CN111135012A - Training method based on hand rehabilitation training device - Google Patents

Training method based on hand rehabilitation training device Download PDF

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Publication number
CN111135012A
CN111135012A CN201911336074.1A CN201911336074A CN111135012A CN 111135012 A CN111135012 A CN 111135012A CN 201911336074 A CN201911336074 A CN 201911336074A CN 111135012 A CN111135012 A CN 111135012A
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freedom
user
gear motor
current
wrist
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张佳楫
左国坤
史斌君
徐佳琳
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Ningbo Institute of Material Technology and Engineering of CAS
Cixi Institute of Biomedical Engineering CIBE of CAS
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Ningbo Institute of Material Technology and Engineering of CAS
Cixi Institute of Biomedical Engineering CIBE of CAS
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
    • A61H1/00—Apparatus for passive exercising; Vibrating apparatus; Chiropractic devices, e.g. body impacting devices, external devices for briefly extending or aligning unbroken bones
    • A61H1/02—Stretching or bending or torsioning apparatus for exercising
    • A61H1/0274—Stretching or bending or torsioning apparatus for exercising for the upper limbs
    • A61H1/0285—Hand
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B21/00—Exercising apparatus for developing or strengthening the muscles or joints of the body by working against a counterforce, with or without measuring devices
    • A63B21/00181—Exercising apparatus for developing or strengthening the muscles or joints of the body by working against a counterforce, with or without measuring devices comprising additional means assisting the user to overcome part of the resisting force, i.e. assisted-active exercising
    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B23/00—Exercising apparatus specially adapted for particular parts of the body
    • A63B23/035—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously
    • A63B23/12—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously for upper limbs or related muscles, e.g. chest, upper back or shoulder muscles
    • A63B23/14—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously for upper limbs or related muscles, e.g. chest, upper back or shoulder muscles for wrist joints
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
    • A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
    • A61H2201/12—Driving means
    • A61H2201/1207—Driving means with electric or magnetic drive
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
    • A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
    • A61H2201/16—Physical interface with patient
    • A61H2201/1602—Physical interface with patient kind of interface, e.g. head rest, knee support or lumbar support
    • A61H2201/1635—Hand or arm, e.g. handle
    • A61H2201/1638—Holding means therefor
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
    • A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
    • A61H2201/50—Control means thereof
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
    • A61H2205/00—Devices for specific parts of the body
    • A61H2205/06—Arms
    • A61H2205/065—Hands

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  • Health & Medical Sciences (AREA)
  • Orthopedic Medicine & Surgery (AREA)
  • General Health & Medical Sciences (AREA)
  • Physical Education & Sports Medicine (AREA)
  • Life Sciences & Earth Sciences (AREA)
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  • Pain & Pain Management (AREA)
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Abstract

The invention discloses a training method based on a hand rehabilitation training device, wherein the hand rehabilitation training device comprises a first speed reduction motor, a second speed reduction motor and a third speed reduction motor which are used for respectively carrying out three-degree-of-freedom posture control on a palm tray; the first gear motor, the second gear motor and the third gear motor are provided with angle sensors for measuring rotation angles in each degree of freedom, the first gear motor, the second gear motor, the third gear motor and each angle sensor are electrically connected with an industrial personal computer, and the industrial personal computer is provided with a motor driving and controlling circuit which is electrically or wirelessly connected with an upper computer; the invention can quantitatively judge the active participation degree of the patient to the training task according to the training condition after single training.

Description

Training method based on hand rehabilitation training device
Technical Field
The invention relates to the technical field of medical instrument control, in particular to a training method based on a hand rehabilitation training device.
Background
In China, the number of people with brain injury such as brain trauma and cerebral palsy caused by accidents and environmental pollution is considerable, and particularly, with the coming of aging society, cerebral apoplexy becomes a main factor of movement dysfunction and hemiplegia. With increasing levels of medical care, the mortality rate from stroke is gradually decreasing, but of stroke survivors, approximately 80-90% of patients suffer from hand motor function deficits, loss of voluntary living and motor abilities. The normal work and life of the patient are seriously affected, and the nursing is time-consuming and labor-consuming, and burdens the society and families. Therefore, the rehabilitation training system for hands becomes a hot point of research.
Medical theory and practice prove that the limb movement function of a hemiplegic patient caused by stroke can be recovered to a certain degree through a large amount of repetitive function training. The rehabilitation robot is used for assisting rehabilitation training, so that a large amount of manpower and material resources can be saved, the rehabilitation level of a patient can be evaluated in a real-time and quantitative manner, and the whole rehabilitation industry is influenced positively.
Research proves that single joint independent training is more effective than multi-joint simultaneous training in rehabilitation training, so that aiming at the characteristics of wrist rehabilitation, repeated passive training needs to be carried out aiming at a certain degree of freedom of the wrist, but meanwhile, in the training process, the movement intention and the movement capability of a trainer need to be evaluated in real time, the passive training mode and the active training mode are switched in time, and the trainer is assisted to carry out better rehabilitation.
In the existing wrist rehabilitation training device, the CPM system is mainly used for hands, but the CPM system is used as a continuous passive system for hands, only has a passive training mode and does not have an active training function, and the motion size of hand assistance cannot be adjusted in time according to the wrist motion intention and the motion capability of a user.
Disclosure of Invention
The technical problem to be solved by the invention is to overcome the defects of the prior art: the method can quantitatively judge the active participation degree of the patient to the training task according to the training condition after single training.
The hardware equipment of the invention is a hand rehabilitation training device based on the patent number CN 209630106U published by the applicant: the palm support device comprises a base, an arm tray fixed on the base, an L-shaped first rotary support arm, a T-shaped second rotary support arm and a palm tray; the first end of the first rotary supporting arm can rotate around a vertical central rotation axis relative to the base, and the first end of the second rotary supporting arm can rotate around a horizontal central rotation axis relative to the second end of the first rotary supporting arm; the palm tray can rotate around a horizontal central axis of rotation relative to the second end of the second rotary support arm. The device is used for driving a synchronous belt to carry out three-degree-of-freedom attitude control on the palm tray by a first speed reducing motor, a second speed reducing motor and a third speed reducing motor.
The invention designs a rehabilitation training algorithm containing a reward and punishment mechanism, and after a training period, the difficulty of next training is adjusted according to the quantitative data of the active participation degree of a patient so as to prevent a trainer from lacked in training.
The technical solution of the invention is as follows: a training method based on a hand rehabilitation training device comprises a first gear motor, a second gear motor and a third gear motor, wherein the first gear motor, the second gear motor and the third gear motor are used for respectively carrying out three-degree-of-freedom posture control on a palm tray; the first gear motor, the second gear motor and the third gear motor are provided with a device for measuring the rotation angle theta of each degree of freedom1、θ2、θ3And the angle sensor, first gear motor, second gear motor, third gear motor and each angle sensor all are connected with the industrial computer electricity, the industrial computer is equipped with motor drive and control circuit, and it is connected with host computer electricity or wireless connection:
the definition of the rotation angle in rehabilitation training is as follows:
θ1: the direction of motion of palmar flexion and dorsal extension;
θ2: ulnar deviation and radial deviation movement direction;
θ3: forearm pronation/supination direction of motion;
the specific algorithm is as follows:
1) the upper computer prompts the movement direction of the user for wrist training, induces the trainer to move the wrist in the direction of the specified degree of freedom, and generates the expected angle theta at each moment by the following formuladDesired angular velocity
Figure BDA0002330941870000021
Figure BDA0002330941870000022
Wherein, thetad: desired angle of theta1、θ2、θ3A desired angle of one of them;
t: expecting a time independent variable of the angle function, and training starting time t is 0;
la: the angle from the starting point of the starting section to the starting point of the stopping section is set by a user according to the rehabilitation training requirement;
ta：lacorresponding movement duration; said t isaCan be set by a user according to the rehabilitation training requirement;
wherein the angular velocity is desired
Figure BDA0002330941870000023
Can be obtained by derivation of formula (1);
2) the industrial personal computer judges whether t is less than or equal to taIf yes, jumping to the step 3) to be executed in sequence; if not, jumping to the step 6) to execute in sequence;
3) real-time detection of the actual current angle theta and the current angular velocity of the wrist of the trainer rotated in the specified degree of freedom
Figure BDA0002330941870000031
4) Calculating the deviation of the current angle from the expected angle and the current angular speed from the expected angular speed:
Figure BDA0002330941870000032
5) calculating the output torque tau of the driving motor with the current appointed degree of freedom according to the self-adaptive control ratem：
5.1) calculating the following parameters according to the physical characteristics of the hand rehabilitation training device:
Figure BDA0002330941870000033
θ: current angle of current specified degree of freedom selected from theta1、θ2、θ3；
τf: the coulomb friction force of the moving part of the wrist rehabilitation training device in the direction of the current specified degree of freedom;
A1、A2、B1、B2、C1、C2: coulomb friction model parameters, which can be obtained by performing friction parameter identification experiment in the direction of the current specified degree of freedom;
τg(θ)＝MagLbcos(θ) (3)
τg(θ): the current specified degree of freedom drives the gravity moment born by the motor;
g: acceleration of gravity;
θ: currently specifying an angle of freedom;
Ma: the quality of the moving part of the wrist rehabilitation training device in the current specified degree of freedom;
Lb: the wrist rehabilitation training device is used for determining the distance from the center of mass of the moving part to the rotation center in the current specified degree of freedom;
τw＝MbgLbcos(θ) (4)
τw: the hand of the user needs to provide the moment for the current specified freedom degree activity under the condition of not needing the assistance of a wrist rehabilitation training device;
Mb: quality of moving part of user's hand in current specified degree of freedomAn amount;
Lb: the distance between the center of mass of the moving part of the hand of the user on the current specified degree of freedom and the moving center point of the wrist;
wherein M isb、LbThe average physical value of the hand of the user can be calculated according to the difference between the age and the gender of the user and by referring to human body data in national standard GB 10000-1988;
Figure BDA0002330941870000041
i: the moment of inertia of the movable part of the wrist rehabilitation training device in the direction of the current specified degree of freedom;
γ: calculating the torque required to be provided by the driving motor of the wrist rehabilitation training device in the direction of the current specified degree of freedom according to the ideal state;
5.2) calculating the moment tau of the self-adaptive track tracking motor1：
Figure BDA0002330941870000042
Figure BDA0002330941870000043
Figure BDA0002330941870000044
Figure BDA0002330941870000045
Figure BDA0002330941870000046
The initial value of the estimated value of the real physical system parameter a is 1, and the estimation is carried out after the control algorithm starts;
Figure BDA0002330941870000047
variation of estimated values of parameters of real physical systemThe initial value of the rate is 0, and the control algorithm is updated after starting;
c: sliding mode surface parameters, specified by a user; typically ranges between [0.15 ]; a larger parameter indicates that the control system will track the desired curve faster, and a smaller parameter value indicates that the system will track the desired curve slower;
β(Es) The training difficulty evaluation method comprises the steps of determining difficulty of training according to active participation (Es) after last training, wherein the larger the parameter value is, the smaller the training difficulty is, otherwise, the smaller the parameter is, the parameter is 10000 during the first training, and after the training starts, the calculation method of the parameter is shown in step 7. according to the training difficulty evaluation method, a reward punishment factor is introduced, the principle is that the difficulty of the training is adjusted according to the active participation degree of a trainee during last training, the reward punishment factor β is increased when the training difficulty needs to be reduced, the wrist can track an expected rule only by paying a small moment during training, and otherwise, the reward punishment factor β is reduced when the training difficulty needs to be increased, and the wrist can track the expected trajectory only by paying a large moment during training, so that the training person is prevented from being lacked.
5.3) calculating the compliance control moment tau2：
Figure BDA0002330941870000048
k: stiffness parameters in compliance control, adjustable by a user;
b: damping parameters in the compliance control, adjustable by the user;
the compliance control moment tau applied in the step is designed2The aim is that when the actual training track of the trainer deviates from the expected track, the controller can apply a reverse moment with a soft feeling to the hand of a person to induce the motion track of the trainer to return to the planned motion track.
Calculating the comprehensive output torque tau of the driving motor in the direction of the current specified degree of freedommMoment τ applied by the user at the current moments：
τm＝τ1+τ2(11)
τs＝γ-τm(12)
Equation (10) is used to estimate the moment applied by the trainer at the present moment, and its principle lies in
Figure BDA0002330941870000051
6) Calculating the wrist payment energy E of the user for the trainings：
Es＝∫τsdθ
7) Updating next training reward and punishment factor β (E)s)：
Figure BDA0002330941870000052
8) Using updated reward penalty factor β (E)s) The next training is started.
Wherein the initial state of the palm tray of the wrist rehabilitation training device in the horizontal forward direction is defined as theta1、θ2、θ3The initial value is 0.
The invention has the beneficial effects that: the existing wrist rehabilitation system cannot provide auxiliary force according to the capacity of a patient. Because the existing wrist rehabilitation training system cannot judge the motor ability of the patient in real time according to the motor performance of the patient, the auxiliary force cannot be provided to the patient in real time according to the requirement. Most of the existing wrist rehabilitation systems cannot adaptively adjust the training scheme according to the performance of a trainer. After a certain number of training sessions, the patient has different exercise ability from that before the training session, so it is necessary to evaluate the training effect and adjust the training parameters in the next training session according to the training session.
The self-adaptive method adopted by a few existing wrist rehabilitation systems does not adjust the difficulty of next training in time according to the active participation degree of a patient during training, and a trainer produces subjective lackluster after a plurality of times of training.
The invention provides the active participation evaluation by taking the wrist energy as an index when a trainee trains, so that the active participation degree of the wrist rehabilitation training can be quantized.
According to the invention, reward and punishment factors are introduced, active participation is taken as an index, a proper function is designed to adjust the training difficulty, the trainee is prevented from being lacked, and the rehabilitation effect is improved.
Drawings
FIG. 1 is a schematic diagram of a wrist rehabilitation training device system of the present invention;
FIG. 2 is a flow chart of the algorithm of the present invention;
FIG. 3 is a schematic diagram of adaptive control rate of the present invention;
Detailed Description
The present invention will be described in further detail with reference to the following examples, but the present invention is not limited to the following examples.
Examples
The following examples show the direction of dorsiflexion and dorsiflexion motion1Training as the specified degree of freedom direction:
the specific algorithm is as follows:
1) the upper computer prompts the movement direction of the user for wrist training and induces the training person to move the wrist in the palm bending and back stretching movement direction, and the corresponding rotation angle is theta1And a desired angle theta at each time is generated by the following formuladDesired angular velocity
Figure BDA0002330941870000061
Figure BDA0002330941870000062
Wherein, thetad：θ1The desired angle of (d);
t: expecting a time independent variable of the angle function, and training starting time t is 0;
la: the angle from the starting point of the starting section to the starting point of the stopping section is set by a user according to the rehabilitation training requirement, and l is set at the positiona＝π/6；
ta：laCorresponding movement duration; said t isaCan be set by a user according to the rehabilitation training requirement, and t is set at the positiona＝3s；
Wherein the angular velocity is desired
Figure BDA0002330941870000063
Can be obtained by derivation of formula (1);
2) the industrial personal computer judges whether t is less than or equal to taIf yes, jumping to the step 3) to be executed in sequence; if not, jumping to the step 6) to execute in sequence;
3) real-time detection of the actual current angle theta and the current angular velocity of the wrist of the trainer rotated in the specified degree of freedom
Figure BDA0002330941870000064
4) Calculating the deviation of the current angle from the expected angle and the current angular speed from the expected angular speed:
Figure BDA0002330941870000071
5) calculating the output torque tau of the driving motor with the current appointed degree of freedom according to the self-adaptive control ratem：
5.1) calculating the following parameters according to the physical characteristics of the hand rehabilitation training device:
Figure BDA0002330941870000072
θ: current angle of current specified degree of freedom selected from theta1、θ2、θ3；
τf: the coulomb friction force of the moving part of the wrist rehabilitation training device in the direction of the current specified degree of freedom;
A1、A2、B1、B2、C1、C2: coulomb friction model parameters, which can be obtained by performing friction parameter identification experiment in the direction of the current specified degree of freedom;
τg(θ)＝MagLbcos(θ) (3)
τg(θ): the current specified degree of freedom drives the gravity moment born by the motor;
g: acceleration of gravity;
θ: currently specifying an angle of freedom;
Ma: the quality of the moving part of the wrist rehabilitation training device in the current specified degree of freedom;
Lb: the wrist rehabilitation training device is used for determining the distance from the center of mass of the moving part to the rotation center in the current specified degree of freedom;
τw＝MbgLbcos(θ) (4)
τw: the hand of the user needs to provide the moment for the current specified freedom degree activity under the condition of not needing the assistance of a wrist rehabilitation training device;
Mb: the quality of the moving part of the user's hand in the current specified degree of freedom;
Lb: the distance between the center of mass of the moving part of the hand of the user on the current specified degree of freedom and the moving center point of the wrist;
wherein M isb、LbThe average physical value of the hand of the user can be calculated according to the difference between the age and the gender of the user and by referring to human body data in national standard GB 10000-1988;
Figure BDA0002330941870000073
i: the moment of inertia of the movable part of the wrist rehabilitation training device in the direction of the current specified degree of freedom;
γ: calculating the torque required to be provided by the driving motor of the wrist rehabilitation training device in the direction of the current specified degree of freedom according to the ideal state;
5.2) calculating the moment tau of the self-adaptive track tracking motor1：
Figure BDA0002330941870000081
Figure BDA0002330941870000082
Figure BDA0002330941870000083
Figure BDA0002330941870000084
Figure BDA0002330941870000085
The initial value of the estimated value of the real physical system parameter a is 1, and the estimation is carried out after the control algorithm starts;
a: the ratio of the output of the mathematical model of the physical system to the output of the real physical system, which reflects the degree of fidelity of the physical system to the real physical system, represents that the simulation value of the mathematical model of the physical system is identical to the output value of the real physical system when the value is 1.
Figure BDA0002330941870000086
The change rate of the real physical system parameter estimation value is 0 in the initial value, and the control algorithm is updated after the control algorithm is started;
c: sliding mode surface parameters, specified by a user; typically ranges between [0.15 ]; a larger parameter indicates that the control system will track the desired curve faster, and a smaller parameter value indicates that the system will track the desired curve slower;
β(Es): reward and punishment factors with an initial value of 10000;
5.3) calculating the compliance control moment tau2：
Figure BDA0002330941870000087
k: stiffness parameters in compliance control, adjustable by a user;
b: damping parameters in the compliance control, adjustable by the user;
the compliance control moment tau applied in the step is designed2The aim is that when the actual training track of the trainer deviates from the expected track, the controller can apply a reverse moment with a soft feeling to the hand of a person to induce the motion track of the trainer to return to the planned motion track.
Calculating the comprehensive output torque tau of the driving motor in the direction of the current specified degree of freedommMoment τ applied by the user at the current moments：
τm＝τ1+τ2(11)
τs＝γ-τm(12)
Equation (10) is used to estimate the moment applied by the trainer at the present moment, and its principle lies in
Figure BDA0002330941870000091
6) Calculating the wrist payment energy E of the user for the trainings：
Es＝∫τsdθ
7) Updating next training reward and punishment factor β (E)s)：
Figure BDA0002330941870000092
8) Using updated reward penalty factor β (E)s) The next training is started.
The above are merely characteristic embodiments of the present invention, and do not limit the scope of the present invention in any way. All technical solutions formed by equivalent exchanges or equivalent substitutions fall within the protection scope of the present invention.

Claims (2)

1. A training method based on a hand rehabilitation training device comprises a first gear motor, a second gear motor and a third gear motor, wherein the first gear motor, the second gear motor and the third gear motor are used for respectively carrying out three-degree-of-freedom posture control on a palm tray;the device is characterized in that the first gear motor, the second gear motor and the third gear motor are provided with a device for measuring the rotation angle theta of each degree of freedom1、θ2、θ3And the angle sensor, first gear motor, second gear motor, third gear motor and each angle sensor all are connected with the industrial computer electricity, the industrial computer is equipped with motor drive and control circuit, and it is connected with host computer electricity or wireless connection:
the definition of the rotation angle in rehabilitation training is as follows:
θ1: the direction of motion of palmar flexion and dorsal extension;
θ2: ulnar deviation and radial deviation movement direction;
θ3: forearm pronation/supination direction of motion;
the specific algorithm is as follows:
1) the upper computer prompts the movement direction of the user for wrist training, induces the trainer to move the wrist in the direction of the specified degree of freedom, and generates the expected angle theta at each moment by the following formuladDesired angular velocity
Figure FDA0002330941860000011
Figure FDA0002330941860000012
Wherein, thetad: desired angle of theta1、θ2、θ3A desired angle of one of them;
t: expecting a time independent variable of the angle function, and training starting time t is 0;
la: the angle from the starting point of the starting section to the starting point of the stopping section is set by a user according to the rehabilitation training requirement;
ta：lacorresponding movement duration; said t isaCan be set by a user according to the rehabilitation training requirement;
wherein the angular velocity is desired
Figure FDA0002330941860000013
Can be obtained by derivation of formula (1);
2) the industrial personal computer judges whether t is less than or equal to taIf yes, jumping to the step 3) to be executed in sequence; if not, jumping to the step 6) to execute in sequence;
3) real-time detection of the actual current angle theta and the current angular velocity of the wrist of the trainer rotated in the specified degree of freedom
Figure FDA0002330941860000014
4) Calculating the deviation of the current angle from the expected angle and the current angular speed from the expected angular speed:
Figure FDA0002330941860000015
5) calculating the output torque tau of the driving motor with the current appointed degree of freedom according to the self-adaptive control ratem：
5.1) calculating the following parameters according to the physical characteristics of the hand rehabilitation training device:
Figure FDA0002330941860000021
θ: current angle of current specified degree of freedom selected from theta1、θ2、θ3；
τf: the coulomb friction force of the moving part of the wrist rehabilitation training device in the direction of the current specified degree of freedom;
A1、A2、B1、B2、C1、C2: coulomb friction model parameters, which can be obtained by performing friction parameter identification experiment in the direction of the current specified degree of freedom;
τg(θ)＝MagLbcos(θ) (3)
τg(θ): the current specified degree of freedom drives the gravity moment born by the motor;
g: acceleration of gravity;
θ: currently specifying an angle of freedom;
Ma: the quality of the moving part of the wrist rehabilitation training device in the current specified degree of freedom;
Lb: the wrist rehabilitation training device is used for determining the distance from the center of mass of the moving part to the rotation center in the current specified degree of freedom;
τw＝MbgLbcos(θ) (4)
τw: the hand of the user needs to provide the moment for the current specified freedom degree activity under the condition of not needing the assistance of a wrist rehabilitation training device;
Mb: the quality of the moving part of the user's hand in the current specified degree of freedom;
Lb: the distance between the center of mass of the moving part of the hand of the user on the current specified degree of freedom and the moving center point of the wrist;
wherein M isb、LbThe average physical value of the hand of the user can be calculated according to the difference between the age and the gender of the user and by referring to human body data in national standard GB 10000-1988;
Figure FDA0002330941860000022
i: the moment of inertia of the movable part of the wrist rehabilitation training device in the direction of the current specified degree of freedom;
γ: calculating the torque required to be provided by the driving motor of the wrist rehabilitation training device in the direction of the current specified degree of freedom according to the ideal state;
5.2) calculating the moment tau of the self-adaptive track tracking motor1：
Figure FDA0002330941860000031
Figure FDA0002330941860000032
Figure FDA0002330941860000033
Figure FDA0002330941860000034
Figure FDA0002330941860000035
The initial value of the estimated value of the real physical system parameter a is 1, and the estimation is carried out after the control algorithm starts;
a, the ratio of the output of the mathematical model of the physical system to the output of the real physical system, wherein the value reflects the fidelity of the physical system and the real physical system, and when the value is 1, the simulation numerical value of the mathematical model of the physical system is completely the same as the output value of the real physical system;
Figure FDA0002330941860000036
the change rate of the real physical system parameter estimation value is 0 in the initial value, and the control algorithm is updated after the control algorithm is started;
c: sliding mode surface parameters, specified by a user;
β(Es): reward and punishment factors with an initial value of 10000;
5.3) calculating the compliance control moment tau2：
Figure FDA0002330941860000037
k: stiffness parameters in compliance control, adjustable by a user;
b: damping parameters in the compliance control, adjustable by the user;
calculating the comprehensive output torque tau of the driving motor in the direction of the current specified degree of freedommMoment τ applied by the user at the current moments：
τm＝τ1+τ2(11)
τs＝γ-τm(12)
Equation (10) is used to estimate the moment applied by the trainer at the present moment, and its principle lies in
Figure FDA0002330941860000038
6) Calculating the wrist payment energy E of the user for the trainings:
Es＝∫τsdθ
7) Updating next training reward and punishment factor β (E)s)：
Figure FDA0002330941860000041
8) Using updated reward penalty factor β (E)s) The next training is started.
2. A training method based on a hand rehabilitation training device according to claim 1, characterized in that the horizontal forward direction of the palm tray of the wrist rehabilitation training device is defined as θ1、θ2、θ3Are all initial states of 0.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114831847A (en) * 2022-03-29 2022-08-02 中国农业大学 Neck rehabilitation training robot with four branched chain parallel mechanisms and force control method thereof

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114831847A (en) * 2022-03-29 2022-08-02 中国农业大学 Neck rehabilitation training robot with four branched chain parallel mechanisms and force control method thereof

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