Posture control assessment system for neurological disorders

Abstract

The application provides a posture control evaluation system for nervous system diseases, and relates to the technical field of posture control evaluation. The method comprises the following steps: a joint angle module, which acquires joint angles through a joint goniometer; a joint range of motion scoring module, which determines a joint range of motion score; a joint coordinate module, which acquires a plurality of joint coordinates; a center of gravity scoring module, which determines a center of gravity score according to the joint coordinates; a plantar pressure data module, which acquires plantar pressure data of a plurality of sampling points at a plurality of motion simulation time points through a pressure insole; a pressure scoring module, which determines a pressure score according to the plantar pressure data; and a posture control scoring module, which performs weighted average on the joint range of motion score, the center of gravity score and the pressure score to determine a posture control score. According to the application, the posture control function under different motion states and different motion mode conversions can be accurately evaluated according to the joint range of motion score, the center of gravity score and the pressure score.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of posture control evaluation, and particularly relates to a posture control evaluation system for nervous system diseases. BACKGROUND

[0002] In the related art, CN119405266A discloses a multi-sensory re-weighting dynamic balance evaluation method, including: (1) data acquisition: collecting the center of pressure (COP) data of the subject under different sensory disturbance conditions; (2) posture stability evaluation: fitting the 95% confidence ellipse of the COP data, calculating the sway area A, and evaluating the overall posture stability of the subject; (3) COP signal decomposition: preprocessing the COP data, and decomposing it into different frequency bands using discrete wavelet transform; (4) multi-sensory re-weighting analysis: mapping the frequency bands to the sensory system, calculating the energy proportion, and quantifying the contribution of each sensory system to balance control; (5) data integration and evaluation. This scheme combines linear indicators (sway area) and nonlinear indicators (energy distribution of discrete wavelet transform) to comprehensively and objectively evaluate the posture stability of the subject and the contribution of each sensory system to balance control under multi-sensory disturbance conditions.

[0003] CN115040078A relates to the technical field of rehabilitation training equipment, and specifically relates to a dynamic balance ability evaluation device, including a base plate; a force plate arranged on the base plate, the force plate including two force modules arranged on the base plate in the front-rear direction; a vertical interference mechanism arranged between the force modules and the base plate, and the force modules and the vertical interference mechanism are fixedly connected; wherein the vertical interference mechanism has a driving component, and the vertical interference mechanism is assembled to independently control each of the force modules to move in the vertical direction under the driving of the driving component, so as to apply different types of interference to the subject standing on the force plate. The device of this scheme can apply various interferences in the vertical direction to the subject, and measure the force signal of the subject in the process of maintaining posture stability in the face of interference through the force plate. By analyzing the force signal, the balance ability of the subject can be evaluated.

[0004] Therefore, in the related art, although the balance ability of the subject can be evaluated, the related art does not consider the influence of posture control evaluation under different motion states and different motion mode transitions, that is, it is impossible to accurately evaluate the posture control function under different motion states and different motion mode transitions according to joint activity score, center of gravity score and pressure score.

[0005] The information disclosed in the Background section of the present application is only intended to enhance the understanding of the general background of the present application and should not be taken as an acknowledgement or any form of suggestion that this information forms prior art that is already known to those skilled in the art. SUMMARY

[0006] The present application provides a posture control evaluation system for nervous system diseases, which can solve the technical problem that related art cannot accurately evaluate posture control function under different motion states and different motion mode transitions according to joint range of motion score, center of gravity score and pressure score.

[0007] According to the present application, a posture control evaluation system for nervous system diseases is provided, comprising:

[0008] A joint angle module is configured to acquire joint angles of multiple joints of a testee in multiple joint motions through a joint goniometer.

[0009] A joint range of motion scoring module is configured to determine a joint range of motion score according to the joint angles.

[0010] A joint coordinate module is configured to acquire multiple joint coordinates by shooting the posture of the testee in motion simulation of multiple physical models at multiple motion simulation time points through a depth camera.

[0011] A center of gravity scoring module is configured to determine a center of gravity score according to the joint coordinates.

[0012] A plantar pressure data module is configured to acquire plantar pressure data of multiple sampling points at multiple motion simulation time points through a pressure insole.

[0013] A pressure scoring module is configured to determine a pressure score according to the plantar pressure data.

[0014] A posture control scoring module is configured to determine a posture control score by weighted average of the joint range of motion score, the center of gravity score and the pressure score.

[0015] Further, determining a joint range of motion score according to the joint angles comprises:

[0016] The joint angles are divided into left upper limb joint angles, right upper limb joint angles, left lower limb joint angles and right lower limb joint angles.

[0017] A left limb joint vector is determined according to the left upper limb joint angles and the left lower limb joint angles.

[0018] A right limb joint vector is determined according to the right upper limb joint angles and the right lower limb joint angles.

[0019] obtaining a preset joint angle threshold range of each joint in multiple joint movements;

[0020] determining a joint range of motion score according to the left limb joint vector, the right limb joint vector, the joint angle, and the preset joint angle threshold range.

[0021] Further, determining a joint range of motion score according to the left limb joint vector, the right limb joint vector, the joint angle, and the preset joint angle threshold range comprises:

[0022] according to the formula

[0023]

[0024] determining a joint range of motion score A1, wherein θ i,j is the joint angle of the ith joint in the jth joint movement, θ p,min is the minimum value of the preset joint angle threshold, θ p,max is the maximum value of the preset joint angle threshold, is the joint angle of the 1st, 2nd, …, Xth left upper limb joint in the jth joint movement, is the joint angle of the 1st, 2nd, …, Yth left lower limb joint in the jth joint movement, is the joint angle of the 1st, 2nd, …, Xth right upper limb joint in the jth joint movement, is the joint angle of the 1st, 2nd, …, Yth right lower limb joint in the jth joint movement, is the left limb joint vector, is the right limb joint vector, is the transpose vector of , α1 and α2 are preset weights, α1+α2=1, N is the number of joints, J i is the number of joint movements of the ith joint, X is the number of left upper limb joints or right upper limb joints, Y is the number of left lower limb joints or right lower limb joints, i≤N, j≤J i , and i, j, N, J i , X and Y are positive integers, and if is a conditional function.

[0025] Further, determining a center of gravity score according to the joint coordinates comprises:

[0026] dividing the human body into multiple segments, and obtaining the mass proportion and the center of mass position of the multiple segments according to biomechanical standard data;

[0027] obtaining the center of mass coordinates of the multiple segments at multiple movement simulation time points according to the joint coordinates and the center of mass positions;

[0028] According to the mass proportion and the centroid coordinates, a barycenter score is determined.

[0029] Further, according to the mass proportion and the centroid coordinates, a barycenter score is determined, including:

[0030] According to the formula

[0031]

[0032] A barycenter score A2 is determined, wherein m e is the mass proportion of the e th segment, r e,k is the centroid coordinate of the e th segment at the k th motion simulation moment, r e,k+1 is the centroid coordinate of the e th segment at the k+1 th motion simulation moment, r e,k+2 is the centroid coordinate of the e th segment at the k+2 th motion simulation moment, is the barycenter displacement vector from the k th motion simulation moment to the k+1 th motion simulation moment, is the barycenter displacement vector from the k th motion simulation moment to the k+2 th motion simulation moment, is the transpose vector of E is the number of segments, K is the number of motion simulation moments, e≤E, k≤K, and e, k, E and K are all positive integers.

[0033] Further, according to the plantar pressure data, a pressure score is determined, including:

[0034] The plantar pressure data is determined to be left plantar pressure data and right plantar pressure data;

[0035] The left plantar pressure data of multiple sampling points at each motion simulation moment is averaged to obtain average left plantar pressure data at each motion simulation moment;

[0036] The right plantar pressure data of multiple sampling points at each motion simulation moment is averaged to obtain average right plantar pressure data at each motion simulation moment;

[0037] The average left plantar pressure data and the motion simulation moment are fitted to obtain an average left plantar pressure function;

[0038] According to the average left plantar pressure function, an average left plantar pressure derivative function is obtained;

[0039] According to the average left plantar pressure derivative function, an average left plantar pressure change rate at multiple motion simulation moments is determined;

[0040] The average right plantar pressure data and the motion simulation moment are fitted to obtain an average right plantar pressure function;

[0041] obtaining an average right foot pressure derivative function according to the average right foot pressure function;

[0042] determining average right foot pressure change rates at a plurality of motion simulation time points according to the average right foot pressure derivative function;

[0043] determining a pressure score according to the foot pressure data, the average left foot pressure change rate and the average right foot pressure change rate.

[0044] Further, determining a pressure score according to the foot pressure data, the average left foot pressure change rate and the average right foot pressure change rate, comprises:

[0045] according to the formula

[0046]

[0047] determining a pressure score A3, wherein F L,s,k is left foot pressure data of the s-th sampling point at the k-th motion simulation time point, F R,s,k is right foot pressure data of the s-th sampling point at the k-th motion simulation time point, is the average left foot pressure change rate at the k-th motion simulation time point, is the average right foot pressure change rate at the k-th motion simulation time point, β1 and β2 are preset weights, β1 + β2 = 1, M is the number of sampling points, K is the number of motion simulation time points, s ≤ M, k ≤ K, and s, k, M and K are all positive integers, max is a maximum value function, and min is a minimum value function.

[0048] Technical effects: According to the present application, the posture control ability of the measured person is quantitatively scored through multiple dimensions such as joint range of motion score, center of gravity score and pressure score, which helps to objectively and accurately reflect the posture control level of the measured person. The range of motion of the human body joint, the center of gravity transfer in the process of human body movement and the plantar pressure are detected under different motion states and different motion mode conversion, so as to accurately evaluate the posture control function and reduce the risk of falling. When determining the joint range of motion score, the joint range of motion score can be determined based on the left limb joint vector, the right limb joint vector, the joint angle and the preset joint angle threshold range. By judging whether the joint angle is within the preset joint angle threshold range, the abnormal degree of joint activity can be accurately described. By comparing the left and right joint activity of the human body through the cosine similarity of the left limb joint vector and the right limb joint vector, it can be judged whether the joint activity of the human body is in a relative balance state, thereby improving the comprehensiveness and reliability of the joint range of motion score. When determining the center of gravity score, the center of gravity score can be determined based on the mass ratio and the center of mass coordinates. By the mass ratio and the center of mass coordinates, the overall center of gravity coordinates are calculated, so as to obtain the cosine similarity of the center of gravity displacement vector, which can evaluate the smoothness and stability of the center of gravity transfer in the continuous motion process. When determining the pressure score, the pressure score can be determined based on the plantar pressure data, the average left plantar pressure change rate and the average right plantar pressure change rate. By the distribution and left-right change symmetry of the plantar pressure in the motion simulation, the foot function and posture control ability can be evaluated, and the comprehensiveness, reliability and objectivity of the pressure score are improved.

[0049] It should be understood that the above general description and the following detailed description are exemplary and explanatory, but not limiting the present application. Other features and aspects of the present application will be more apparent from the following detailed description of exemplary embodiments with reference to the accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0050] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiment or prior art description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can also obtain other embodiments from these drawings without creative labor;

[0051] Figure 1 An exemplary block diagram of a posture control evaluation system for nervous system diseases according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0052] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0053] The technical solutions of the present application will be described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and some embodiments may not be described again for the same or similar concepts or processes.

[0054] Figure 1 An example block diagram of a posture control evaluation system for nervous system diseases according to an embodiment of the present application is shown, which includes:

[0055] A joint angle module for acquiring joint angles of multiple joints of a person being tested in various joint movements through a joint goniometer;

[0056] A joint range of motion scoring module for determining a joint range of motion score according to the joint angles;

[0057] A joint coordinate module for acquiring multiple joint coordinates by shooting the posture of the person being tested in motion simulation of various physical models at multiple motion simulation time points through a depth camera;

[0058] A center of gravity scoring module for determining a center of gravity score according to the joint coordinates;

[0059] A plantar pressure data module for acquiring plantar pressure data of multiple sampling points at multiple motion simulation time points through a pressure insole;

[0060] A pressure scoring module for determining a pressure score according to the plantar pressure data;

[0061] A posture control scoring module for determining a posture control score by weighted average of the joint range of motion score, the center of gravity score and the pressure score.

[0062] The posture control evaluation system for nervous system diseases according to the embodiment of the present application quantitatively scores the posture control ability of the person being tested through multiple dimensions such as joint range of motion score, center of gravity score and pressure score, which helps to objectively and accurately reflect the posture control level of the person being tested. The activity of human joints, the transfer of center of gravity in human movement and the plantar pressure are detected under different motion states and different motion mode conversion, so as to accurately evaluate the posture control function and reduce the risk of falling.

[0063] According to one embodiment of the present application, in the joint angle module, the joint goniometer is a precision instrument specially used for measuring joint angles, guiding the measured person to perform various joint movements, such as flexion, extension, internal rotation and external rotation, and recording the joint angles when the joint movement reaches the maximum range.

[0064] According to one embodiment of the present application, in the joint range of motion scoring module, the joint range of motion score is determined according to the joint angle.

[0065] According to one embodiment of the present application, the joint range of motion score is determined according to the joint angle, including: determining that the joint angle is divided into left upper limb joint angle, right upper limb joint angle, left lower limb joint angle and right lower limb joint angle; determining a left limb joint vector according to the left upper limb joint angle and the left lower limb joint angle; determining a right limb joint vector according to the right upper limb joint angle and the right lower limb joint angle; obtaining a preset joint angle threshold range of each joint in various joint movements; and determining a joint range of motion score according to the left limb joint vector, the right limb joint vector, the joint angle and the preset joint angle threshold range.

[0066] According to one embodiment of the present application, the human body has the most joints in the limbs, therefore, the joint angles at the limbs are measured, and the joint angles are divided into left upper limb joint angle, right upper limb joint angle, left lower limb joint angle and right lower limb joint angle. The left upper limb joint angle and the left lower limb joint angle are combined to obtain a left limb joint vector, that is, the left upper limb joint angle and the left lower limb joint angle are both elements of the left limb joint vector, and similarly, the right upper limb joint angle and the right lower limb joint angle are combined to obtain a right limb joint vector. Different joints have different normal ranges of joint angles, and a preset joint angle threshold range of each joint in various joint movements is obtained, for example, the elbow joint mainly completes flexion and extension joint movements, and the preset joint angle threshold range of the elbow joint includes flexion 135° to 150° and extension 0° to 10°. The wrist joint is a saddle joint and can complete flexion, extension, palmar deviation and dorsal deviation joint movements, and the preset joint angle threshold range of the wrist joint includes flexion 70° to 90°, extension 80° to 90°, palmar deviation 30° to 60° and dorsal deviation 20° to 40°. The left limb joint vector and the right limb joint vector are compared, and it is judged whether the joint angle is within the preset joint angle threshold range, so as to determine the joint range of motion score.

[0067] According to one embodiment of the present application, the joint range of motion score is determined according to the left limb joint vector, the right limb joint vector, the joint angle and the preset joint angle threshold range, including: determining the joint range of motion score A1 according to formula (1),

[0068]

[0069]

[0070] wherein θ i,j is the joint angle of the ith joint in the jth joint movement, θ p,min is the minimum value of the preset joint angle threshold, θ p,max is the maximum value of the preset joint angle threshold, is the joint angle of the 1st, 2nd, …, Xth left upper limb joint in the jth joint movement, is the joint angle of the 1st, 2nd, …, Yth left lower limb joint in the jth joint movement, is the joint angle of the 1st, 2nd, …, Xth right upper limb joint in the jth joint movement, is the joint angle of the 1st, 2nd, …, Yth right lower limb joint in the jth joint movement, is the left limb joint vector, is the right limb joint vector, is the transpose vector of , α1 and α2 are preset weights, α1 + α2 = 1, N is the number of joints, J i is the number of joint movements of the ith joint, X is the number of left upper limb joints or right upper limb joints, Y is the number of left lower limb joints or right lower limb joints, i ≤ N, j ≤ J i , and i, j, N, J i , X and Y are positive integers, and if is a conditional function.

[0071] According to one embodiment of the present application, in formula (1), if(θ i,j ∈ [θ p,min , θ p,max ], 1, 0) indicates that the joint angle of the ith joint in the jth joint movement is within the preset joint angle threshold range, the value of the conditional function is 1, otherwise, the value of the conditional function is 0. is the average value of the conditional functions corresponding to the joint angles of the plurality of joints in the plurality of joint movements, indicating the degree of abnormality of joint activity, the greater the average value of the conditional functions, the more normal the joint activity, the greater the degree of joint activity, the smaller the average value of the conditional functions, the more abnormal the joint activity, the smaller the degree of joint activity. is the cosine similarity of the left limb joint vector and the right limb joint vector, the closer the cosine similarity to 1, the closer the joint activity status of the left limb joint to the joint activity status of the right limb joint. The average value of the cosine similarity in the plurality of joint motions represents the similarity of the joint activities of the left limb joints and the right limb joints, and the greater the average value of the cosine similarity, the more similar the joint activities of the left limb joints and the right limb joints, the closer the joint activities of the human body, that is, the joint activities of the human body are in a relatively balanced state, and the greater the joint activity degree. The average value of the cosine similarity in the plurality of joint motions represents the similarity of the joint activities of the left limb joints and the right limb joints, and the greater the average value of the cosine similarity, the more similar the joint activities of the left limb joints and the right limb joints, the closer the joint activities of the human body, that is, the joint activities of the human body are in a relatively balanced state, and the greater the joint activity degree.

[0072] In this way, the joint activity degree score can be determined based on the left limb joint vector, the right limb joint vector, the joint angle and the preset joint angle threshold range, the abnormal degree of joint activity can be accurately described by judging whether the joint angle is within the preset joint angle threshold range, and whether the joint activities of the human body are in a relatively balanced state can be judged by comparing the joint activity degrees of the left and right limbs of the human body through the cosine similarity of the left limb joint vector and the right limb joint vector, thereby improving the comprehensiveness and reliability of the joint activity degree score.

[0073] According to an embodiment of the present application, in the joint coordinate module, the physical model includes a roadblock model, a step model, a ramp model and an obstacle model, which are used to simulate the motion posture of the measured person in different situations. The interval between adjacent motion simulation moments can be set to 5 seconds, 10 seconds, etc., and the present application does not limit this. The depth camera can capture the three-dimensional posture information of the measured person, i.e., the joint coordinates. The measured person performs motion simulation on the physical model according to the preset motion scheme, such as the transformation of various actions and postures, such as straight walking, going up and down the steps, crossing the obstacles, bypassing the obstacles, etc., to simulate the motion process in a real situation.

[0074] According to an embodiment of the present application, in the center of gravity scoring module, the center of gravity score is determined according to the joint coordinates.

[0075] According to an embodiment of the present application, the center of gravity score is determined according to the joint coordinates, including: dividing the human body into a plurality of segments, obtaining the mass ratio and the center of mass position of the plurality of segments according to biomechanical standard data; obtaining the center of mass coordinates of the plurality of segments at a plurality of motion simulation moments according to the joint coordinates and the center of mass positions; and determining the center of gravity score according to the mass ratio and the center of mass coordinates.

[0076] According to an embodiment of the present application, according to the principle of biomechanics, the human body can be divided into multiple segments, for example, head, torso, upper limbs (divided into upper arm, forearm and hand), lower limbs (divided into thigh, lower leg and foot) and the like. According to the biomechanical standard data, the mass ratio and the center of mass position of each segment relative to the whole human body are obtained, for example, the mass of the head segment accounts for about 7% of the total body weight, and the center of mass position is located at the position of the geometric center of the head, the mass of the thigh segment (single side) accounts for about 10% of the total body weight, and the center of mass position is located at the position of 45% from the hip joint to the knee joint. At multiple motion simulation moments, according to the obtained joint coordinates and the center of mass position of each segment, the center of mass coordinates of each segment at multiple motion simulation moments are calculated, for example, the thigh segment, if the joint coordinates of the hip joint are (x a ,y a ,z a ), the joint coordinates of the knee joint are (x b ,y b ,z b ), and the center of mass position of the thigh segment is located at the position of 45% from the hip joint to the knee joint, therefore, using the linear interpolation method, the center of mass coordinates of the thigh segment are (x a +0.45(x b -x a ),y a +0.45(y b -y a ),z a +0.45(z b -z a )). According to the mass ratio and the center of mass coordinates, the center of gravity score

[0077] According to an embodiment of the present application, according to the mass ratio and the center of mass coordinates, the center of gravity score is determined, comprising: determining the center of gravity score A2 according to formula (2),

[0078]

[0079] wherein m e is the mass ratio of the e-th segment, r e,k is the center of mass coordinates of the e-th segment at the k-th motion simulation moment, r e,k+1 is the center of mass coordinates of the e-th segment at the k+1-th motion simulation moment, r e,k+2 is the center of mass coordinates of the e-th segment at the k+2-th motion simulation moment, is the center of gravity displacement vector from the k-th motion simulation moment to the k+1-th motion simulation moment, is the center of gravity displacement vector from the k-th motion simulation moment to the k+2-th motion simulation moment, is is a transpose vector of the center of mass vector of the segment, E is the number of segments, K is the number of motion simulation time points, e≤E, k≤K, and e, k, E and K are positive integers.

[0080] According to one embodiment of the present application, in formula (2), the overall center of gravity is a weighted sum of the center of mass coordinates of each segment, and the weight is the mass proportion of each segment, that is, is the sum of the center of mass coordinates of each segment at the kth motion simulation time point and the mass proportion of each segment, represents the overall center of gravity coordinates at the kth motion simulation time point, and similarly, is the overall center of gravity coordinates at the k+1th motion simulation time point, is the overall center of gravity coordinates at the k+2th motion simulation time point, is the cosine similarity of the center of gravity displacement vector between the kth motion simulation time point and the k+1th motion simulation time point and the center of gravity displacement vector between the kth motion simulation time point and the k+2th motion simulation time point, and the closer the cosine similarity is to 1, the smaller the center of gravity transfer between the kth motion simulation time point and the k+2th motion simulation time point, and the better the posture control ability. The cosine similarity of the center of gravity displacement vector between multiple motion simulation time points is averaged to obtain the center of gravity score, and the larger the center of gravity score, the smaller the center of gravity transfer, and the better the posture control ability.

[0081] In this way, the center of gravity score can be determined based on the mass proportion and the center of mass coordinates, the overall center of gravity coordinates can be calculated through the mass proportion and the center of mass coordinates, and the cosine similarity of the center of gravity displacement vector can be obtained, so that the smoothness and stability of the center of gravity transfer in the continuous motion process can be evaluated.

[0082] According to one embodiment of the present application, in the plantar pressure data module, two pressure insoles are prepared, the pressure insoles are internally provided with a plurality of pressure sensors, and can sense and record the pressure distribution of the plantar surface at different positions. Different positions of one pressure insole are sampled as sampling points, the sampling points can be set according to different regions of the plantar surface, for example, the forefoot, the arch, the heel, etc., and the other pressure insole samples the symmetric sampling points of the pressure insole. The person to be measured wears the shoes provided with the pressure insoles, and performs motion simulation according to a preset motion scheme to obtain the plantar pressure data of the sampling points at multiple motion simulation time points.

[0083] According to one embodiment of the present application, in the pressure score module, the pressure score is determined according to the plantar pressure data.

[0084] According to one embodiment of the present application, the pressure score is determined according to the plantar pressure data, comprising: determining that the plantar pressure data is divided into left plantar pressure data and right plantar pressure data; averaging the left plantar pressure data of multiple sampling points at each movement simulation moment to obtain average left plantar pressure data at each movement simulation moment; averaging the right plantar pressure data of multiple sampling points at each movement simulation moment to obtain average right plantar pressure data at each movement simulation moment; fitting the average left plantar pressure data and the movement simulation moment to obtain an average left plantar pressure function; obtaining an average left plantar pressure derivative function according to the average left plantar pressure function; determining the average left plantar pressure change rate at multiple movement simulation moments according to the average left plantar pressure derivative function; fitting the average right plantar pressure data and the movement simulation moment to obtain an average right plantar pressure function; obtaining an average right plantar pressure derivative function according to the average right plantar pressure function; determining the average right plantar pressure change rate at multiple movement simulation moments according to the average right plantar pressure derivative function; and determining the pressure score according to the plantar pressure data, the average left plantar pressure change rate and the average right plantar pressure change rate.

[0085] According to one embodiment of the present application, the plantar pressure data is divided into left plantar pressure data and right plantar pressure data. For each movement simulation moment, the left plantar pressure data of multiple sampling points on the left foot is averaged to obtain average left plantar pressure data at each movement simulation moment, which can represent the average value of the overall pressure level of the left foot at the movement simulation moment. Similarly, the right plantar pressure data of multiple sampling points on the right foot is averaged to obtain average right plantar pressure data at each movement simulation moment. The average left plantar pressure data and the movement simulation moment are fitted to obtain an average left plantar pressure function for describing the change of the average left plantar pressure over time. The average left plantar pressure function is differentiated to obtain an average left plantar pressure derivative function. The multiple movement simulation moments are substituted into the average left plantar pressure derivative function to determine the average left plantar pressure change rate at the multiple movement simulation moments. Similarly, the average right plantar pressure change rate can be obtained, which is helpful for evaluating the stress condition of the foot during movement.

[0086] According to one embodiment of the present application, the pressure score is determined according to the plantar pressure data, the average left plantar pressure change rate and the average right plantar pressure change rate, comprising: determining the pressure score A3 according to formula (3),

[0087]

[0088] wherein F L,s,k is the left plantar pressure data of the s-th sampling point at the k-th movement simulation moment, F R,s,kThe right plantar pressure data at the s-th sampling point at the k-th motion simulation time. Let be the average rate of change of left plantar pressure at the k-th moment of the motion simulation. Let be the average right plantar pressure change rate at the k-th motion simulation moment, β1 and β2 are preset weights, β1+β2=1, M is the number of sampling points, K is the number of motion simulation moments, s≤M, k≤K, and s, k, M and K are all positive integers, max is the maximum value function, and min is the minimum value function.

[0089] According to one embodiment of the present invention, in formula (3), This is the ratio of the difference between the maximum and minimum values ​​of left plantar pressure data at multiple sampling points at the k-th time of the motion simulation to the average left plantar pressure data at the k-th time of the motion simulation. In other words, it is the relative difference between the maximum and minimum values ​​of left plantar pressure data. The smaller this relative difference, the more uniform the distribution of left plantar pressure at the k-th time of the motion simulation. This is the ratio of the difference between the maximum and minimum values ​​of right plantar pressure data at multiple sampling points at the k-th moment of the motion simulation to the average right plantar pressure data at the k-th moment of the motion simulation. In other words, it is the relative difference between the maximum and minimum values ​​of the right plantar pressure data. The smaller this relative difference, the more uniform the distribution of right plantar pressure at the k-th moment of the motion simulation. We can obtain 1 minus... and The result of the average value,

[0090] The average value of this result across multiple motion simulation moments represents the pressure distribution on the left and right feet. The larger the average value, the more uniform the pressure distribution on the left and right feet. The value of the relative difference between the average rate of change of left plantar pressure at the k-th motion simulation time and the average rate of change of right plantar pressure at the k-th motion simulation time is the larger the relative difference. The greater the relative difference, the more asymmetrical the changes in plantar pressure between the left and right feet, and the worse the posture control ability. The average value of 1 minus the relative difference between the average rate of change of left plantar pressure and the average rate of change of right plantar pressure over multiple motion simulation moments is considered. A larger average value indicates more symmetrical changes in plantar pressure between the left and right feet, and better postural control. and Weighted summation yields a pressure score. The higher the pressure score, the more even the pressure distribution on the left and right soles, the more symmetrical the pressure changes on the left and right soles, and the better the postural control ability.

[0091] In this way, the pressure score can be determined based on the plantar pressure data, the average left plantar pressure change rate and the average right plantar pressure change rate, and the foot function and the posture control ability can be evaluated through two aspects of whether the distribution and the left-right change of the plantar pressure in the motion simulation are symmetrical, so that the comprehensiveness, reliability and objectivity of the pressure score are improved.

[0092] According to one embodiment of the present application, in the posture control score module, the joint activity score, the center of gravity score and the pressure score are weighted and averaged to obtain the posture control score, and the greater the posture control score is, the better the posture control ability is, and vice versa.

[0093] The posture control evaluation system for nervous system diseases according to the embodiment of the present application quantitatively scores the posture control ability of the measured person through multiple dimensions such as the joint activity score, the center of gravity score and the pressure score, which helps to objectively and accurately reflect the posture control level of the measured person, detects the activity of the human joints, the transfer of the center of gravity in the process of human movement and the plantar pressure under different motion states and different motion mode conversion, thereby accurately evaluates the posture control function and reduces the risk of falling. When determining the joint activity score, the joint activity score can be determined based on the left limb joint vector, the right limb joint vector, the joint angle and the preset joint angle threshold range, the abnormal degree of joint activity can be accurately described by judging whether the joint angle is within the preset joint angle threshold range, the relative balance state of the human joint activity can be judged by comparing the left and right joint activity of the human body through the cosine similarity of the left limb joint vector and the right limb joint vector, and the comprehensiveness and reliability of the joint activity score are improved. When determining the center of gravity score, the center of gravity score can be determined based on the mass ratio and the center of mass coordinates, the overall center of gravity coordinates are calculated through the mass ratio and the center of mass coordinates, and the cosine similarity of the center of gravity displacement vector is obtained, so that the smoothness and stability of the center of gravity transfer in the continuous motion process can be evaluated. When determining the pressure score, the pressure score can be determined based on the plantar pressure data, the average left plantar pressure change rate and the average right plantar pressure change rate, the foot function and the posture control ability can be evaluated through two aspects of whether the distribution and the left-right change of the plantar pressure in the motion simulation are symmetrical, and the comprehensiveness, reliability and objectivity of the pressure score are improved.

[0094] The present application can be a method, device, system and / or computer program product. The computer program product can include a computer readable storage medium having computer readable program instructions loaded thereon for performing various aspects of the present application.

[0095] Those skilled in the art will understand that the embodiments of the application described above and shown in the drawings are merely illustrative and that numerous other modifications and configurations can be devised without departing from the principles of the present application. The scope of the application is best defined by the appended claims.

Claims

1. A posture control evaluation system for neurological diseases, characterized by, The application relates to a joint angle module for acquiring joint angles of multiple joints of a person being measured in multiple joint movements through a joint goniometer; a joint range of motion scoring module for determining a joint range of motion score according to the joint angles; a joint coordinate module for acquiring multiple joint coordinates by shooting the posture of the person being measured in multiple physical model movement simulations through a depth camera at multiple movement simulation time points; a center of gravity scoring module for determining a center of gravity score according to the joint coordinates; a plantar pressure data module for acquiring plantar pressure data of multiple sampling points at multiple movement simulation time points through pressure shoe pads; a pressure scoring module for determining a pressure score according to the plantar pressure data; and a posture control scoring module for determining a posture control score by weightedly averaging the joint range of motion score, the center of gravity score and the pressure score. The application relates to a joint angle module for acquiring joint angles of multiple joints of a person being measured in multiple joint movements through a joint goniometer; a joint range of motion scoring module for determining a joint range of motion score according to the joint angles; a joint coordinate module for acquiring multiple joint coordinates by shooting the posture of the person being measured in multiple physical model movement simulations through a depth camera at multiple movement simulation time points; a center of gravity scoring module for determining a center of gravity score according to the joint coordinates; a plantar pressure data module for acquiring plantar pressure data of multiple sampling points at multiple movement simulation time points through pressure shoe pads; a pressure scoring module for determining a pressure score according to the plantar pressure data; and a posture control scoring module for determining a posture control score by weightedly averaging the joint range of motion score, the center of gravity score and the pressure score. The application relates to a joint angle module for acquiring joint angles of multiple joints of a person being measured in multiple joint movements through a joint goniometer; a joint range of motion scoring module for determining a joint range of motion score according to the joint angles; a joint coordinate module for acquiring multiple joint coordinates by shooting the posture of the person being measured in multiple physical model movement simulations through a depth camera at multiple movement simulation time points; a center of gravity scoring module for determining a center of gravity score according to the joint coordinates; a plantar pressure data module for acquiring plantar pressure data of multiple sampling points at multiple movement simulation time points through pressure shoe pads; a pressure scoring module for determining a pressure score according to the plantar pressure data; and a posture control scoring module for determining a posture control score by weightedly averaging the joint range of motion score, the center of gravity score and the pressure score. The application relates to a joint angle module for acquiring joint angles of multiple joints of a person being measured in multiple joint movements through a joint goniometer; a joint range of motion scoring module for determining a joint range of motion score according to the joint angles; a joint coordinate module for acquiring multiple joint coordinates by shooting the posture of the person being measured in multiple physical model movement simulations through a depth camera at multiple movement simulation time points; a center of gravity scoring module for determining a center of gravity score according to the joint coordinates; a plantar pressure data module for acquiring plantar pressure data of multiple sampling points at multiple movement simulation time points through pressure shoe pads; a pressure scoring module for determining a pressure score according to the plantar pressure data; and a posture control scoring module for determining a posture control score by weightedly averaging the joint range of motion score, the center of gravity score and the pressure score. The application relates to a joint angle module for acquiring joint angles of multiple joints of a person being measured in multiple joint movements through a joint goniometer; a joint range of motion scoring module for determining a joint range of motion score according to the joint angles; a joint coordinate module for acquiring multiple joint coordinates by shooting the posture of the person being measured in multiple physical model movement simulations through a depth camera at multiple movement simulation time points; a center of gravity scoring module for determining a center of gravity score according to the joint coordinates; a plantar pressure data module for acquiring plantar pressure data of multiple sampling points at multiple movement simulation time points through pressure shoe pads; a pressure scoring module for determining a pressure score according to the plantar pressure data; and a posture control scoring module for determining a posture control score by weightedly averaging the joint range of motion score, the center of gravity score and the pressure score. ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ determine a joint range of motion score A1, wherein θ i,j is the joint angle of the ith joint in the jth joint motion, p,min is the minimum value of the preset joint angle threshold, p,max is the maximum value of the preset joint angle threshold, is the joint angle of the 1st, 2nd, …, Xth left upper limb joint in the jth joint motion, is the joint angle of the 1st, 2nd, …, Yth left lower limb joint in the jth joint motion, is the joint angle of the 1st, 2nd, …, Xth right upper limb joint in the jth joint motion, is the joint angle of the 1st, 2nd, …, Yth right lower limb joint in the jth joint motion, is the left limb joint vector, is the right limb joint vector, is the transpose vector of , α1 and α2 are preset weights, α1 + α2 = 1, N is the number of joints, J i is the number of joint motions of the ith joint, X is the number of left upper limb joints or right upper limb joints, Y is the number of left lower limb joints or right lower limb joints, i ≤ N, j ≤ J i , and i, j, N, J i , X and Y are positive integers, and if is a conditional function.

2. The postural control evaluation system for neurological diseases according to claim 1, wherein ​ ​ ​ ​ 3. The postural control evaluation system for neurological diseases according to claim 2, wherein ​ ​ determining a center of gravity score A2, wherein m e is the mass proportion of the e-th segment, r e,k is the center of mass coordinate of the e-th segment at the k-th motion simulation moment, r e,k+1 is the center of mass coordinate of the e-th segment at the k+1-th motion simulation moment, r e,k+2 is the center of mass coordinate of the e-th segment at the k+2-th motion simulation moment, is the center of gravity displacement vector from the k-th motion simulation moment to the k+1-th motion simulation moment, is the center of gravity displacement vector from the k-th motion simulation moment to the k+2-th motion simulation moment, is the transpose vector of E is the number of segments, K is the number of motion simulation moments, e≤E, k≤K, and e, k, E and K are all positive integers.

4. The postural control evaluation system for neurological diseases according to claim 1, wherein ​ ​ ​ ​ ​ ​ ​ ​ ​ determining an average left foot plantar pressure rate of change at the plurality of motion simulation time instants based on the average left foot plantar pressure derivative function; determining a pressure score based on the plantar pressure data, the average left foot plantar pressure rate of change, and the average right foot plantar pressure rate of change.

5. The postural control evaluation system for neurological diseases according to claim 4, wherein determining a pressure score based on the plantar pressure data, the average left foot plantar pressure rate of change, and the average right foot plantar pressure rate of change, including: based on the formula determining a pressure score A3, wherein, F #,s,k is the left foot plantar pressure data of the s th sampling point at the k th motion simulation moment, F -,s,k is the right foot plantar pressure data of the s th sampling point at the k th motion simulation moment, is the average left foot plantar pressure change rate at the k th motion simulation moment, is the average right foot plantar pressure change rate at the k th motion simulation moment, β 1 and β 2 are preset weights, β 1 + β 2 = 1, M is the number of sampling points, K is the number of motion simulation moments, s ≤ M, k ≤ K, and s, k, M and K are all positive integers, max is a maximum value function, and min is a minimum value function.

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