CN117899358B

CN117899358B - Adaptive electrical stimulation balance rehabilitation training system

Info

Publication number: CN117899358B
Application number: CN202410084301.0A
Authority: CN
Inventors: 徐瑞; 白宇; 明东; 王维豪; 王紫尧; 孟琳
Original assignee: Tianjin University
Current assignee: Tianjin University
Priority date: 2024-01-19
Filing date: 2024-01-19
Publication date: 2024-10-15
Anticipated expiration: 2044-01-19
Also published as: CN117899358A

Abstract

The invention belongs to the technical field of rehabilitation therapy, and discloses a self-adaptive electric stimulation balance rehabilitation training system. According to the invention, the self-adaptive electric stimulation for disturbance is realized by collecting the joint angle of the subject in the period of maintaining balance on the multi-degree-of-freedom platform and controlling the functional electric stimulation FES parameter based on the real-time joint angle. The self-adaptive electrical stimulation strategy is realized based on the joint angle of the patient, so that the balance of the patient is maintained, and simple and effective help is provided for the rehabilitation of the apoplexy patient. The technical effect is clear, and a technical scheme is provided for individuation and active rehabilitation treatment of patients.

Description

Self-adaptive electric stimulation balance rehabilitation training system

Technical Field

The invention relates to the fields of motion analysis, rehabilitation engineering technology and electromechanical system control, in particular to a disturbance-oriented self-adaptive electric stimulation control strategy, and specifically relates to a self-adaptive electric stimulation balance rehabilitation training system. The study realizes a disturbance-oriented adaptive electrical stimulation strategy by collecting joint angles of a subject during the balance maintenance on a multi-degree-of-freedom platform and controlling functional electrical stimulation (Functional Electrical Stimulation, FES) parameters based on the real-time joint angles, so that the subject maintains balance to complete balance training.

Background

Stroke, also known as "stroke," is an acute cerebrovascular disease, and dyskinesia after stroke is mainly caused by damage to the descending spinal cord, which causes the brain to lose control of its extremities. After stroke, the balance of the patient varies from lesion to lesion, but usually there is a decrease in muscle strength, dystonia, poor coordination, a decrease in balance feeling and posture control ability.

The central nervous system of the brain assumes effective postural control (Postural Control, PC) when the person's own movements shift the center of gravity due to changes in the geometry of the limbs, to ensure that the body's center of gravity is within a supporting polygon, which refers to a virtual polygonal area formed by the person's feet as the end points, and when the person stands, the body's center of gravity is usually controlled within this virtual polygonal area formed between the feet in order to maintain body stability. Firstly, the brain can continuously detect the position of the gravity center of the body through the vestibule system, vision and proprioception to judge whether the body is in a balanced state, when the body inclination is detected, the central nervous system can instruct related muscle groups to shrink or relax to generate a correction effect, the body inclination is mainly adjusted through the cooperative shrinkage and relaxation of lower limbs and trunk muscles, such as plantar muscles, triceps calf muscles, quadriceps femoris muscles and the like, the trunk muscles are responsible for fine adjustment and posture control, the rigidity of the upper body is changed, the stability is increased, and finally, the gravity center distribution of the body part is adjusted through joints to keep the gravity center of the body in a supporting polygon, so that the body is kept balanced. In the whole process of maintaining balance, muscles are regulated to provide posture rigidity, control the posture of the trunk, make quick sounds and absorb shock, and are the most important executive organs in a balance system, and the muscle strength, speed and coordination of stroke patients directly influence the balance capacity.

In recent years, FES has been widely used for improving or restoring muscle or muscle group function and plays a role in balance recovery in stroke patients, especially in helping stroke patients improve muscle control, alleviate muscle atrophy, enhance balance and coordination. Typically FES's can be combined with rehabilitation training to assist the patient in balance and gait training. By stimulating the relevant muscle groups, the patient can better exercise standing, walking and balancing actions, or as a portable device, so that the patient can perform self-training at home, and the rehabilitation progress of the patient is promoted. Clinical studies have demonstrated that functional electrical stimulation can effectively improve motor capacity and muscle strength in hemiplegic patients. However, the single stimulation mode and lack of active participation of the patient have prevented further application of functional electrical stimulation, and FES treatment needs to be adjusted in real time according to the balance ability of the patient, so that development of an adaptive electrical stimulation balance rehabilitation system adapting to the balance ability of the patient is highly demanded.

Disclosure of Invention

The invention aims to develop a disturbance-oriented self-adaptive electric stimulation balance rehabilitation training system. The functional electric stimulation is combined with the balance task, so that the self-adaptive electric stimulation training under disturbance is realized, the coordination between the limbs and trunk muscle groups of a patient is improved, the functions of the muscles and the muscle groups are recovered, and a more effective balance rehabilitation training scheme is provided for stroke patients.

The technical scheme of the invention is that the self-adaptive electric stimulation balance rehabilitation training system mainly comprises a multi-degree-of-freedom platform, an upper computer, a PID regulator and an electric stimulator; firstly, acquiring data of joint angles of a healthy subject on a multi-degree-of-freedom platform to maintain balance under disturbance to generate a joint angle template; then, the output electric stimulation is controlled and regulated through a PID algorithm, and the real-time joint angle of the patient under disturbance is detected; and finally, taking the deviation of the real-time joint angle and the joint angle template of the patient as input, and outputting the electric stimulation parameters through a PID (proportion integration differentiation) regulating system to realize self-adaptive electric stimulation training under the disturbance condition.

The method of the system comprises the following specific steps:

(1) And (3) data acquisition: after cleaning the skin surface, respectively fixing inertial motion units on two sides of ankle joints, knee joints and hip joint body segments of a subject, standing the subject on a platform with multiple degrees of freedom, recording the changing angle of the platform in real time, carrying out small-amplitude periodic swinging of 0-5 degrees on the platform under four different oblique directions, standing the subject on the platform to keep self balance, and synchronously recording IMU signals of the subject in the balance maintaining process under different disturbance directions;

(2) Data offline processing and template establishment

Firstly removing high-frequency noise, calibrating to eliminate zero drift by detecting resting bias in a resting state, then establishing a lower limb movement model based on the static calibration to obtain joint angles, finally calibrating each piece of data to obtain joint angle data in different disturbance directions, and aligning IMU data time axes in the same disturbance direction to obtain a joint angle response template of a healthy subject;

(3) Data on-line processing and electric stimulation control realization

Inputting a joint angle template into an upper computer, acquiring a platform change angle to the upper computer in real time through an IMU (inertial measurement unit) by a patient in the using process, preprocessing data in the upper computer, acquiring real-time joint angle data of the patient under the disturbance of the platform in the same processing mode as an off-line processing mode, calculating a real-time deviation angle based on the real-time joint angle data of the patient and a joint angle response template of a healthy subject, and inputting the real-time deviation angle into a PID (proportion integration differentiation) controller to complete the control of self-adaptive electrical stimulation;

(4) PID controller for realizing self-adaptive electric stimulation control

In the adaptive electric stimulation experiment, the deviation is formed according to the joint angle response template r (t) of the healthy subject and the real-time joint angle y (t) of the patient: e (t) =r (t) -y (t), the proportion (P), integral (I) and derivative (D) of the joint angle deviation are linearly combined to form a control quantity, and the electric stimulator is controlled, wherein the control rule is as follows:

The transfer function is:

Wherein U(s) is Laplacian transformation output by the PID controller, E(s) is Laplacian transformation of joint angle deviation, K _p is a proportionality coefficient, T _i is an integral time constant, T _d is a differential time constant, K _i＝K_p/T_i is an integral coefficient, and K _d＝K_p*T_d is a differential coefficient;

(5) Functional electrical stimulation parameter control

Based on the real-time joint angle data and the joint angle response template of the healthy subject, calculating to obtain a real-time deviation angle, taking the real-time deviation angle as a control quantity, inputting the control quantity into a PID controller, and adjusting different parameters of the electric stimulation FES in real time through the controller, including frequency, pulse, duty ratio, wave rise/wave fall and current intensity, stimulating the muscle losing the nerve control by using low-frequency pulse current, and inducing the muscle movement or simulating normal autonomous movement.

Further, the frequency of the functional electrical stimulation parameter is 15-50 Hz.

Further, the pulse width of the functional electrical stimulation parameter is 100-1000 us.

Further, the duty cycle of the functional electrical stimulation parameter is between 1:1 and 1:3.

Further, the wave rise/wave fall of the functional electrical stimulation parameter takes 1-2 s.

Further, the current intensity of the functional electrical stimulation parameter is between 0mA and 100mA

Advantageous effects

According to the invention, an electrical stimulation control technology is used for collecting IMU signals of ankle joints, knee joints and hip joints, and functional electrical stimulation rehabilitation training based on the platform change angle is realized through a real-time joint angle of a patient and a healthy human joint angle template under the condition of disturbance of a multi-degree-of-freedom platform. According to the invention, the stimulation mode is automatically adjusted according to the balance capacity of the patient, the patient is not required to be relied on, the balance training of the patient is assisted, and the recovery of the muscle function of the patient is promoted, so that the patient can obtain a better recovery effect.

Drawings

FIG. 1 is a technical flow;

FIG. 2 is a schematic diagram of an execution action;

FIG. 3 is an electrical stimulation output logic diagram;

FIG. 4 is a diagram outlining PID control;

Figure 5 is a functional electrical stimulation parameter diagram.

Detailed Description

The invention is further described below with reference to the accompanying drawings.

The existing electric stimulation device cannot realize an electric stimulation training scheme capable of being adjusted in real time according to the balance state of a patient when the patient faces disturbance. The invention provides a disturbance-oriented self-adaptive electric stimulation balance rehabilitation training system, which can realize a self-adaptive electric stimulation strategy based on the joint angle of a patient, further help the patient maintain balance, and provide simple and effective help for rehabilitation of stroke patients. The technical effect is clear, and a technical scheme is provided for individuation and active rehabilitation treatment of patients.

The self-adaptive electric stimulation balance rehabilitation training system firstly generates a joint angle template according to the data of the healthy subject under disturbance, then controls functional electric stimulation through a PID control algorithm, takes the real-time angle of the joint of the patient under disturbance and the deviation of the joint angle template as input, realizes self-adaptive electric stimulation training under the disturbance condition, and assists the patient to adjust the joint angle through a healthy artificial template. The general technical flow is shown in figure 1.

Data acquisition (one)

After cleaning the skin surface, the inertial motion units (Inertial Motion Unit, IMU) are respectively stuck to the two sides of the ankle joint, the knee joint and the hip joint of the subject, and are firmly fixed by using elastic bandages and the like, so that looseness is avoided. The subject stands on the platform with multiple degrees of freedom, the inertial gyroscope is arranged on the platform to record the changing angle of the platform in real time, the platform swings in small amplitude period of 0-5 degrees in four different tilting directions, the subject stands on the platform to keep self balance, as shown in figure 2, 1 represents pelvis, 2 represents thigh, 3 represents calf and 4 represents foot. IMU signals during the subject's maintenance balance in different disturbance directions were recorded simultaneously.

(II) offline data processing and template establishment

And performing off-line processing on the acquired IMU signals, firstly removing high-frequency noise through a low-pass filter, performing calibration to eliminate zero drift by detecting resting bias in a resting state, then establishing a lower limb movement model based on the static calibration to obtain joint angles, finally calibrating each piece of data to obtain joint angle data in different disturbance directions, and aligning IMU data time axes in the same disturbance direction to obtain a joint angle response template of a healthy subject.

(III) data on-line processing and electric stimulation control realization

The method comprises the steps of inputting a joint angle template into an upper computer, acquiring a platform change angle to the upper computer in real time through an IMU (inertial measurement unit) in the using process of a stroke patient, preprocessing data in the upper computer, obtaining real-time joint angle data under platform disturbance in the same processing mode as an off-line processing mode, calculating a real-time deviation angle based on the real-time joint angle data and a healthy subject joint angle response template, and inputting the real-time deviation angle into a PID (proportion integration differentiation) controller to complete the control of self-adaptive electrical stimulation. The overall control method works in principle, please refer to fig. 3.

(IV) implementation of adaptive electro-stimulation control by PID controller

The PID controller is a linear controller, and forms deviation with the actual joint angle y (t) of the patient according to the joint angle response template r (t) of the healthy subject: e (t) =r (t) -y (t). The proportion (P), integral (I) and derivative (D) of the joint angle deviation are linearly combined to form a control quantity, so that the control of the electric stimulator is realized:

The transfer function is:

Wherein U(s) is Laplacian transformation output by the PID controller, E(s) is Laplacian transformation of joint angle deviation, K _p is a proportionality coefficient, T _i is an integral time constant, and T _d is a differential time constant; k _i＝K_p/T_i is an integral coefficient; k _d＝K_p*T_d is the differential coefficient.

Wherein, the function of each correction link of the PID controller:

The proportional link is used for proportionally reflecting the real-time deviation angle value e (t) of the control system, and once the joint angle deviation of the patient and the healthy subject is generated, the controller immediately generates a responsive control action to reduce the error, and the proportional control is regulated based on the joint angle deviation;

the integral link can memorize the angle deviation, is mainly used for eliminating static difference and improving the no-difference degree of the system, and the intensity of the integral action depends on the integral time constant Ti, and the larger the integral time constant Ti is, the weaker the integral action is;

the differential ring can save energy, reflect the change rate of the joint angle deviation, and can introduce an effective early correction signal into the system before the joint angle deviation value of the patient and the healthy subject gradually becomes larger, so that the action speed of the system is accelerated, and the adjustment time is reduced. (V) functional Electrical stimulation implementation parameters

Functional Electrical Stimulation (FES) belongs to the category of Neuromuscular Electrical Stimulation (NES), and is to stimulate one or more groups of muscles by a preset program using a low-frequency pulse current with a certain intensity, induce muscle movement and simulate normal autonomous movement, so as to improve or restore the function of the stimulated muscles or muscle groups, and different parameters need to be adjusted according to specific experiments and patient conditions. The frequency is 1-100 Hz in theory, wherein the lower frequency is less than 20Hz, the action effect is not great, but the muscle is not easy to fatigue; higher frequencies >50Hz, which are prone to muscle tonic contractions, but muscles are prone to fatigue, often between 15 and 50 Hz. The pulse width is usually 100-1000 us, and 200-300 us is used more, so that the pulse width is relatively fixed in treatment.

The duty ratio (power on/off ratio) is mostly between 1:1 and 1:3, and is related to the fatigue resistance degree of the person who stimulates the muscles, and the muscles are electrified, contracted, moved and released when power is off.

Wave rise/wave fall: wave rise refers to the time required to reach maximum current, wave fall refers to the time required to fall back from maximum current to power off, and wave rise and wave fall are usually 1 to 2 seconds.

The current intensity is between 0mA and 100mA when the surface electrode is used in general FES, and can be specifically adjusted according to the tolerance condition and the stimulation purpose of patients.

(VI) rehabilitation effect verification

After the functional electric stimulation training, a scientific evaluation method is required to be applied to verify the improvement effect of the patient after the rehabilitation training, and the effectiveness and the reliability of the self-adaptive electric stimulation balance rehabilitation training are verified.

Movement Index (MI)

Through the MI index, a single basic movement of the lower limb joint can be analyzed to assess muscle strength. Ankle dorsiflexion, knee extension, and hip flexion were explored for the lower extremities. Muscle activity was divided into 6 classes, which were converted into weighted scores. For each joint, the score ranges from 0 (no motion) to 33 (normal power), with the total score of the joint ranging from 0-99.MI shows excellent internal rating and retest reliability in chronic stroke patients.

Fugl-Meyer lower extremity evaluation (FMA-LE)

FMA is mainly used to evaluate recovery of sensorimotor performance in stroke patients. FMA-LE explored hip, knee and ankle movements and recorded layered recovery from reflex to cooperative and non-cooperative movements based on the brunstrom recovery phase. FMA-LE motion fields use a 3-point sequence scale: 0, unable to be executed; 1. partial performance; 2. the performance is complete, the possible score ranges from 0 to 34, the coordination, the sensory function, the joint movement degree and the joint pain of the patient are also evaluated, and the study proves that the index has high reliability in scoring and retesting of the cerebral apoplexy patient.

10M walking test (10 mWT)

10MWT calculates the walking speed by measuring the time required to walk 10m at the patient selected speed. The test was repeated intermittently 3 times and the average value was calculated. Personal aids may be used during the test, allowing for additional acceleration and deceleration phases, and not used in determining speed. The test can rapidly evaluate walking conditions, is widely used for evaluating stroke patients, musculoskeletal disease patients and healthy people, and has excellent scoring performance and retest reliability.

Berger Balance Scale (BBS)

The BBS can objectively measure the patient's balance and fall risk. The BBS explores 14 actions in daily life on a 5-point sequential scale (range 0-4). A score of 0 indicates the lowest functional level, a score of 4 indicates normal performance, and the total score ranges from 0 to 56. One study showed an increased risk of falls for patients with BBS scores greater than 45. BBS is widely used to evaluate stroke patients, with excellent reliability in both acute and chronic stroke patients in terms of rating and inter-remitter confidence. The structural efficiency is good to excellent compared with other balance indexes.

TUG test

The TUG test is used to measure the balance and functional walking of a patient. A chair with a backrest and armrests was placed at the end of a 3-meter aisle. The inspector measures the time that the subject takes to stand up from the chair, walk 3 meters, turn around, walk back to the chair and sit down. TUG tests are widely used to evaluate stroke patients, parkinson's disease, and various musculoskeletal disease patients. The TUG test shows excellent scoring grade and retest reliability in acute to chronic stroke patients. Compared with other indexes, the index has good construction efficiency.

Claims

1. An adaptive electrical stimulation balance rehabilitation training system, characterized in that the system is mainly composed of a multi-degree-of-freedom platform, a host computer, a PID regulator and an electrical stimulator; first, the data of the joint angles of healthy subjects maintaining balance on the multi-degree-of-freedom platform are collected under disturbance to generate a joint angle template; then, the output electrical stimulation is adjusted through the PID algorithm control to detect the real-time joint angle of the patient under disturbance; finally, the deviation between the real-time joint angle of the patient and the joint angle template is used as input, and the electrical stimulation parameters are output through the PID adjustment system to achieve adaptive electrical stimulation training under disturbance;

The specific steps are as follows:

(1) Data collection: After cleaning the skin surface, the inertial motion units were fixed on both sides of the subject's ankle, knee, and hip joints. The subject was asked to stand on a multi-degree-of-freedom platform, and the platform angle change was recorded in real time. The platform was swung in a small amplitude of 0 to 5° in four different tilt directions: front, back, left, and right. The subject stood on the platform to maintain his or her balance, and the IMU signals of the subject maintaining balance in different disturbance directions were recorded synchronously.

(2) Offline data processing and template creation

First, high-frequency noise is removed, and calibration is performed to eliminate zero drift by detecting the resting bias in the static state. Then, a lower limb motion model is established based on static calibration to obtain joint angles. Finally, each segment of data is calibrated to obtain joint angle data under different disturbance directions. The time axis of the IMU data under the same disturbance direction is aligned to obtain the joint angle response template of healthy subjects.

(3) Online data processing and electrical stimulation control

The joint angle template is input into the host computer. When the patient is in use, the platform change angle is collected in real time to the host computer through the IMU. The data is preprocessed in the host computer in the same way as the offline processing method to obtain the patient's real-time joint angle data under platform disturbance. The real-time deviation angle is calculated based on the patient's real-time joint angle data and the joint angle response template of the healthy subjects, and then input into the PID controller to complete the control of the adaptive electrical stimulation.

(4) PID controller realizes adaptive electrical stimulation control

In the adaptive electrical stimulation experiment, the joint angle response template r(t) of the healthy subjects and the patient's real-time joint angle y(t) constitute a deviation: e(t) = r(t) - y(t). The proportion (P), integral (I) and differential (D) of the joint angle deviation are linearly combined to form a control quantity to control the electrical stimulator. The control law is:

The transfer function is:

Wherein, U(s) is the Laplace transform of the PID controller output, E(s) is the Laplace transform of the joint angle deviation, _Kp is the proportional coefficient, _Ti is the integral time constant, _Td is the differential time constant, _Ki = _Kp / _Ti is the integral coefficient, and _Kd = _Kp * _Td is the differential coefficient;

(5) Functional electrical stimulation parameter control

The real-time deviation angle is calculated based on the real-time joint angle data and the joint angle response template of healthy subjects, and then input into the PID controller as the control quantity. The controller adjusts the different parameters of FES in real time, including frequency, pulse, duty cycle, wave rise/wave fall, and current intensity. Low-frequency pulse current is used to stimulate muscles that have lost nerve control, inducing muscle movement or simulating normal voluntary movement.

2. The adaptive electrical stimulation balance rehabilitation training system according to claim 1, characterized in that the frequency of the functional electrical stimulation parameters is between 15 and 50 Hz.

3. The adaptive electrical stimulation balance rehabilitation training system according to claim 1, characterized in that the pulse width of the functional electrical stimulation parameter is between 100 and 1000 us.

4. The adaptive electrical stimulation balance rehabilitation training system according to claim 1, characterized in that the duty cycle of the functional electrical stimulation parameters is between 1:1 and 1:3.

5 . The adaptive electrical stimulation balance rehabilitation training system according to claim 1 , wherein the wave rise/wave fall of the functional electrical stimulation parameter is 1 to 2 seconds.

6 . The adaptive electrical stimulation balance rehabilitation training system according to claim 1 , wherein the functional electrical stimulation parameter has a current intensity of 0 mA to 100 mA.