according to the first embodiment includes a score calculation reference expression and a score for calculating a score that is an index indicating superiority or inferiority of a plurality of walking parameters (walking speed, walking rhythm difference, hip bending, etc.). The calculation deviation is stored in advance for each walking parameter.
FIG. 4 is an explanatory diagram for explaining a score calculation procedure for walking speed, which is one of walking parameters. As shown in FIG. 4, the reference formula for score calculation uses the independent variables as the actual ages of a plurality of humans and the dependent variable as a walking parameter (walking speed in the example shown in FIG. 4) calculated for the plurality of humans. It is a regression formula for calculating the walking parameter reference value E using the actual age X as a variable, which is calculated by analysis. The reference formula for score calculation of the first embodiment is a quadratic regression formula of actual age X. That is, the score calculation reference expression is represented by E = m1X ² + m2X + m3 (m1 to m3 are predetermined constants). However, the present invention is not limited to this, and other regression equations such as a linear regression equation and a cubic regression equation can be used. The score calculation deviation is a value obtained by multiplying the standard deviation SD of the walking parameters (walking speed in the example shown in FIG. 4) calculated for a plurality of humans by a predetermined coefficient. In the first embodiment, two types (l ₁ , l ₂ ) are used as the predetermined coefficients, and the score calculation deviations are l ₁ SD and l ₂ SD (where l ₁ and l ₂ are l ₁ <l ₂ , 0 <l ₁ and a predetermined constant satisfying 0 <l ₂ ).

The analysis device 2 calculates the walking parameter reference value E of the subject H by substituting the actual age X of the subject H input in S1 of FIG. The difference between the walking parameter (walking speed in the example shown in FIG. 4) of the subject H calculated using the three-dimensional coordinates of the body feature points (chest and hips) of the subject H and the walking parameter reference value E is calculated as a score. Compared with the deviations for use l ₁ SD and l ₂ SD, a score set in advance according to the magnitude is calculated as a score of the walking parameter of the subject H (walking speed in the example shown in FIG. 4).

In the example shown in FIG. 4, when the walking speed calculated for the subject H is P, when the difference between P and E is larger than l ₂ SD, that is, when P> (E + l ₂ SD), A score is set in advance so that a score “5” indicating superiority is calculated. Similarly, a score “4” is calculated when (E + l ₂ SD) ≧ P> (E + l ₁ SD), and a score “3” when (E + l ₁ SD) ≧ P> (E−l ₁ SD). ”Is calculated, and score“ 2 ”is calculated when (E−l ₁ SD) ≧ P> (E−l ₂ SD), and most inferior when (E−l ₂ SD)> P Is set so that a score “1” indicating that the
In the example illustrated in FIG. 4, the walking speed is described as an example of the walking parameter, but the analysis device 2 of the first embodiment can calculate the score of the subject H similarly for other walking parameters. In the case of walking speed, the higher value is determined to be a higher score. For example, in the case of hip flexion, the lower value is the higher score determination (“4 “5” or “5”), and in accordance with the characteristics of each walking parameter, whichever value is larger or smaller is set in advance.

  As described above, in the first embodiment, a score calculation reference expression for calculating an average value of each walking parameter (walking parameter reference value E) according to the actual age of a plurality of humans, Using the deviation for score calculation related to the standard deviation SD of each walking parameter for humans, the value of each walking parameter of the subject H is determined for each average walking parameter according to the actual age of the subject H. A score indicating whether it is at a certain level is calculated. For this reason, it can be expected to lead to improvement in the consciousness of the subject H with respect to improvement in walking ability.

  The analysis apparatus 2 according to the first embodiment outputs the analysis results (the subject H's speed age, balance age, posture age, walking age, walking parameter score, etc.) after executing the analysis step S5 described above (see FIG. 2 S6), the operation ends. The output of the analysis result may be printed from a printer connected to the analysis device 2 in addition to being displayed on a monitor mounted on the analysis device 2. Moreover, you may make it transmit an analysis result to information terminals, such as a personal computer and a smart phone which the test subject H owns via the internet. In addition, the analysis results are stored on the Internet using a cloud storage service, etc., and the subject H accesses the location where the analysis results are stored from his / her terminal via the Internet and sees the results whenever he / she likes. You may be made to do.

  According to the walking analysis system 100 according to the first embodiment described above, in addition to the walking speed related to the speed age and the left-right difference of the walking rhythm related to the balance age, the posture age that cannot be evaluated by the conventional method The walking age is calculated using the involved hip bending as a walking parameter. Therefore, compared with the conventional method, the walking ability can be comprehensively evaluated from the walking state of the whole body, and the walking age that matches the walking ability of the subject H can be calculated.

  In the first embodiment, the speed age, balance age, and posture age of the subject H calculated in S52 of FIG. 2 are corrected (S53 of FIG. 2), and the walking age is calculated using each age after the correction. Although the configuration has been described, the present invention is not limited to this, and the walking age can be calculated using the speed age, balance age, and posture age of the subject H calculated in S52 of FIG. 2 as they are. is there.

  In the first embodiment, the walking age of the subject H is calculated (S54 in FIG. 2), and then the walking parameter score of the subject H is calculated (S55 in FIG. 2) as an example. The present invention is not limited to this, and it is possible to use a procedure for calculating the walking age of the subject H after calculating the walking parameter score of the subject H, and calculating the walking age of the subject H and the walking parameters. It is also possible to perform the score calculation in parallel. It is also possible to adopt a configuration in which only the walking age is calculated without calculating the walking parameter score, or conversely, only the walking parameter score is calculated without calculating the walking age.

[Second Embodiment]
Hereinafter, a gait analysis system according to a second embodiment of the present invention will be described.
The gait analysis system according to the second embodiment also has the same schematic configuration as the gait analysis system 100 according to the first embodiment shown in FIG. 1, and is the same as the gait analysis system 100 according to the first embodiment shown in FIG. Perform the general operation. For this reason, also with respect to the walking analysis system according to the second embodiment, with reference to FIGS. 1 and 2 as appropriate, the same components and similar steps as those in the first embodiment are the same as those used in the first embodiment. This will be described using reference numerals. Hereinafter, the gait analysis system according to the second embodiment will be described mainly with respect to differences from the first embodiment, and description of similar points will be omitted.

  In the walking analysis system according to the second embodiment, the content of the analysis step S5 executed by the analysis device 2 is different from that of the first embodiment, and operates to calculate the apparent age of the subject H. Accordingly, the content of the walking parameter calculated in the analysis step S5 is also different from the first embodiment. This will be specifically described below.

In the analysis step S5, the analysis device 2 according to the second embodiment uses at least walking speed, waist bending, waist rotation as walking parameters using the three-dimensional coordinates of the plurality of body feature points of the subject H. Is calculated.
Since the walking speed and the bending of the waist are the same as those in the first embodiment, description thereof is omitted.
The rotation of the waist means the degree of rotation of the waist during walking. For example, in one walking cycle, the swing width (maximum value and minimum value) of the angle formed by the straight line connecting the left and right pelvis projected on the horizontal plane and the left and right axes However, the angle is defined as a positive value when the right hip side of the straight line connecting the left and right pelvis is tilted forward with respect to the left and right axis), and the chest and waist measured by the three-dimensional measuring device 1 It can be calculated using the three-dimensional coordinates of the left and right pelvis.

The analysis apparatus 2 according to the second embodiment includes, as the walking parameters, the above-described three parameters of walking speed, hip bending and hip rotation, as well as the difference in walking angle, left and right head swing, walking angle, and head movement. Four parameters of lateral shaking are further calculated.
Since the left-right difference and the walking angle of the walking angle are the same as those in the first embodiment, the description thereof is omitted.

  The back-and-forth movement of the head means the back-and-forth movement of the head during walking. For example, the swing width (the difference between the maximum value and the minimum value) at the position where the head moves back and forth from the center of the pelvis in one walking cycle. However, the value is defined as a positive value when the head is positioned forward with respect to the center of the pelvis), and the three-dimensional coordinates of the thoracolumbar, the center of the pelvis and the head measured by the three-dimensional measuring apparatus 1 are used. Can be calculated. Note that the three-dimensional coordinates of the head can be measured without markers using Kinect (registered trademark).

  The lateral shaking of the head means the lateral shaking of the head during walking. For example, in one walking cycle, the swing width (the difference between the maximum value and the minimum value) at the position where the head is shifted from the center of the pelvis to the left or right. However, the value is defined as a positive value when the head is located on the right foot side with respect to the center of the pelvis), and the three-dimensional coordinates of the thoracolumbar, the center of the pelvis and the head measured by the three-dimensional measuring device 1 are used. And can be calculated.

Next, in the analysis step S5, the analysis device 2 of the second embodiment uses the walking age, the hip bending and the hip rotation, which are walking parameters, and the correspondence relationship stored in advance, and the apparent age of the subject H. Is calculated. More specifically, the analysis device 2 according to the second embodiment includes the walking speed, the bending of the waist and the rotation of the waist, the left / right difference of the walking angle (specifically, the left / right difference of the walking angle knee), and the front and back of the head. The apparent age of the subject H is calculated using the swing of the direction, the walking angle (specifically, the walking angle toe), the horizontal swing of the head, and the correspondence stored in advance.
Corresponding relationships stored in advance in the analysis device 2 of the second embodiment include walking speed, hip bending and hip rotation, walking angle left / right difference (walking angle knee left / right difference), head back-and-forth swing, walking It is expressed by a linear multiple regression equation in which at least one of the corners (walking toes) and the lateral shaking of the head (all in the second embodiment) is an independent variable and the apparent age is a dependent variable. Yes. In other words, walking speeds, hip bending, hip rotation, walking angle left / right difference (walking angle knee left / right difference), head anteroposterior shaking, walking angle (walking angle toe) and head lateral direction are independent variables. And X7, X2, X3, X4, X5, X6, and X7, respectively, and the apparent age as a dependent variable is Y, the correspondence is expressed as Y = a1X1 + a2X2 + a3X3 + a4X4 + a5X5 + a6X6 + a7X7 + b (a1 to a7, b are predetermined constants) It is. The constants a1 to a7 and b can be calculated by regression analysis using the independent variables as the walking parameters X1 to X7 calculated for the plurality of humans with the dependent variables as the apparent age determined by a third party for the plurality of humans. It is. Note that the multiple regression equation representing the correspondence relationship is not limited to the first order, and a multi-order multiple regression equation such as a second-order multiple regression equation or a third-order multiple regression equation may be employed.

FIG. 5 is a diagram illustrating an example of a result of calculating an apparent age by the walking analysis system according to the second embodiment. The calculated value shown on the horizontal axis in FIG. 5 means the apparent age calculated by the walking analysis system according to the second embodiment, and the actually measured value shown on the vertical axis in FIG. 5 means the apparent age determined by a third party. To do. The results shown in FIG. 5 are obtained by plotting the apparent age calculated by analyzing the gait of 100 or more subjects H on the horizontal axis, and the walking of each subject H by 20 third parties different from the subject H. The average value of the apparent age determined by observation is plotted on the vertical axis.
As can be seen from the results shown in FIG. 5, according to the walking analysis system according to the second embodiment, it is possible to calculate an apparent age that closely approximates the result of observation and determination by a third party.

[Third Embodiment]
Hereinafter, a gait analysis system according to a third embodiment of the present invention will be described.
The gait analysis system according to the third embodiment has the same schematic configuration as the gait analysis system 100 according to the first embodiment shown in FIG. 1, and is the same as the gait analysis system 100 according to the first embodiment shown in FIG. Perform the general operation. For this reason, also with respect to the walking analysis system according to the third embodiment, with reference to FIGS. 1 and 2 as appropriate, the same components and similar steps as those in the first embodiment are the same as those used in the first embodiment. This will be described using reference numerals. Hereinafter, with respect to the walking analysis system according to the third embodiment, differences from the first embodiment and the second embodiment will be mainly described, and description of similar points will be omitted.

  In the gait analysis system according to the third embodiment, the content of the analysis step S5 executed by the analysis device 2 is different from the first embodiment, and a beauty posture evaluation value that is an index representing the beauty of the walking posture of the subject H is calculated. To work. Accordingly, the content of the walking parameter calculated in the analysis step S5 is also different from the first embodiment. This will be specifically described below.

In the analysis step S5, the analysis device 2 according to the third embodiment uses at least a forward tilt posture, a walking speed, and an elbow swing as walking parameters using the three-dimensional coordinates of the plurality of body feature points of the subject H. Specifically, the elbow sagittal plane angle and the elbow frontal plane angle) are calculated.
Since the walking speed and the swing of the elbow are the same as those in the first embodiment, description thereof is omitted.

The forward leaning posture means a forward leaning state of the posture during walking, and is expressed by, for example, any one of the bending of the waist, the inclination of the head in the front-rear direction, and the inclination of the shoulder in the front-rear direction.
Since the bending of the waist is the same as in the first embodiment, the description thereof is omitted.
The tilt of the head in the front-rear direction means the tilt of the head in the front-rear direction during walking. For example, the average value of the position where the head deviates from the center of the pelvis in one walking cycle It can be calculated using the three-dimensional coordinates of the thoracolumbar, the center of the pelvis, and the head measured by the three-dimensional measuring apparatus 1.
The forward / backward inclination of the shoulder means the forward / backward inclination of the shoulder during walking. For example, the average value of the position where the shoulder is shifted back and forth from the center of the pelvis in one walking cycle (however, the value of the shoulder is the pelvis) It can be calculated using the three-dimensional coordinates of the thoracolumbar, the center of the pelvis, and the head measured by the three-dimensional measuring apparatus 1.

The analysis device 2 of the third embodiment includes, as the walking parameters, the above-described three parameters of the forward tilt posture, the walking speed, and the swing of the elbow, the left-right difference of the walking angle, the lateral shaking of the head, the rotation of the waist, Nine parameters are calculated: head lateral tilt, shin tilt, thigh lift, toe lift, step and shoulder frontal face angle. Although not calculated in the third embodiment, a left-right difference in walking angle or walking rhythm may be further calculated as in the first embodiment.
Since the left-right difference of the walking angle and the rise of the toe are the same as those in the first embodiment, the description thereof is omitted. Further, since the horizontal shaking of the head and the rotation of the waist are the same as those in the second embodiment, description thereof is omitted.

  The horizontal inclination of the head means the horizontal inclination of the head during walking. For example, the average absolute value of the position where the head is shifted left and right from the center of the pelvis in one walking cycle (however, the value is Can be calculated using the three-dimensional coordinates of the thoraco-lumbar, the center of the pelvis, and the head measured by the three-dimensional measuring apparatus 1.

  The fall of the shin means the fall of the shin during walking. For example, in one walking cycle, the angle formed by the straight line connecting the left knee and the left ankle projected on the front face when the left foot is touched and the vertical axis And the average value of the angle formed by the vertical axis and the straight line connecting the right knee and the right ankle projected on the frontal plane when the right foot touches the ground (however, each angle is determined by the knee side of the straight line connecting the knee and the ankle) It can be calculated using the three-dimensional coordinates of the chest and hips, the left and right knees, and the left and right ankles measured by the three-dimensional measuring apparatus 1.

  Thigh rise means the degree of thigh rise during walking. For example, in one walking cycle, the maximum value of the angle formed by the straight line connecting the right pelvis projected on the sagittal plane and the right knee and the vertical axis And the average value of the angle between the straight line connecting the left pelvis and the left knee projected on the sagittal plane and the vertical axis (however, each angle is determined by the knee side of the straight line connecting the pelvis and the knee) It can be calculated using the three-dimensional coordinates of the thoraco-lumbar, the left and right pelvis, and the left and right knees measured by the three-dimensional measuring apparatus 1.

  The gait means the distance between the left and right feet during walking. For example, in one walking cycle, the distance between the left and right ankles when the left foot is grounded, and the right and left ankles when the right foot is grounded It can be calculated by using the three-dimensional coordinates of the chest and waist and the left and right ankles measured by the three-dimensional measuring device 1.

  The front shoulder face angle means how the arm swings during walking. For example, in one walking cycle, the swing width of the angle formed by the straight line connecting the left shoulder and the left elbow projected on the front face and the vertical axis ( The difference between the maximum value and the minimum value) and the swing of the angle formed by the vertical axis and the straight line connecting the right shoulder and right elbow projected on the front face (the difference between the maximum and minimum values) Value (however, each angle is defined as a positive value when the elbow side of the straight line connecting the shoulder and the elbow is tilted forward) Can be calculated using the three-dimensional coordinates of the elbow.

Next, in the analysis step S5, the analysis apparatus 2 according to the third embodiment includes at least a forward tilt posture (specifically, tilt in the front-rear direction of the head), walking speed, and elbow swing (specifically, walking parameters). Calculates the beauty posture evaluation value of the subject H using the elbow sagittal plane angle and the elbow frontal plane angle) and the correspondence relationship stored in advance. More specifically, the analysis device 2 according to the third embodiment is capable of walking in addition to a forward tilt posture (head tilt in the front-rear direction), walking speed, and elbow swing (elbow sagittal plane angle and frontal elbow face angle). Left / right difference in angle (specifically, left / right difference in walking angle knee and left / right difference in walking angle toe), lateral shaking of the head, rotation of the hips, lateral tilt of the head, shin fall, thigh lift The beauty posture evaluation value of the subject H is calculated using the toe lift, the step distance, the shoulder face angle, and the correspondence stored in advance.
The correspondence relationship stored in advance in the analysis device 2 of the third embodiment includes a forward tilt posture (head tilt in the front-rear direction), walking speed, elbow swing (elbow sagittal plane angle and frontal elbow face angle), and walking. Left-right difference in angle (left-right difference in walking angle knee and left-right difference in walking angle toe), walking angle, left-right difference in walking rhythm, lateral shaking of head, hip rotation, lateral tilt of head, shin tilt At least one of thigh rise, toe rise, step distance and front shoulder face angle (in the third embodiment, all except for the left and right differences in walking angle and walking rhythm) is an independent variable, and the beauty posture evaluation It is represented by a first order multiple regression equation with the value as the dependent variable. In other words, the anteversion posture (inclination in the front-rear direction of the head), walking speed, elbow sagittal plane angle of elbow swing, elbow frontal face angle of elbow swing, left-right difference of walking angle (walking angle) Left-right difference of knee), left-right difference of walking angle (left-right difference of walking angle toe), horizontal shaking of head, hip rotation, horizontal tilt of head, shin fall, thigh lift, toe lift, Assume that the step and shoulder frontal face angles are X1, X2, X3, X4, X5, X6, X7, X8, X9, X10, X11, X12, X13, and X14, and the beauty posture evaluation value that is a dependent variable is Y. The correspondence relationship is expressed as Y = a1X1 + a2X2 + a3X3 + a4X4 + a5X5 + a6X6 + a7X7 + a8X8 + a9X9 + a10X10 + a11X11 + a12X12 + a13X13 + a14X14 + b (a1 to a14, b are predetermined constants) . The constants a1 to a14 and b are obtained by performing regression analysis with the dependent variables as beauty posture evaluation values determined by a third person for a plurality of persons and the independent variables as the respective walking parameters X1 to X14 calculated for the plurality of persons. It can be calculated. Note that the multiple regression equation representing the correspondence relationship is not limited to the first order, and a multi-order multiple regression equation such as a second-order multiple regression equation or a third-order multiple regression equation may be employed.

FIG. 6 is a diagram illustrating an example of a result of calculating a beauty posture evaluation value by the walking analysis system according to the third embodiment. The calculated value shown on the horizontal axis of FIG. 6 means the beauty posture evaluation value calculated by the walking analysis system according to the third embodiment, and the actual measurement value shown on the vertical axis of FIG. Means evaluation value. In the example shown in FIG. 6, the beautiful posture evaluation value “1” is “not beautiful”, the beautiful posture evaluation value “2” is “somewhat not beautiful”, the beautiful posture evaluation value “3” is “normal”, and the beautiful posture evaluation value. “4” means “slightly beautiful”, and the beauty posture evaluation value “5” means “beautiful”. The results shown in FIG. 6 are obtained by plotting the posture evaluation values calculated by analyzing the gait of 100 or more subjects H on the horizontal axis. The average value of the beauty posture evaluation values observed and determined by the three parties is plotted on the vertical axis.
As can be seen from the results shown in FIG. 6, according to the walking analysis system according to the third embodiment, it is possible to calculate a beauty posture evaluation value that closely approximates the result of observation and determination by a third party.

DESCRIPTION OF SYMBOLS 1 ... Three-dimensional measuring apparatus 2 ... Analysis apparatus 100 ... Gait analysis system H ... Test subject

Claims (22)

A three-dimensional measuring device that sequentially measures three-dimensional coordinates of a plurality of predetermined body feature points of the subject as the subject walks;
A first correspondence relationship between a plurality of walking parameters calculated using the three-dimensional coordinates of the body feature points or calculated using other methods and the speed age, balance age, and posture age; and the speed age, The balance age and the second correspondence relationship between the posture age and the walking age are stored in advance, and calculated using the three-dimensional coordinates of the plurality of body feature points of the subject measured by the three-dimensional measuring device, or The speed age, balance age and posture age of the subject are calculated using the plurality of walking parameters of the subject calculated using another method and the first correspondence relationship stored in advance, and the calculated age Using a speed age, a balance age and a posture age of the subject, and an analysis device for calculating the walking age of the subject using the second correspondence relationship stored in advance.
The plurality of walking parameters include at least walking speed, left-right difference in walking rhythm, and hip bending,
The first correspondence relationship includes the first regression equation having the walking speed as an independent variable, the speed age as a dependent variable, and at least the left-right difference of the walking rhythm as an independent variable, and the balance age as a dependent variable. A second regression equation, and a third regression equation including at least the waist bending as an independent variable and the posture age as a dependent variable, are included.
A gait analysis system characterized by this. Each of the first regression equation, the second regression equation, and the third regression equation performs regression analysis with the dependent variable as the actual age of a plurality of humans and the independent variable as each gait parameter calculated for the plurality of humans. Is calculated by
The gait analysis system according to claim 1. The second correspondence relationship is a relationship representing the walking age as a linear sum of the speed age, the balance age, and the posture age.
The gait analysis system according to claim 1 or 2 characterized by things. The plurality of body feature points include at least thoracolumbar and the center of the pelvis,
The walking speed is calculated using the three-dimensional coordinates of the thoracolumbar or other methods,
The left-right difference of the walking rhythm is calculated using the three-dimensional coordinates of the chest and waist,
The hip bend is calculated using the three-dimensional coordinates of the thoracolumbar and the center of the pelvis.
The gait analysis system according to any one of claims 1 to 3, wherein: The plurality of body feature points further includes left and right pelvis and left and right knees, further includes left and right knees and left and right ankles, or further includes left and right ankles and left and right toes,
The plurality of walking parameters are calculated using three-dimensional coordinates of the thoracolumbar, the left and right pelvis and the left and right knees, or three-dimensional coordinates of the thoracolumbar, the left and right knees and the left and right ankles. Or a left-right difference in walking angle calculated using three-dimensional coordinates of the thoracolumbar, the left and right ankles and the left and right toes,
The second regression equation included in the first correspondence relationship is a multiple regression equation in which at least the left-right difference of the walking rhythm and the left-right difference of the walking angle are independent variables and the balance age is a dependent variable. ,
The gait analysis system according to claim 4. The plurality of body feature points further include left and right pelvis and left and right knees,
The plurality of walking parameters further include a left-right difference in the rise of the thigh calculated using three-dimensional coordinates of the thoracolumbar, the left and right pelvis, and the left and right knees,
The second regression equation included in the first correspondence relationship is a multiple regression equation in which at least the lateral difference of the walking rhythm and the lateral difference of the thigh rise are independent variables and the balance age is a dependent variable. is there,
The gait analysis system according to claim 4. The plurality of body feature points further include left and right shoulders,
The plurality of walking parameters further include a shoulder horizontal angle calculated using three-dimensional coordinates of the thoracolumbar and the left and right shoulders,
The second regression equation included in the first correspondence relationship is a multiple regression equation with at least the left-right difference of the walking rhythm and the shoulder horizontal angle as independent variables and the balance age as a dependent variable.
The gait analysis system according to claim 4. The plurality of body feature points further includes left and right pelvis and left and right knees, further includes left and right knees and left and right ankles, or further includes left and right ankles and left and right toes,
The plurality of walking parameters are calculated using three-dimensional coordinates of the thoracolumbar, the left and right pelvis and the left and right knees, or three-dimensional coordinates of the thoracolumbar, the left and right knees and the left and right ankles. Or a walking angle calculated using three-dimensional coordinates of the thoracolumbar, the left and right ankles, and the left and right toes,
The third regression equation included in the first correspondence relationship is a multiple regression equation in which at least the hip bending and the walking angle are independent variables and the posture age is a dependent variable.
The gait analysis system according to claim 4. The plurality of body feature points further include left and right toes,
The plurality of walking parameters further include toe rise calculated using the three-dimensional coordinates of the thoracolumbar and the left and right toes,
The third regression equation included in the first correspondence is at least a multiple regression equation in which the hip bending and the toe rise are independent variables and the posture age is a dependent variable.
The gait analysis system according to claim 4. The plurality of body feature points further include left and right elbows and left and right wrists,
The plurality of walking parameters further include elbow swing calculated using three-dimensional coordinates of the thoracolumbar, the left and right elbows, and the left and right wrists,
The third regression equation included in the first correspondence relationship is a multiple regression equation in which at least the bending of the waist and the swing of the elbow are independent variables and the posture age is a dependent variable.
The gait analysis system according to claim 4. The analysis device stores in advance a speed age correction formula for correcting the speed age, a balance age correction formula for correcting the balance age, and a posture age correction formula for correcting the posture age. Has been
The velocity age correction formula divides a plurality of human real ages into a younger age group and an older age group that is older than the young age group, and the actual age of the humans belonging to the young age group and an independent variable are defined as the young age group. The correction term with the actual age as a variable, which is obtained by the difference from the regression line calculated by performing regression analysis as the velocity age calculated for the human belonging to the younger group as the actual age of the human belonging to Young age velocity age correction formula for calculation, the real age of the human belonging to the older age group, the independent variable as the actual age of the human belonging to the older age group, and the dependent variable as the human age belonging to the older age group It is composed of a velocity age correction formula for elderly people for calculating a correction term using a real age as a variable, which is obtained by a difference from a regression line calculated by regression analysis as a velocity age calculated for
The balance age correction formula divides the actual age of a plurality of humans into a younger age group and an older age group that is older than the young age group, and the actual age of the human belonging to the young age group and an independent variable are defined as the young age group. The correction term with the actual age as a variable, which is obtained by the difference from the regression line calculated by performing regression analysis as the balance age calculated for the human belonging to the younger group as the dependent age as the actual age of the human belonging to The balance age correction formula for young people to calculate, the real age of the human belonging to the older age group, the independent variable as the actual age of the human belonging to the older age group, and the dependent variable as the human age belonging to the older age group From the balance age correction formula for the elderly to calculate the correction term using the actual age as a variable, obtained by the difference from the regression line calculated by regression analysis as the balance age calculated for It has been made,
The posture age correction formula divides the actual age of a plurality of humans into a younger age group and an older age group that is older than the young age group, and the actual age of the human belonging to the young age group and an independent variable are defined as the young age group. The correction term with the actual age as a variable, which is obtained by the difference from the regression line calculated by performing regression analysis as the posture age calculated for the human being belonging to the younger group as the dependent age as the actual age of the human belonging to The posture age correction formula for young people to calculate, the real age of the human belonging to the older age, the independent variable as the actual age of the human belonging to the older age, and the dependent variable as the human belonging to the older age group It is composed of a posture age correction formula for elderly people for calculating a correction term using a real age as a variable, which is obtained by a difference from a regression line calculated by performing regression analysis as a posture age calculated for
The analysis device includes:
Of the young age velocity age correction formula and the older age velocity age correction formula, select one of the correction formulas according to the actual age of the input subject, and select the actual age of the subject By adding the correction term obtained by substituting into the corrected equation to the calculated velocity age of the subject, the velocity age of the subject is corrected,
Of the balance age correction formula for the younger group and the balance age correction formula for the older group, select one of the correction formulas according to the input actual age of the subject, and select the actual age of the subject The correction term obtained by substituting into the corrected equation is added to the calculated balance age of the subject to correct the balance age of the subject,
Of the posture age correction formula for the younger group and the posture age correction formula for the older group, either one of the correction formulas corresponding to the input actual age of the subject is selected, and the actual age of the subject is selected. Correcting the posture age of the subject by adding a correction term obtained by substituting into the calculated correction formula to the calculated posture age of the subject,
Using the corrected velocity age of the subject, the corrected balance age of the subject, the corrected posture age of the subject, and the second correspondence relationship stored in advance, the walking age of the subject To calculate,
The gait analysis system according to any one of claims 1 to 10, wherein: In the analysis device, a reference formula for score calculation for calculating a score that is an index indicating superiority or inferiority of the plurality of walking parameters and a deviation for score calculation are stored in advance for each walking parameter,
The reference formula for score calculation is a walking parameter criterion using the actual age as a variable, which is calculated by regression analysis using the independent variable as the actual age of a plurality of humans and the dependent variable as a walking parameter calculated for the plurality of humans. A regression equation for calculating the value,
The score calculation deviation is a value obtained by multiplying a standard deviation of walking parameters calculated for the plurality of humans by a predetermined coefficient,
The analysis device calculates a walking parameter reference value by substituting the inputted actual age of the subject into the score calculation reference formula, and calculates the subject using the three-dimensional coordinates of the body feature points of the subject The difference between the walking parameter and the walking parameter reference value is compared with the score calculation deviation, and a score set in advance according to the magnitude is calculated as the walking parameter score of the subject.
The gait analysis system according to any one of claims 1 to 11, wherein A three-dimensional measuring device that sequentially measures three-dimensional coordinates of a plurality of predetermined body feature points of the subject as the subject walks;
An analysis device that calculates a plurality of walking parameters of the subject using the three-dimensional coordinates of the body feature points;
In the analysis device, a reference formula for score calculation for calculating a score that is an index indicating superiority or inferiority of the plurality of walking parameters and a deviation for score calculation are stored in advance for each walking parameter,
The analysis device calculates a walking parameter reference value by substituting the inputted actual age of the subject into the score calculation reference formula, and calculates the subject using the three-dimensional coordinates of the body feature points of the subject The difference between the walking parameter and the walking parameter reference value is compared with the score calculation deviation, and a score set in advance according to the magnitude is calculated as the walking parameter score of the subject.
A gait analysis system characterized by this. A three-dimensional measurement step of sequentially measuring three-dimensional coordinates of a plurality of predetermined body feature points of the subject as the subject walks;
A first correspondence relationship between a plurality of walking parameters calculated using the three-dimensional coordinates of the body feature points or calculated using other methods and the speed age, balance age, and posture age; and the speed age, The balance age and the second correspondence relationship between the posture age and the walking age are stored in advance and calculated using the three-dimensional coordinates of the plurality of body feature points of the subject measured by the three-dimensional measurement process. Alternatively, the speed age, balance age, and posture age of the subject are calculated using the plurality of walking parameters of the subject calculated using another method and the first correspondence relationship stored in advance, and the calculated age Using the velocity age, balance age and posture age of the subject, and the second correspondence relationship stored in advance, and calculating the walking age of the subject,
The plurality of walking parameters include at least walking speed, left-right difference in walking rhythm, and hip bending,
The first correspondence relationship includes the first regression equation having the walking speed as an independent variable, the speed age as a dependent variable, and at least the left-right difference of the walking rhythm as an independent variable, and the balance age as a dependent variable. A second regression equation, and a third regression equation including at least the waist bending as an independent variable and the posture age as a dependent variable, are included.
A gait analysis method characterized by this. A three-dimensional measuring device that sequentially measures three-dimensional coordinates of a plurality of predetermined body feature points of the subject as the subject walks;
Correspondences between a plurality of walking parameters calculated using the three-dimensional coordinates of the body feature points or calculated using other methods and the appearance age are stored in advance and measured by the three-dimensional measuring device. The subject using the plurality of walking parameters of the subject calculated using the three-dimensional coordinates of the plurality of body feature points of the subject or using other methods, and the correspondence relationship stored in advance. An analysis device for calculating the appearance age of
The plurality of walking parameters include at least walking speed, hip bending, and hip rotation,
The correspondence relationship is represented by a multiple regression equation having at least the walking speed, the bending of the waist, and the rotation of the waist as independent variables, and the apparent age as a dependent variable.
A gait analysis system characterized by this. The plurality of body feature points include at least thoracolumbar, pelvic center, and left and right pelvises,
The walking speed is calculated using the three-dimensional coordinates of the thoracolumbar or other methods,
The hip curvature is calculated using the three-dimensional coordinates of the thoracolumbar and the center of the pelvis,
The rotation of the waist is calculated using the three-dimensional coordinates of the thoracolumbar and the left and right pelvises,
The gait analysis system according to claim 15. The plurality of body feature points further include left and right knees, left and right ankles, left and right toes, and a head,
The plurality of walking parameters further include at least one of a left-right difference in walking angle, a head anteroposterior shaking, a walking angle, and a head shaking in the lateral direction,
The left-right difference of the walking angle is calculated using the three-dimensional coordinates of the thoracolumbar, the left and right pelvis and the left and right knees, or the three-dimensional coordinates of the thoracolumbar, the left and right knees and the left and right ankles Or calculated using the three-dimensional coordinates of the thoracolumbar, the left and right ankles and the left and right toes,
The longitudinal shaking of the head is calculated using the thoracolumbar, the center of the pelvis and the three-dimensional coordinates of the head,
The walking angle is calculated using the three-dimensional coordinates of the thoracolumbar, the left and right pelvis and the left and right knees, or using the three-dimensional coordinates of the thoracolumbar, the left and right knees and the left and right ankles. Or calculated using three-dimensional coordinates of the thoracolumbar, the left and right ankles and the left and right toes,
The lateral shaking of the head is calculated using the thoracolumbar, the center of the pelvis and the three-dimensional coordinates of the head,
The correspondence relationship includes at least any one of the walking speed, the bending of the waist and the rotation of the waist, the left-right difference of the walking angle, the shaking of the head in the front-rear direction, the walking angle and the shaking of the head in the lateral direction. It is expressed by a multiple regression equation with one or the other as an independent variable and the appearance age as a dependent variable.
The gait analysis system according to claim 16. A three-dimensional measurement step of sequentially measuring three-dimensional coordinates of a plurality of predetermined body feature points of the subject as the subject walks;
Correspondences between a plurality of walking parameters calculated using the three-dimensional coordinates of the body feature points or using other methods and visual ages are stored in advance and measured by the three-dimensional measurement step. The subject using the plurality of walking parameters of the subject calculated using the three-dimensional coordinates of the plurality of body feature points of the subject or using other methods and the correspondence relationship stored in advance. An analysis step of calculating the appearance age of
The plurality of walking parameters include at least walking speed, hip bending, and hip rotation,
The correspondence relationship is represented by a multiple regression equation having at least the walking speed, the bending of the waist, and the rotation of the waist as independent variables, and the apparent age as a dependent variable.
A gait analysis method characterized by this. A three-dimensional measuring device that sequentially measures three-dimensional coordinates of a plurality of predetermined body feature points of the subject as the subject walks;
A correspondence relationship between a plurality of walking parameters calculated using the three-dimensional coordinates of the body feature points or other methods and a beauty posture evaluation value that is an index representing the beauty of the walking posture is provided. A plurality of walking parameters of the subject calculated in advance using a three-dimensional coordinate of a plurality of body feature points of the subject measured in advance and stored by the three-dimensional measuring device; An analysis device that calculates a beauty posture evaluation value of the subject using the correspondence stored in advance,
The plurality of walking parameters include at least a forward leaning posture, a walking speed, and an elbow swing,
The correspondence relationship is represented by a multiple regression equation with at least the forward leaning posture, the walking speed, and the elbow swing as independent variables and the beauty posture evaluation value as a dependent variable.
A gait analysis system characterized by this. The plurality of body feature points include at least thoracolumbar, pelvic center, head, left and right elbows, and left and right wrists,
The anteversion posture is calculated using the three-dimensional coordinates of the thoracolumbar and the center of the pelvis, or calculated using the three-dimensional coordinates of the thoracolumbar, the center of the pelvis and the head,
The walking speed is calculated using the three-dimensional coordinates of the thoracolumbar or other methods,
The elbow swing is calculated using the three-dimensional coordinates of the chest and hips, the left and right elbows and the left and right wrists.
The gait analysis system according to claim 19. The plurality of body feature points further include left and right pelvis, left and right knees, left and right ankles, left and right toes, and left and right shoulders,
The plurality of walking parameters include: walking angle left and right difference, walking angle, walking rhythm left and right difference, lateral shaking of the head, hip rotation, lateral tilt of the head, and shin tilt. And at least one of thigh lift, toe lift, step, and frontal face angle,
The left-right difference of the walking angle and the walking angle are calculated using three-dimensional coordinates of the thoracolumbar, the left and right pelvis and the left and right knees, or the thoracolumbar, the left and right knees and the left and right ankles Or using the three-dimensional coordinates of the thoracolumbar, the left and right ankles and the left and right toes,
The left-right difference of the walking rhythm is calculated using the three-dimensional coordinates of the chest and waist,
The lateral shaking of the head is calculated using the thoracolumbar, the center of the pelvis and the three-dimensional coordinates of the head,
The hip rotation is calculated using three-dimensional coordinates of the thoracolumbar and the left and right pelvises,
The lateral tilt of the head is calculated using the thoracolumbar, the center of the pelvis and the three-dimensional coordinates of the head,
The shin fall is calculated using the three-dimensional coordinates of the thoracolumbar, the left and right knees, and the left and right ankles,
The rise of the thigh is calculated using the three-dimensional coordinates of the thoracolumbar, the left and right pelvis and the left and right knees,
The rise of the toes is calculated using the three-dimensional coordinates of the thoracolumbar and the left and right toes,
The step is calculated using three-dimensional coordinates of the thoracolumbar and the left and right ankles,
The shoulder frontal face angle is calculated using the three-dimensional coordinates of the chest waist, the left and right shoulders and the left and right elbows,
The correspondence relationship includes the forward leaning posture, the walking speed and the swing of the elbow, the left-right difference of the walking angle, the walking angle, the left-right difference of the walking rhythm, the lateral shaking of the head, the rotation of the waist , The lateral posture of the head, tilting of the shin, rising of the thigh, rising of the toe, the step distance and the frontal face angle are independent variables, and the beauty posture evaluation value Represented by a multiple regression equation with
The gait analysis system according to claim 20. A three-dimensional measurement step of sequentially measuring three-dimensional coordinates of a plurality of predetermined body feature points of the subject as the subject walks;
A correspondence relationship between a plurality of walking parameters calculated using the three-dimensional coordinates of the body feature points or other methods and a beauty posture evaluation value that is an index representing the beauty of the walking posture. A plurality of walking parameters of the subject calculated in advance using three-dimensional coordinates of the plurality of physical feature points of the subject measured in the three-dimensional measurement step or calculated using other methods; An analysis step of calculating a beauty posture evaluation value of the subject using the correspondence relationship stored in advance,
The plurality of walking parameters include at least a forward leaning posture, a walking speed, and an elbow swing,
The correspondence relationship is represented by a multiple regression equation with at least the forward leaning posture, the walking speed, and the elbow swing as independent variables and the beauty posture evaluation value as a dependent variable.
A gait analysis method characterized by this.