CN119818930B - Fusion feedback processing device and method for lower limb rehabilitation training - Google Patents
Fusion feedback processing device and method for lower limb rehabilitation trainingInfo
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Abstract
本发明公开了一种用于下肢康复训练的融合反馈处理装置和方法，所述装置包括：增强现实模块、运动轨迹采集模块、训练评估模块、反馈处理模块、下肢康复训练模块、生理信息采集模块；所述运动轨迹采集模块，用于采集得到用户在利用下肢康复训练模块进行下肢康复训练时的下肢运动轨迹信息集合；所述训练评估模块，用于进行评估判别处理，得到评估分析结果；所述下肢康复训练模块，用于采集得到力量值序列；所述反馈处理模块，用于对进行反馈计算处理，得到融合反馈输出值集合。本发明主要解决了当前下肢康复训练设备主要基于力量训练为主，缺乏对人体的感知信息的利用和发掘，导致训练效果和效率受限的问题。
The present invention discloses a fusion feedback processing device and method for lower limb rehabilitation training, the device comprising: an augmented reality module, a motion trajectory acquisition module, a training evaluation module, a feedback processing module, a lower limb rehabilitation training module, and a physiological information acquisition module; the motion trajectory acquisition module is used to acquire a set of lower limb motion trajectory information of a user when performing lower limb rehabilitation training using the lower limb rehabilitation training module; the training evaluation module is used to perform evaluation and discrimination processing to obtain evaluation and analysis results; the lower limb rehabilitation training module is used to acquire a sequence of strength values; the feedback processing module is used to perform feedback calculation processing to obtain a set of fusion feedback output values. The present invention mainly solves the problem that current lower limb rehabilitation training equipment is mainly based on strength training, lacks the use and exploration of human body's sensory information, resulting in limited training effect and efficiency.
Description
Technical Field
The invention relates to the field of exoskeleton robots and the field of intelligent control, in particular to a fusion feedback processing device and method for lower limb rehabilitation training.
Background
For recovery of patients with lower limb dyskinesia, rehabilitation training is important. In the conventional rehabilitation therapy, a rehabilitation therapist usually performs one-to-one rehabilitation therapy on a patient in a freehand manner, and individual therapeutic means, experience differences, subjective consciousness and fatigue degrees of the rehabilitation therapist directly affect the therapeutic effect. The traditional rehabilitation training has the defects of single function, high cost, long rehabilitation period, tedious process, poor initiative, incapability of accurately evaluating the rehabilitation state and the like of rehabilitation equipment, and has the defects of deficiency of rehabilitation doctors.
In the currently applied lower limb rehabilitation training devices, mainly based on strength training, the utilization and the development of perception information of human bodies are lacked, so that the training effect and the efficiency are limited.
Disclosure of Invention
The invention mainly solves the problems that the current lower limb rehabilitation training equipment mainly based on strength training lacks of utilization and development of human perception information, and the training effect and efficiency are limited.
The embodiment of the application discloses a fusion feedback processing device for lower limb rehabilitation training, which comprises an augmented reality module, a motion trail acquisition module, a training evaluation module, a feedback processing module, a lower limb rehabilitation training module and a physiological information acquisition module;
the augmented reality module is used for displaying training scene information to a user through an augmented reality means;
The motion trail acquisition module is connected with the training evaluation module and is used for acquiring a lower limb motion trail information set of a user when the lower limb rehabilitation training module is used for performing lower limb rehabilitation training;
The training evaluation module is connected with the motion trail acquisition module and is used for evaluating, judging and processing the lower limb motion trail information set and the standard motion trail information to obtain an evaluation analysis result;
the lower limb rehabilitation training module is connected with the training evaluation module and used for performing rehabilitation training on lower limbs of a user and acquiring a force value sequence applied by the user during rehabilitation training;
The feedback processing module is connected with the training evaluation module and the physiological information acquisition module and is used for carrying out feedback calculation processing on the strength value sequence, the evaluation analysis result and the physiological information set to obtain a fusion feedback output value set, wherein the fusion feedback output value set comprises a force feedback value for adjusting the acting force of the lower limb rehabilitation training module on a user when the user performs lower limb rehabilitation training and a touch feedback value for adjusting the touch stimulation amount of the lower limb rehabilitation training module on the user when the user performs lower limb rehabilitation training;
The physiological information acquisition module is used for acquiring a physiological parameter set of a user when performing lower limb rehabilitation training, wherein the physiological parameter set comprises a heart rate information sequence, a blood pressure information sequence, a blood oxygen saturation information sequence and a body temperature information sequence.
The motion trail acquisition module is realized by adopting an image acquisition and analysis sub-module or an accelerometer sensor arranged on the lower limb of the user;
The lower limb movement track information set comprises a plurality of lower limb movement track information sequences;
The accelerometer sensor is used for acquiring lower limb movement tracks of a user when the lower limb rehabilitation training module is used for performing lower limb rehabilitation training, and constructing and obtaining a lower limb movement track information set by using all acquired lower limb movement tracks;
the image acquisition analysis sub-module comprises an image acquisition unit and an image analysis unit, wherein the image acquisition unit is used for acquiring images of a user when the user performs lower limb rehabilitation training by using the lower limb rehabilitation training module, and the image analysis unit is used for extracting lower limb parts of the images of the user when the user performs lower limb rehabilitation training by using the lower limb rehabilitation training module to obtain lower limb movement tracks, and constructing and obtaining a lower limb movement track information set by using all acquired lower limb movement tracks.
The lower limb rehabilitation training module comprises a fixed seat, a pedal plate and a rotating connecting arm, wherein the rotating connecting arm is used for connecting the pedal plate to the fixed seat, a mechanical sensor is arranged on the pedal plate and used for measuring and obtaining a force value sequence applied by a user when the lower limb rehabilitation training module is used for performing lower limb rehabilitation training, a plurality of soft needle-shaped structures for generating touch stimulus are arranged on the surface of the pedal plate, and a motor for controlling the pedal plate to apply acting force to the user is arranged on the rotating connecting arm.
The second aspect of the embodiment of the invention discloses a fusion feedback processing method for lower limb rehabilitation training, which is realized by using the fusion feedback processing device for lower limb rehabilitation training, and comprises the following steps:
S1, displaying training scene information to a user by using the augmented reality module, performing rehabilitation training on the lower limbs of the user by using the lower limb rehabilitation training module, and acquiring a force value sequence applied by the user during rehabilitation training;
S2, acquiring a lower limb movement track information set of a user when the lower limb rehabilitation training module is used for performing lower limb rehabilitation training by using the movement track acquisition module;
s3, utilizing the training evaluation module to evaluate and judge the lower limb movement track information set and the standard movement track information to obtain an evaluation analysis result;
And S4, carrying out feedback calculation processing on the force value sequence, the evaluation analysis result and the physiological information set by using the feedback processing module to obtain a fusion feedback output value set, wherein the fusion feedback output value set comprises a force feedback value for adjusting the acting force of the lower limb rehabilitation training module on a user when the user performs lower limb rehabilitation training and a touch feedback value for adjusting the touch stimulation amount of the lower limb rehabilitation training module on the user when the user performs lower limb rehabilitation training.
The step of carrying out evaluation and discrimination processing on the lower limb movement track information set and the standard movement track information to obtain an evaluation analysis result comprises the following steps:
s31, constructing a lower limb movement matrix by using the lower limb movement track information set, wherein row vectors of the lower limb movement matrix are lower limb movement track information;
S32, copying the row vectors according to the column direction by taking the standard motion track information as the row vectors to obtain a standard motion matrix, wherein the dimension of the standard motion matrix is the same as the dimension of the lower limb motion matrix;
S33, subtracting the lower limb movement matrix from the standard movement matrix to obtain a difference matrix;
S34, carrying out characteristic decomposition processing on the difference matrix to obtain a characteristic value sequence;
S35, fitting calculation processing is carried out on the characteristic value sequence, and a weight factor vector is obtained;
And S36, carrying out evaluation calculation processing on the characteristic value sequence, the weight factor vector, the lower limb movement matrix and the standard movement matrix to obtain an evaluation analysis result.
The expression of the evaluation and calculation process is:
wherein lambda i is the i-th eigenvalue in the eigenvalue sequence, which is also the eigenvalue corresponding to the i-th row vector of the difference matrix, A ij and B ij are the i-th row and j-th column elements of the lower limb motion matrix and the standard motion matrix respectively, M and N are the row dimension and the column dimension of the lower limb motion matrix respectively, v is the evaluation analysis result, h i is the i-th evaluation sub-result value, and k i is the i-th element of the weight factor vector.
The feedback calculation processing is performed on the strength value sequence, the evaluation analysis result and the physiological information set to obtain a fused feedback output value set, and the method comprises the following steps:
performing force feedback calculation processing on the force value sequence and the evaluation analysis result to obtain a force feedback value for adjusting the acting force of the lower limb rehabilitation training module to the user when the user performs lower limb rehabilitation training;
and carrying out haptic feedback calculation processing on the evaluation analysis result and the physiological information set to obtain a haptic feedback value for adjusting the haptic stimulus quantity of the user when the lower limb rehabilitation training module carries out lower limb rehabilitation training on the user.
The force feedback calculation processing is performed on the force value sequence and the evaluation analysis result to obtain a force feedback value for adjusting the acting force of the lower limb rehabilitation training module to the user when the user performs lower limb rehabilitation training, and the method comprises the following steps:
Obtaining a standard force value;
performing force feedback calculation processing on the standard force value, the force value sequence and the evaluation analysis result to obtain a force feedback value for adjusting the acting force of the lower limb rehabilitation training module to the user when the user performs lower limb rehabilitation training;
the expression of the force feedback calculation process is as follows:
Wherein, L 2 () and L 3 () are a second order legendre polynomial and a third order legendre polynomial, ρ is a preset multiplication factor, f i is the i element of the force value sequence, NF is the length of the force value sequence, f 0 is a standard force value, np is the force feedback value, and v is an evaluation analysis result.
The haptic feedback calculation processing is performed on the evaluation analysis result and the physiological information set to obtain a haptic feedback value for adjusting the haptic stimulus amount of the lower limb rehabilitation training module to the user when the user performs the lower limb rehabilitation training, and the method comprises the following steps:
obtaining standard physiological information, wherein the standard physiological information comprises a heart rate standard value, a blood pressure standard value, a blood oxygen saturation standard value and a body temperature standard value;
The standard physiological information is expressed as a standard physiological vector, wherein the 1 st element to the 4 th element of the standard physiological vector are respectively a heart rate standard value, a blood pressure standard value, a blood oxygen saturation standard value and a body temperature standard value;
The physiological information set is expressed as a physiological information matrix, wherein the 1 st row vector to the 4 th row vector of the physiological information matrix are respectively a heart rate information sequence, a blood pressure information sequence, a blood oxygen saturation information sequence and a body temperature information sequence;
and performing haptic feedback calculation processing on the evaluation analysis result, the standard physiological vector and the physiological information matrix to obtain a haptic feedback value for adjusting the haptic stimulus quantity of the user when the lower limb rehabilitation training module performs lower limb rehabilitation training on the user.
The expression of the haptic feedback calculation process is:
wherein pe is the haptic feedback value, v is the evaluation analysis result, T i () represents the ith order polynomial of the first chebyshev polynomial, p i is the ith feedback term, a ij represents the i-th row and j-th column element of the physiological information matrix, z i represents the i-th element of the standard physiological vector, exp represents the exponential operation of the constant e, and n is the length of the standard physiological vector.
The beneficial effects of the invention are as follows:
The invention mainly solves the problems of limited training effect and efficiency caused by lack of utilization and development of human perception information in the prior lower limb rehabilitation training equipment mainly based on strength training.
According to the invention, the evaluation analysis result and the physiological information set are subjected to haptic feedback calculation processing according to the training effect and the acquired physiological parameters of the user during lower limb rehabilitation training, so that a haptic feedback value for adjusting the haptic stimulus of the lower limb rehabilitation training module to the user during lower limb rehabilitation training is obtained, and meanwhile, the feedback of two types of training variables is realized, and the training efficiency is improved.
When the force feedback value is calculated, the force feedback calculation processing is carried out on the standard force value, the force value sequence and the evaluation analysis result, so that the force feedback value for adjusting the acting force of the lower limb rehabilitation training module to the user when the user carries out the lower limb rehabilitation training is obtained, the model of the force feedback calculation processing is specially separated, and the precision and the effectiveness of the force feedback calculation are improved.
When the haptic feedback value is calculated, the evaluation analysis result, the standard physiological vector and the physiological information matrix are subjected to haptic feedback calculation processing to obtain the haptic feedback value for adjusting the haptic stimulus quantity of the user when the lower limb rehabilitation training module is used for performing lower limb rehabilitation training, the evaluation analysis result and the standard physiological vector are comprehensively considered, and the calculation accuracy of the haptic feedback value is improved.
Drawings
FIG. 1 is a schematic diagram of the apparatus of the present invention;
fig. 2 is a flow chart of the implementation of the method of the present invention.
Detailed Description
For a better understanding of the present disclosure, an embodiment is presented herein.
FIG. 1 is a schematic diagram of the apparatus of the present invention, and FIG. 2 is a flow chart of the implementation of the method of the present invention.
Aiming at the problems that the current lower limb rehabilitation training equipment is mainly based on strength training, and lacks of utilization and development of human perception information, so that training effect and efficiency are limited, the invention discloses a fusion feedback processing device and method for lower limb rehabilitation training.
The embodiment of the application discloses a fusion feedback processing device for lower limb rehabilitation training, which comprises an augmented reality module, a motion trail acquisition module, a training evaluation module, a feedback processing module, a lower limb rehabilitation training module and a physiological information acquisition module;
the augmented reality module is used for displaying training scene information to a user through an augmented reality means;
The motion trail acquisition module is connected with the training evaluation module and is used for acquiring a lower limb motion trail information set of a user when the lower limb rehabilitation training module is used for performing lower limb rehabilitation training;
The training evaluation module is connected with the motion trail acquisition module and is used for evaluating, judging and processing the lower limb motion trail information set and the standard motion trail information to obtain an evaluation analysis result;
the lower limb rehabilitation training module is connected with the training evaluation module and used for performing rehabilitation training on lower limbs of a user and acquiring a force value sequence applied by the user during rehabilitation training;
The feedback processing module is connected with the training evaluation module and the physiological information acquisition module and is used for carrying out feedback calculation processing on the strength value sequence, the evaluation analysis result and the physiological information set to obtain a fusion feedback output value set, wherein the fusion feedback output value set comprises a force feedback value for adjusting the acting force of the lower limb rehabilitation training module on a user when the user performs lower limb rehabilitation training and a touch feedback value for adjusting the touch stimulation amount of the lower limb rehabilitation training module on the user when the user performs lower limb rehabilitation training;
The physiological information acquisition module is used for acquiring a physiological parameter set of a user when performing lower limb rehabilitation training, wherein the physiological parameter set comprises a heart rate information sequence, a blood pressure information sequence, a blood oxygen saturation information sequence and a body temperature information sequence;
the augmented reality module may be implemented by AR glasses or AR helmets.
The motion trail acquisition module is realized by adopting an image acquisition and analysis sub-module or an accelerometer sensor arranged on the lower limb of the user;
The lower limb movement track information set comprises a plurality of lower limb movement track information sequences;
The accelerometer sensor is used for acquiring lower limb movement tracks of a user when the lower limb rehabilitation training module is used for performing lower limb rehabilitation training, and constructing and obtaining a lower limb movement track information set by using all acquired lower limb movement tracks;
The image acquisition and analysis sub-module comprises an image acquisition unit and an image analysis unit; the system comprises an image acquisition unit, an image analysis unit, a lower limb movement track acquisition unit and a lower limb movement track analysis unit, wherein the image acquisition unit is used for acquiring images of a user when the user performs lower limb rehabilitation training by using a lower limb rehabilitation training module;
The lower limb rehabilitation training module comprises a fixed seat, a pedal plate and a rotating connecting arm, wherein the rotating connecting arm is used for connecting the pedal plate to the fixed seat, a mechanical sensor is arranged on the pedal plate and used for measuring and obtaining a force value sequence applied by a user when the lower limb rehabilitation training module is used for performing lower limb rehabilitation training, a plurality of soft needle structures for generating touch stimulus are arranged on the surface of the pedal plate, and a motor for controlling the force value applied by the pedal plate to the user is arranged on the rotating connecting arm.
The training evaluation module performs evaluation and discrimination processing on the lower limb movement track information set and the standard movement track information to obtain an evaluation analysis result, and comprises the following steps:
constructing a lower limb movement matrix by using the lower limb movement track information set, wherein row vectors of the lower limb movement matrix are lower limb movement track information;
Copying the row vector according to the column direction by taking the standard motion track information as a row vector to obtain a standard motion matrix, wherein the dimension of the standard motion matrix is the same as the dimension of the lower limb motion matrix;
subtracting the lower limb movement matrix from the standard movement matrix to obtain a difference matrix;
performing characteristic decomposition treatment on the difference matrix to obtain a characteristic value sequence;
Fitting calculation is carried out on the characteristic value sequence, and a weight factor vector is obtained;
Performing evaluation calculation processing on the characteristic value sequence, the weight factor vector, the lower limb movement matrix and the standard movement matrix to obtain an evaluation analysis result;
the expression of the evaluation and calculation process is:
wherein lambda i is the ith eigenvalue in the eigenvalue sequence, which is also the eigenvalue corresponding to the ith row vector of the difference matrix, A ij and B ij are the elements of the ith row and the jth column of the lower limb motion matrix and the standard motion matrix respectively, M and N are the row dimension and the column dimension of the lower limb motion matrix respectively, v is the evaluation analysis result, h i is the ith evaluation sub-result value, and k i is the ith element of the weight factor vector;
the feedback processing module performs feedback calculation processing on the force value sequence, the evaluation analysis result and the physiological information set to obtain a fused feedback output value set, and the feedback processing module comprises:
performing force feedback calculation processing on the force value sequence and the evaluation analysis result to obtain a force feedback value for adjusting the acting force of the lower limb rehabilitation training module to the user when the user performs lower limb rehabilitation training;
performing haptic feedback calculation processing on the evaluation analysis result and the physiological information set to obtain a haptic feedback value for adjusting the haptic stimulus amount of the user when the lower limb rehabilitation training module performs lower limb rehabilitation training on the user;
The force feedback calculation processing is performed on the force value sequence and the evaluation analysis result to obtain a force feedback value for adjusting the acting force of the lower limb rehabilitation training module to the user when the user performs lower limb rehabilitation training, and the method comprises the following steps:
Obtaining a standard force value;
performing force feedback calculation processing on the standard force value, the force value sequence and the evaluation analysis result to obtain a force feedback value for adjusting the acting force of the lower limb rehabilitation training module to the user when the user performs lower limb rehabilitation training;
the expression of the force feedback calculation process is as follows:
wherein, L 2 () and L 3 () are a second order legendre polynomial and a third order legendre polynomial, ρ is a preset multiplication factor, the value of ρ can be 0.3, f i is the i element of the force value sequence, NF is the length of the force value sequence, f 0 is the standard force value, np is the force feedback value, and v is the evaluation analysis result.
The haptic feedback calculation processing is performed on the evaluation analysis result and the physiological information set to obtain a haptic feedback value for adjusting the haptic stimulus amount of the lower limb rehabilitation training module to the user when the user performs the lower limb rehabilitation training, and the method comprises the following steps:
obtaining standard physiological information, wherein the standard physiological information comprises a heart rate standard value, a blood pressure standard value, a blood oxygen saturation standard value and a body temperature standard value;
The standard physiological information is expressed as a standard physiological vector, wherein the 1 st element to the 4 th element of the standard physiological vector are respectively a heart rate standard value, a blood pressure standard value, a blood oxygen saturation standard value and a body temperature standard value;
The physiological information set is expressed as a physiological information matrix, wherein the 1 st row vector to the 4 th row vector of the physiological information matrix are respectively a heart rate information sequence, a blood pressure information sequence, a blood oxygen saturation information sequence and a body temperature information sequence;
Performing haptic feedback calculation processing on the evaluation analysis result, the standard physiological vector and the physiological information matrix to obtain a haptic feedback value for adjusting the haptic stimulus quantity of the user when the lower limb rehabilitation training module performs lower limb rehabilitation training on the user;
The expression of the haptic feedback calculation process is;
wherein pe is the haptic feedback value, v is the evaluation analysis result, T i () represents the ith order polynomial of the first chebyshev polynomial, p i is the ith feedback term, a ij represents the i-th row and j-th column element of the physiological information matrix, z i represents the i-th element of the standard physiological vector, exp represents the exponential operation of the constant e, and n is the length of the standard physiological vector.
The extraction of the lower limb part can be realized by adopting human body key point identification.
The human body key point identification can be realized by adopting a SURF characteristic point detection algorithm or a corner point detection algorithm or OpenPose algorithm in OpenCV.
The acting force of the lower limb rehabilitation training module on the user when the user performs lower limb rehabilitation training can be a mechanical value applied by a motor control pedal to the user.
The lower limb rehabilitation training module comprises a fixed seat, a first rotating connecting arm, a second rotating connecting arm and a pedal, wherein the fixed seat, the first rotating connecting arm, the second rotating connecting arm and the pedal are sequentially connected in a rotating mode, the second rotating connecting arm and the fixed seat are rotatably arranged at two ends of the first rotating connecting arm, the pedal is rotatably connected to one end, far away from the first rotating connecting arm, of the second rotating connecting arm, the driving assembly is used for driving the first rotating connecting arm and the second rotating connecting arm to rotate, the driving assembly comprises a motor and a synchronous belt, the motor is erected on the fixed seat, the synchronous belt is connected with rotating shafts at two ends of the first rotating connecting arm, one end of the first rotating connecting arm is fastened with a driving shaft of the motor, and when the motor drives the first rotating connecting arm and the second rotating connecting arm to be in linkage, the pedal is in a horizontal movement state.
The amount of haptic stimulus determines the set density and radius of the soft needle-like structure on the surface of the foot pedal.
And performing fitting calculation on the characteristic value sequence to obtain a weight factor vector, wherein the fitting calculation comprises the following steps:
performing linear fitting treatment on the elements of the characteristic value sequence and the element sequence number values to obtain an optimal consistent approximation polynomial;
and taking the element sequence number value of the characteristic value sequence as an input value, and calculating by using an optimal consistent approximation polynomial to obtain a weight factor vector.
The linear fitting process is to use an element sequence number value Ix of a characteristic value sequence as a known independent variable, use an element value of the characteristic value sequence as a known dependent variable, construct a curve to be approximated by using the known independent variable and the known dependent variable, and perform curve fitting on the curve to be approximated by using a function approximation method to obtain an optimal consistent approximation polynomial f (Ix).
The characteristic value sequence is represented as I a,Ia＝[λ1,λ2,…,λN1, N1 is the number of elements contained in the characteristic value sequence, and the curve fitting is carried out on the curve to be approximated by using a function approximation method, so that an optimal consistent linear approximation method can be adopted. The best consistent approximation polynomial f (Ix) has the expression:
f(Ix)＝αP1(Ix)P1+αP1-1(Ix)P1-1+…+α2(Ix)2+α1(Ix)+α0,
Wherein P1 is the order of the best consistent approximation polynomial f (Ix), α0, α1, α2,..α P1 is the coefficient of the best consistent approximation polynomial f (Ix);
the second aspect of the embodiment of the invention discloses a fusion feedback processing method for lower limb rehabilitation training, which is realized by using the fusion feedback processing device for lower limb rehabilitation training, and comprises the following steps:
S1, displaying training scene information to a user by using the augmented reality module, performing rehabilitation training on the lower limbs of the user by using the lower limb rehabilitation training module, and acquiring a force value sequence applied by the user during rehabilitation training;
S2, acquiring a lower limb movement track information set of a user when the lower limb rehabilitation training module is used for performing lower limb rehabilitation training by using the movement track acquisition module;
s3, utilizing the training evaluation module to evaluate and judge the lower limb movement track information set and the standard movement track information to obtain an evaluation analysis result;
And S4, carrying out feedback calculation processing on the force value sequence, the evaluation analysis result and the physiological information set by using the feedback processing module to obtain a fusion feedback output value set, wherein the fusion feedback output value set comprises a force feedback value for adjusting the acting force of the lower limb rehabilitation training module on a user when the user performs lower limb rehabilitation training and a touch feedback value for adjusting the touch stimulation amount of the lower limb rehabilitation training module on the user when the user performs lower limb rehabilitation training.
The step of carrying out evaluation and discrimination processing on the lower limb movement track information set and the standard movement track information to obtain an evaluation analysis result comprises the following steps:
constructing a lower limb movement matrix by using the lower limb movement track information set, wherein row vectors of the lower limb movement matrix are lower limb movement track information;
Copying the row vector according to the column direction by taking the standard motion track information as a row vector to obtain a standard motion matrix, wherein the dimension of the standard motion matrix is the same as the dimension of the lower limb motion matrix;
subtracting the lower limb movement matrix from the standard movement matrix to obtain a difference matrix;
performing characteristic decomposition treatment on the difference matrix to obtain a characteristic value sequence;
Fitting calculation is carried out on the characteristic value sequence, and a weight factor vector is obtained;
Performing evaluation calculation processing on the characteristic value sequence, the weight factor vector, the lower limb movement matrix and the standard movement matrix to obtain an evaluation analysis result;
the expression of the evaluation and calculation process is:
Wherein lambda i is the ith eigenvalue in the eigenvalue sequence, which is also the eigenvalue corresponding to the ith row vector of the difference matrix, A ij and B ij are the elements of the ith row and the jth column of the lower limb motion matrix and the standard motion matrix respectively, M and N are the row dimension and the column dimension of the lower limb motion matrix respectively, v is the evaluation analysis result, h i is the ith evaluation sub-result value, and k i is the ith element of the weight factor vector;
the feedback calculation processing is performed on the strength value sequence, the evaluation analysis result and the physiological information set to obtain a fused feedback output value set, and the method comprises the following steps:
performing force feedback calculation processing on the force value sequence and the evaluation analysis result to obtain a force feedback value for adjusting the acting force of the lower limb rehabilitation training module to the user when the user performs lower limb rehabilitation training;
performing haptic feedback calculation processing on the evaluation analysis result and the physiological information set to obtain a haptic feedback value for adjusting the haptic stimulus amount of the user when the lower limb rehabilitation training module performs lower limb rehabilitation training on the user;
The force feedback calculation processing is performed on the force value sequence and the evaluation analysis result to obtain a force feedback value for adjusting the acting force of the lower limb rehabilitation training module to the user when the user performs lower limb rehabilitation training, and the method comprises the following steps:
Obtaining a standard force value;
performing force feedback calculation processing on the standard force value, the force value sequence and the evaluation analysis result to obtain a force feedback value for adjusting the acting force of the lower limb rehabilitation training module to the user when the user performs lower limb rehabilitation training;
the expression of the force feedback calculation process is as follows:
wherein, L 2 () and L 3 () are a second order legendre polynomial and a third order legendre polynomial, ρ is a preset multiplication factor, the value of ρ can be 0.3, f i is the i-th element of the force value sequence, NF is the length of the force value sequence, f 0 is the standard force value, np is the force feedback value, ν is the evaluation analysis result.
The haptic feedback calculation processing is performed on the evaluation analysis result and the physiological information set to obtain a haptic feedback value for adjusting the haptic stimulus amount of the lower limb rehabilitation training module to the user when the user performs the lower limb rehabilitation training, and the method comprises the following steps:
obtaining standard physiological information, wherein the standard physiological information comprises a heart rate standard value, a blood pressure standard value, a blood oxygen saturation standard value and a body temperature standard value;
The standard physiological information is expressed as a standard physiological vector, wherein the 1 st element to the 4 th element of the standard physiological vector are respectively a heart rate standard value, a blood pressure standard value, a blood oxygen saturation standard value and a body temperature standard value;
The physiological information set is expressed as a physiological information matrix, wherein the 1 st row vector to the 4 th row vector of the physiological information matrix are respectively a heart rate information sequence, a blood pressure information sequence, a blood oxygen saturation information sequence and a body temperature information sequence;
Performing haptic feedback calculation processing on the evaluation analysis result, the standard physiological vector and the physiological information matrix to obtain a haptic feedback value for adjusting the haptic stimulus quantity of the user when the lower limb rehabilitation training module performs lower limb rehabilitation training on the user;
The expression of the haptic feedback calculation process is;
Wherein pe is the haptic feedback value, v is the evaluation analysis result, T i () represents the ith order polynomial of the first chebyshev polynomial, p i is the ith feedback component, a ij represents the ith row and jth column elements of the physiological information matrix, z i represents the ith element of the standard physiological vector, exp represents the exponential operation of the constant e, and n is the length of the standard physiological vector.
And performing fitting calculation on the characteristic value sequence to obtain a weight factor vector, wherein the fitting calculation comprises the following steps:
performing linear fitting treatment on the elements of the characteristic value sequence and the element sequence number values to obtain an optimal consistent approximation polynomial;
and taking the element sequence number value of the characteristic value sequence as an input value, and calculating by using an optimal consistent approximation polynomial to obtain a weight factor vector.
The linear fitting process is to use an element sequence number value Ix of a characteristic value sequence as a known independent variable, use an element value of the characteristic value sequence as a known dependent variable, construct a curve to be approximated by using the known independent variable and the known dependent variable, and perform curve fitting on the curve to be approximated by using a function approximation method to obtain an optimal consistent approximation polynomial f (Ix).
The characteristic value sequence is represented as I a,Ia＝[λ1,λ2,…,λN1, N1 is the number of elements contained in the characteristic value sequence, and the curve fitting is carried out on the curve to be approximated by using a function approximation method, so that an optimal consistent linear approximation method can be adopted. The best consistent approximation polynomial f (Ix) has the expression:
f(Ix)＝αP1(Ix)P1+αP1-1(Ix)P1-1+…+α2(Ix)2+α1(Ix)+α0,
Where P1 is the order of the best consistent approximation polynomial f (Ix), α0, α1, α2,..α P1 is the coefficient of the best consistent approximation polynomial f (Ix).
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.
Claims (5)
1. The fusion feedback processing method for the lower limb rehabilitation training is characterized by comprising an augmented reality module, a motion track acquisition module, a training evaluation module, a feedback processing module, a lower limb rehabilitation training module and a physiological information acquisition module, wherein the lower limb rehabilitation training module comprises a fixed seat, a pedal and a rotating connecting arm, and the method comprises the following steps:
S1, displaying training scene information to a user by using the augmented reality module, performing rehabilitation training on the lower limbs of the user by using the lower limb rehabilitation training module, and acquiring a force value sequence applied by the user during rehabilitation training;
S2, acquiring a lower limb movement track information set of a user when the lower limb rehabilitation training module is used for performing lower limb rehabilitation training by using the movement track acquisition module;
s3, utilizing the training evaluation module to evaluate and judge the lower limb movement track information set and the standard movement track information to obtain an evaluation analysis result;
S4, carrying out feedback calculation processing on the force value sequence, the evaluation analysis result and the physiological information set by using the feedback processing module to obtain a fusion feedback output value set, wherein the fusion feedback output value set comprises a force feedback value for adjusting the acting force of a lower limb rehabilitation training module on a user when the user performs lower limb rehabilitation training and a touch feedback value for adjusting the touch stimulation amount of the lower limb rehabilitation training module on the user when the user performs lower limb rehabilitation training;
The step of carrying out evaluation and discrimination processing on the lower limb movement track information set and the standard movement track information to obtain an evaluation analysis result comprises the following steps:
s31, constructing a lower limb movement matrix by using the lower limb movement track information set, wherein row vectors of the lower limb movement matrix are lower limb movement track information;
S32, copying the row vectors according to the column direction by taking the standard motion track information as the row vectors to obtain a standard motion matrix, wherein the dimension of the standard motion matrix is the same as the dimension of the lower limb motion matrix;
S33, subtracting the lower limb movement matrix from the standard movement matrix to obtain a difference matrix;
S34, carrying out characteristic decomposition processing on the difference matrix to obtain a characteristic value sequence;
S35, fitting calculation processing is carried out on the characteristic value sequence, and a weight factor vector is obtained;
S36, carrying out evaluation calculation processing on the characteristic value sequence, the weight factor vector, the lower limb movement matrix and the standard movement matrix to obtain an evaluation analysis result;
the expression of the evaluation and calculation process is:
wherein lambda i is the i-th eigenvalue in the eigenvalue sequence, which is also the eigenvalue corresponding to the i-th row vector of the difference matrix, A ij and B ij are the i-th row and j-th column elements of the lower limb motion matrix and the standard motion matrix respectively, M and N are the row dimension and the column dimension of the lower limb motion matrix respectively, v is the evaluation analysis result, h i is the i-th evaluation sub-result value, and k i is the i-th element of the weight factor vector.
2. The fusion feedback processing method for rehabilitation training of lower limbs according to claim 1, wherein the feedback calculation processing is performed on the strength value sequence, the evaluation analysis result and the physiological information set to obtain a fusion feedback output value set, and the fusion feedback output value set comprises:
performing force feedback calculation processing on the force value sequence and the evaluation analysis result to obtain a force feedback value for adjusting the acting force of the lower limb rehabilitation training module to the user when the user performs lower limb rehabilitation training;
And carrying out haptic feedback calculation processing on the evaluation analysis result and the physiological information set to obtain a haptic feedback value for adjusting the haptic stimulus quantity of the user when the lower limb rehabilitation training module carries out lower limb rehabilitation training on the user.
3. The fusion feedback processing method for lower limb rehabilitation training according to claim 2, wherein the performing force feedback calculation processing on the force value sequence and the evaluation analysis result to obtain a force feedback value for adjusting the acting force of the lower limb rehabilitation training module on the user when the user performs lower limb rehabilitation training comprises:
Obtaining a standard force value;
performing force feedback calculation processing on the standard force value, the force value sequence and the evaluation analysis result to obtain a force feedback value for adjusting the acting force of the lower limb rehabilitation training module to the user when the user performs lower limb rehabilitation training;
the expression of the force feedback calculation process is as follows:
wherein, the And L 3 (v) are a second order Legendre polynomial and a third order Legendre polynomial respectively, ρ is a preset multiplication factor, f i is the ith element of the force value sequence, NF is the length of the force value sequence, f 0 is a standard force value, np is the force feedback value, and v is an evaluation analysis result.
4. The fusion feedback processing method for rehabilitation training of lower limbs according to claim 2, wherein the performing haptic feedback calculation processing on the evaluation analysis result and the physiological information set to obtain a haptic feedback value for adjusting the haptic stimulus amount of the lower limb rehabilitation training module to the user when the user performs rehabilitation training of the lower limb comprises:
the standard physiological information comprises a heart rate standard value, a blood pressure standard value, a blood oxygen saturation standard value and a body temperature standard value;
The standard physiological information is expressed as a standard physiological vector, wherein the 1 st element to the 4 th element of the standard physiological vector are respectively a heart rate standard value, a blood pressure standard value, a blood oxygen saturation standard value and a body temperature standard value;
The physiological information set is expressed as a physiological information matrix, wherein the 1 st row vector to the 4 th row vector of the physiological information matrix are respectively a heart rate information sequence, a blood pressure information sequence, a blood oxygen saturation information sequence and a body temperature information sequence;
And carrying out haptic feedback calculation processing on the evaluation analysis result, the standard physiological vector and the physiological information matrix to obtain a haptic feedback value for adjusting the haptic stimulus quantity of the user when the lower limb rehabilitation training module carries out lower limb rehabilitation training on the user.
5. The fusion feedback processing method for rehabilitation training of lower limbs according to claim 4, wherein the expression of the haptic feedback calculation process is;
Wherein pe is the haptic feedback value, v is the evaluation analysis result, T i(pi v) represents the ith order polynomial of the first chebyshev polynomial, p i is the ith feedback component, a ij represents the ith row and jth column elements of the physiological information matrix, z i represents the ith element of the standard physiological vector, exp represents the exponential operation of the constant e, and n is the length of the standard physiological vector.
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