CN110404168B - An Adaptive Electrical Stimulation Training System - Google Patents

Abstract

The invention discloses a self-adaptive electric stimulation training system, which comprises an information acquisition module, an analog-to-digital conversion module, an electric stimulation control module and a multi-channel electric stimulator, wherein the electric stimulation control module comprises an iterative learning controller and a linear controller, the kinematic signals and the dynamic signals which are acquired by the information acquisition module and synchronously transmitted by the analog-to-digital transmission module are fused, the iterative learning controller establishes an iterative learning model of output intensity parameters, the linear controller establishes a linear model of output phase parameters, and the electric stimulation control module self-adaptively adjusts the output phase and intensity of the multi-channel electric stimulator through the change of the kinematic signals and the dynamic signals in gait, so that the walking capacity of a patient is improved.

Description

An Adaptive Electrical Stimulation Training System

technical field

The invention relates to the technical field of medical rehabilitation, in particular to an adaptive electrical stimulation training system.

Background technique

Due to the long-term loss of lower limb function in patients with hemiplegia, atrophy of multiple muscles of one limb, loss of muscle strength, muscle spasticity and spasticity, the inability of the knee joint to complete flexion and extension, foot drop gait and stability of body balance function Therefore, the rehabilitation of lower extremity motor function has become a hot spot in the clinical rehabilitation of stroke patients.

In the 1960s, functional electrical stimulation therapy equipment began to be used in the clinical rehabilitation of stroke patients. With the development in recent decades, on the basis of the original single-channel control, the electric stimulation therapeutic apparatus has developed a multi-channel electric stimulation therapeutic apparatus. Open-loop control of switch control and sensor, and gradually develop from simple open-loop control to closed-loop control of various control methods.

The multi-channel electrical stimulation therapy device conducts electrical stimulation training on multiple muscles of stroke patients. On the one hand, it can help patients to move multiple muscles together, give patients the balance of body weight support transfer and the stability of the load phase during walking. On the other hand, due to the active participation of patients, their self-confidence can be greatly enhanced, which is more conducive to the functional recovery of the affected limbs. In 1971, Kralj et al. improved the single-channel electrical stimulator for the first time and designed a four-channel functional electrical stimulator. On the other hand, compared with the electrical stimulation open-loop control system, the closed-loop control method can not only control the output parameters of the electrical stimulator more accurately, but also adjust the patient's gait parameters in real time according to the preset trajectory, so that the patient's gait The attitude is more in line with the needs of healthy people. In 2000, Mourselas et al. specially designed a closed-loop control system for electrical stimulators for patients with foot drop. It uses the embedded closed-loop control principle to measure the ankle joint angle information during walking in real time, and combines the real-time measurement data with standard data. The feedback information obtained by the comparison adjusts the intensity of the electrical stimulator, and realizes the electrical stimulation adjustment of the PID control. In 2008, based on the iterative learning control algorithm, Nahrstaedt et al. applied the preset fixed stimulus intensity to the system in one gait cycle; before the next gait cycle started, the error of the previous cycle was analyzed; according to the error signal, the The stimulation parameters are corrected to realize the tracking of the preset joint angles during the swing phase. The functional electrical stimulators mentioned above realize the adjustment of electrical stimulation parameters and the adjustment of joint angles through different control methods, but they do not combine the phase of electrical stimulation with intensity adjustment, and because patients with different degrees of hemiplegia There are different walking speeds and gait cycles, so the existing electrical stimulation control methods do not have the adaptive adjustment function, and do not have wide applicability in clinical applications.

Contents of the invention

The adaptive electrical stimulation training system proposed by the present invention can automatically adjust the stimulation output of the multi-channel electrical stimulator according to the patient's own walking state, and help the patient to perform gait rehabilitation training.

Its technical scheme is as follows:

An adaptive electrical stimulation training system comprising:

The information acquisition module is used to acquire kinematic signals and dynamic signals of the patient's lower limb joints during the patient's gait walking training;

An analog-to-digital conversion module, configured to perform analog-to-digital conversion on the kinematics signal and the dynamics signal acquired by the information acquisition module, synchronize the kinematics signal and the dynamics signal, and convert the synchronized kinematics signal and the dynamics signal in real time The kinetic signal is transmitted to the electrical stimulation control module;

Electric stimulation control module, including iterative learning controller and linear controller;

The iterative learning controller is used to obtain the difference between the kinematics signal transmitted by the analog-to-digital conversion module and the target kinematics signal, fuse the dynamics signal transmitted by the analog-to-digital conversion module, and use iterative learning rules to establish the An iterative learning model between the difference and the output intensity parameter output by the iterative learning controller, when the patient’s motion state changes, the changed difference is obtained, and according to the iterative learning model according to the changed Value adjustment of the output intensity parameter output by the iterative learning controller;

The linear controller is used to fuse the kinematics signal and dynamics signal transmitted by the analog-to-digital conversion module, and establish the kinematics signal and dynamics signal transmitted by the analog-to-digital conversion module with the output time of the linear controller A linear model between phase parameters; when the motion state of the patient changes, the change value of the kinematic signal and the dynamic signal transmitted by the analog-to-digital conversion module is obtained, and the linear model is adjusted according to the change value according to the linear model The output phase parameters of the controller;

The electrical stimulation control module is also used to control the multi-channel electrical stimulator according to the output intensity parameters of the iterative learning controller and the output phase parameters of the linear controller;

The multi-channel electrical stimulator is used to control the start and end time of each channel and generate electrical stimulation signals of different intensities according to the output intensity parameters and output phase parameters sent by the electrical stimulation control module.

Further, the analog-to-digital conversion module is specifically used to perform analog-to-digital conversion on the kinematics signal and the dynamics signal obtained by the information acquisition module, and unify the kinematics signals obtained by the information acquisition module through down-sampling or over-sampling methods. The sampling rate of the signal and the dynamics signal, and according to the set special moment, from this moment, the different kinematics signals and dynamics signals after the unified sampling rate are aligned, so as to obtain the synchronized kinematics signal and dynamics signal, The synchronized kinematic and kinetic signals are transmitted to the electrical stimulation control module in real time.

Further, the analog-to-digital conversion module transmits the synchronized kinematics signal and dynamics signal to the electrical stimulation control module in real time, specifically;

The synchronous kinematics signal and dynamics signal are transmitted to the electrical stimulation control module in real time through the serial port communication function of the USB.

Further, the information acquisition module includes a motion signal acquisition unit for acquiring kinematic signals of the patient's lower limb joints and a pressure signal acquisition unit for acquiring dynamic signals of the patient's lower limb joints,

The motion signal collection unit is specifically used to collect angle signals and motion displacement signals of each joint of the patient's lower limbs during motion; preferably, the motion signal collection unit is a motion capture system consisting of a high-speed infrared data collection camera,

The pressure signal acquisition unit is specifically used to acquire the three-dimensional reaction force generated by the patient during walking and the ground. Preferably, the pressure signal acquisition unit includes a pressure sensing device and a three-dimensional pressure sensor placed behind the patient's heel.

Further, the iterative learning controller is specifically configured to, according to the angle signal in the kinematics signal transmitted by the analog-to-digital conversion module, obtain the angle error of the k-th step gait time j angle signal relative to the target angle signal, An iterative learning model between the angle error and the output intensity parameter of the kth step gait moment j output by the iterative learning controller is established by using an iterative learning rule, and the kth step gait moment j is transmitted by the analog-to-digital conversion module Kinetic signal obtained;

The movement state of the patient changes, causing the angle error to change, the iterative learning controller acquires the changed angle error, and adjusts the output of the iterative learning controller according to the changed angle error according to the iterative learning model Output intensity parameter.

Further, the linear controller is specifically used to obtain different walking speeds according to the kinematic signals transmitted by the analog-to-digital conversion module, and obtain corresponding walking speeds at different walking speeds according to the dynamic signals transmitted by the analog-to-digital conversion module. At each stage of the gait cycle, the delay time and duration of the k-th step in the gait cycle are obtained by using the prior linear model established in the prior experiment that the delay time and duration change linearly with the pace.

Further, the electrical stimulation control module is also used to control the multi-channel electrical stimulator according to the output intensity parameters of the iterative learning controller and the output phase parameters of the linear controller, specifically:

Normalize the delay time and duration in the kth step gait cycle, the normalization process is: when the time reaches the delay time calculated by the linear controller, output a digital signal 1, when the time Output a digital signal 0 when the duration calculated by the linear controller is reached, control the high and low level output of the linear controller output phase parameters according to the normalized digital signal, and output the output of the iterative learning controller The intensity parameter and the output phase parameter output by the linear controller are transmitted to the multi-channel electrical stimulator.

Further, the multi-channel electrical stimulator is specifically used to output corresponding electrical stimulation pulse voltages with adjustable waveform frequency, different pulse widths and amplitudes according to the output intensity parameters sent by the electrical stimulation control module Or the current is transmitted to the muscles through the electrode sheets, thereby stimulating the muscles to produce different degrees of contraction; according to the output phase parameters sent by the electric stimulation control module, the switch of the multi-channel electric stimulator is driven to control the output of each channel. Pulse start and end time.

Further, the multi-channel electrical stimulator outputs electrical stimulation pulse voltages or currents with different pulse amplitudes according to the output intensity parameters sent by the electrical stimulation control module, specifically:

The multi-channel electrical stimulator generates electrical stimulation with different pulse amplitudes according to the output intensity parameters sent by the electrical stimulation control module. The electrical pulse voltage or current is a proportional linear process: first, according to the maximum electrical stimulation intensity of the patient in a resting state Set a calibrated output intensity parameter value, the output corresponding to the calibrated output intensity parameter value is the maximum electrical stimulation pulse amplitude, and generate a corresponding pulse amplitude according to the proportional relationship between the actual output intensity parameter and the calibrated output intensity parameter value Electrical stimulation pulses with different values, this conversion process is a proportional linear process.

In summary, the adaptive electrical stimulation training system provided by the embodiment of the present invention can bring the following beneficial effects:

(1) Compared with the previous electric stimulation phase with fixed parameters and the electric stimulation intensity with fixed parameters, the present invention studies the law of kinematics and dynamics signals changing with speed when the state of motion is different, and at the same time through kinematics and dynamics signals In the change of gait, the output phase and intensity of the multi-channel electric stimulator are adaptively adjusted, which is beneficial to enable the patient to restore the physiological function of gait more naturally.

(2) Compared with the single-channel electrical stimulator, the multi-channel electrical stimulation output realized by the electrical stimulation drive module in the present invention is more favorable for the recovery of the physiological functions of each muscle group, and can effectively improve the pathological conditions of the patients at each stage of gait, It is especially suitable for the recovery of walking aid function of stroke patients, for example: it can provide shock absorption when the patient's heel hits the ground and help the knee joint lift when the toe is off the ground; it can increase the distance from the lower limbs to the ground during the gait swing period, thereby increasing the patient's Gait stability; it can improve the symmetry of various kinematic parameters and complete the extension and flexion of each joint of the lower limbs, so as to more comprehensively help patients recover their gait function.

Description of drawings

Fig. 1 is a schematic structural diagram of an adaptive electrical stimulation training system provided by an embodiment of the present invention;

Fig. 2 is a schematic diagram of the adaptive electrical stimulation process of the adaptive electrical stimulation training system;

Figure 3 is a schematic diagram of an iterative learning controller and a linear controller;

Fig. 4 is a schematic diagram of the relationship between the output parameters of the electrical stimulation control module and the electrical stimulation pulses output by the multi-channel electrical stimulator.

Detailed ways

The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

An embodiment of the present invention provides an adaptive electrical stimulation training system, as shown in FIG. comprising an iterative learning controller 1031 and a linear controller 1032;

Referring to Figure 2, the adaptive electrical stimulation process of the adaptive electrical stimulation training system shown in Figure 1 is as follows:

201. The information acquisition module 101 acquires the kinematic signals and dynamic signals of the lower limb joints of the patient during the gait walking training process of the patient;

The information acquisition module 101 includes a motion signal acquisition unit 1011 and a pressure signal acquisition unit 1012 .

(1) The motion signal collection unit 1011 collects the steps of the kinematic signals of the patient's lower limb joints in detail as follows:

The motion signal acquisition unit 1011 is specifically a motion capture system, which is composed of a high-speed infrared data acquisition camera. The motion signal acquisition unit 1011 may also be an inertial sensor or other equipment.

In this embodiment, the kinematic signals of the patient's lower limb joints collected by the motion signal acquisition unit 1011 are the angle signals and motion displacement signals of the joints of the patient's lower limbs during the movement process, and the angle signals include ankle joints, knee joint angles and corresponding angular velocities, Angular acceleration and other data, motion displacement signal includes data such as step length and gait symmetry.

(2) The steps for the pressure signal acquisition unit 1012 to acquire the dynamic signals of the patient's lower limb joints are as follows:

The pressure signal acquisition unit 1012 specifically includes a pressure sensing device placed behind the patient's heel and a three-dimensional pressure sensor, wherein the pressure sensing device placed behind the heel can be a plantar pressure switch, and the three-dimensional pressure sensor can be a three-dimensional force platform or A three-dimensional pressure sensor placed under the treadmill.

In this embodiment, the dynamic signals of the patient's lower limb joints collected by the pressure signal collection unit 1012 are three-dimensional reaction forces generated by the patient and the ground during walking. The judgment of a specific moment in the gait cycle can be judged by the pressure change of the pressure sensing device placed behind the heel. Increase; the three-dimensional pressure sensor can obtain the three-dimensional reaction force of the patient in the process of walking and the ground in real time through the characteristics that the force in the three-dimensional direction of the gait changes during the process of walking.

202. The analog-to-digital conversion module 102 performs analog-to-digital conversion on the kinematics signal and the dynamics signal acquired by the information acquisition module 101, synchronizes the kinematics signal and the dynamics signal, and transmits the synchronized kinematics signal and the dynamics signal to the Electrical stimulation control module 103;

Since different signal acquisition methods will have different sampling rates, the analog-to-digital conversion module 102 unifies the sampling rates of the kinematics signals and dynamics signals acquired by the information acquisition module 101 through down-sampling or over-sampling methods, and according to a special moment, For example, based on a complete gait cycle for analysis, set the starting moment of a complete gait cycle as the moment of heel strike. From this moment, the different kinematic signals and dynamic signals after the unified sampling rate are aligned. Thus, synchronized kinematics signals and dynamics signals are obtained, and then the synchronized kinematics signals and dynamics signals are transmitted to the electrical stimulation control module 103 in real time. In this specific embodiment, the sampling rate of the high-speed infrared data acquisition camera is 100 Hz, the sampling rate of the plantar pressure switch is 100 Hz, and the sampling rate of the three-dimensional pressure sensor is 1000 Hz. The sampling rate of the learning signal is uniform.

Specifically, the kinematics signal and the dynamics signal are transmitted to the electrical stimulation control module 103 through the serial port communication function of the USB, so that the synchronized kinematics signal and the dynamics signal are transmitted in real time.

The electrical stimulation control module 103 includes an iterative learning controller 1031 and a linear controller 1032 .

203. The iterative learning controller 1031 obtains the difference between the kinematics signal transmitted by the analog-to-digital conversion module 102 and the target kinematics signal, fuses the dynamics signal transmitted by the analog-to-digital conversion module 102, and uses an iterative learning rule to establish the difference between the difference and the target kinematics signal. An iterative learning model between the output intensity parameters U _out1 output by the iterative learning controller 1031, when the patient’s motion state changes, the difference is obtained, and the iterative learning control is adjusted according to the difference according to the iterative learning model The output intensity parameter U _out1 output by the device 1031.

Referring to Figure 3, the process of establishing an iterative learning model is as follows:

The iterative learning rule is shown in Formula 1:

U _k (n)=U _k-1 (n)+(f _p +f _i ∑δn+f _d Δ)e _k (n) (Formula 1)

The input value e _k (n) is an n-dimensional vector e=[e(1), e(2),...,e(n)] ^T ∈ R ⁿ in the kth vector, which can be referred to as modulus conversion The kinematic signal transmitted by the module 102 is relative to the change value of the target kinematic signal, and the output values U _k-1 (n) and U _k (n) are respectively an n-dimensional vector U=[U(1), U(2) ,...,U(n)] The k-1th and kth vectors in ^T ∈ R ⁿ can be referred to as the output intensity parameter U _out1 output by the iterative learning controller 1031, and f _p , f _i and f _d are respectively Learn factor matrices for proportional, integral, and difference learning.

As mentioned above, in this embodiment, the kinematics signal is specifically the angle signal and motion displacement signal of each joint of the patient’s lower limbs during the movement process, and in this embodiment, the angle signal is the maximum value of the patient’s foot during the swing period. Ankle dorsiflexion, the swing phase refers to the entire period in which the foot is off the ground.

(1) The iterative learning controller 1031 has acquired the target angle signal in advance, and the target angle signal is the normalized result of the angle data obtained by the experiment of a normal person. The analog-to-digital conversion module 102 inputs the kinematics signal to the iterative learning controller 1031, according to For the angle signal in the kinematics signal transmitted by the analog-to-digital conversion module 102, the iterative learning controller 1031 obtains the angle error of the angle signal relative to the target angle signal, and the angle error is shown in formula 2:

e _k (j) = θ _k (j) - θ _s (j) (Formula 2)

Wherein θ _k (j) is the angle signal of the kth step gait moment j transmitted by the analog-to-digital conversion module 102, θ _s (j) is the target angle signal, and in the present embodiment the target angle signal is 5 °, e _k ( j) is the angle error between the angle signal of the kth step gait moment j and the target angle signal; the kth step gait moment j is obtained by the dynamics signal transmitted by the analog-to-digital conversion module 102, for example, through the analog-to-digital conversion module The dynamic signal transmitted in step 102 is used to calculate the stage moment of the gait cycle, such as the moment when the heel is off the ground. Specifically, as described in step 101, the pressure signal acquisition unit 1012 is used to acquire the three-dimensional reaction force generated by the patient and the ground during walking. The judgment of a specific moment in the gait cycle can be judged by the pressure change of the pressure sensing device placed behind the heel.

(2) Multiply the angle error e _k (j) by the learning parameter L(j) to obtain the input parameter E _k (j), and the learning parameter L(j) can be obtained according to the angle error obtained by the normal person experiment and the actual output intensity during the experiment The ratio between the parameters U _out1 is calculated, as shown in formula 3:

E _k (j) = L(j)e _k (j) (Formula 3)

Wherein L(j) is set to 40 in this specific embodiment.

(3) Linearly calculate the input parameter E _k (j) and the actual output U _out1 of the k-1th step gait time j, and constrain the function T so that the output parameter H(j) is always in the normal electrical stimulation Within the range, the iterative learning model is obtained as shown in formula 4:

U _out1 ＝H _k (j)＝T(H _k-1 (j)+E _k (j)) (Formula 4)

Wherein H _k (j) represents the kth step gait moment j output intensity parameter U _out1 ; H _k-1 (j) represents the k-1th step gait moment j output intensity parameter U _out1 ; T is to make the output parameter H( j) A constraint function that is always within the normal range, the principle of the constraint function is shown in formula 5:

为患者所能承受的最大电刺激强度，约束函数T保证输出参数H(j)绝对不会超过患者所能承受的最大电刺激强度，以保证绝对安全；其中u为最小输出电刺激强度，因为输出电刺激强度不能为负，所以当输出强度参数U_out1计算出为负时，约束函数T使其为0，以避免输出错误的发生。in

is the maximum electrical stimulation intensity that the patient can bear, and the constraint function T ensures that the output parameter H(j) will never exceed the maximum electrical stimulation intensity that the patient can bear to ensure absolute safety; where u is the minimum output electrical stimulation intensity, because The output electrical stimulation intensity cannot be negative, so when the output intensity parameter U _out1 is calculated to be negative, the constraint function T makes it 0 to avoid output errors.

The patient's motion state changes, and the angle error between each joint angle signal and the target angle signal of the patient in different stages of the gait cycle is different, so the angle error e _k (j) changes, and the iterative learning controller 1031 acquires the changed angle Error e _k (j), adjust the output intensity parameter U _out1 output by the iterative learning controller 1031 according to the changing angle error e _k (j) according to the iterative learning model.

When the angle signal is smaller than the target angle signal, obtain the changed angle error e _k (j), use the iterative learning model to obtain the output intensity parameter U _out1 , and the output intensity parameter U _out1 will be larger than the output intensity parameter U _out1 output last time , so as to increase the intensity of electrical stimulation to ensure that the actual kinematics situation is closer to the standard situation; and when the angle signal is greater than the target angle signal, obtain the changed angle error e _k (j), and use the iterative learning model to obtain the output intensity parameter U _out1 , and The obtained output intensity parameter U _out1 will be smaller than the output intensity parameter U _out1 output last time, thereby reducing the intensity of electrical stimulation to ensure normal output in actual kinematic conditions.

204. While executing step 203, the linear controller 1032 fuses the kinematics signal and dynamics signal input by the analog-to-digital conversion module 102 to establish the kinematics signal and dynamics signal input by the analog-to-digital conversion module 102 and the linear controller 1032 Output a linear model between phase parameters; when the patient's motion state changes, obtain the change value of the kinematics signal and the dynamics signal input by the analog-to-digital conversion module 102, and adjust the output of the linear controller 1032 according to the change value according to the linear model Phase parameters.

(1) The process of building a linear model is as follows:

In the prior experiment on normal people, the EMG signals of each muscle group of the patient's lower limbs in multiple gait cycles at different walking speeds were collected through the surface electrodes attached to the corresponding muscle groups. In this embodiment, the EMG signals of four muscles of the lower limbs, the quadriceps, the hamstrings, the gastrocnemius, and the tibialis anterior, are collected.

In the prior experiment, the time point of myoelectric signal change was recorded by the collected myoelectric signal, and the heel-strike moment in the dynamic signal obtained by the plantar pressure switch was used as a reference point to calculate the time difference from heel-strike to muscle contraction and The time difference between the start of contraction and the stop of contraction is calculated, and the two time differences are unified in a complete gait cycle. In the same way, the time difference can also be calculated by taking the moment when the heel is off the ground as a reference point. According to the actual contraction time of each muscle group, through the combination of EMG signal collection and plantar pressure switch, it can be identified whether the reference point is at the moment of heel strike or the moment of heel off the ground. Among them, the time from the reference point to the start of muscle contraction is recorded as the delay time y ₁ , and the time from the start of muscle contraction to the time point of muscle relaxation is recorded as the duration y ₂ , the delay time y ₁ and the duration y ₂ are related to The gait speed has a linear relationship, so the least square fitting method is used to fit the relationship between y ₁ and y ₂ linearly changing with the gait speed into a specific equation within a complete gait cycle, see formula 6.

Equation 6 is the prior linear model.

The linear controller 1032 obtains different walking speeds from the kinematics signals transmitted by the analog-to-digital conversion module 102, and obtains the corresponding gait cycle stages at different walking speeds according to the dynamics signals transmitted by the analog-to-digital conversion module 102, and according to the acquired different walking speeds and the corresponding gait cycle stages at different walking speeds, and obtain the delay time y ₁ and duration y ₂ in the gait cycle, so as to achieve the combination and transformation of dynamic signals and kinematic signals are the two time variable parameters of delay time y ₁ and duration y ₂ .

Due to the individual differences of patients, each person's pace is different, so the delay time y ₁ and the duration y ₂ can be adaptively adjusted according to the difference in pace.

In the actual adjustment process, y ₁ and y ₂ in the k-th step gait cycle are calculated by calculating the pace. The method is as follows: as mentioned above, the longitudinal walking distance d(k-1) in the gait cycle is obtained by the motion signal acquisition unit 1011, and d(k-1) is included in the kinematics signal transmitted by the analog-to-digital conversion module 102 In the motion displacement signal, the k-1th step speed v(k-1) is obtained by formula 7, and then the k-th step speed uv(k) is obtained by averaging the previous N step speeds, see formula 8, where N is the set average number of steps.

According to the k-th step velocity uv(k), based on the prior linear model (Formula 6), the delay time y ₁ and duration y ₂ in the k-th gait cycle are calculated. As shown in Figure 3.

205. The electrical stimulation control module 103 also controls the multi-channel electrical stimulator 104 according to the output intensity parameter U _out1 of the iterative learning controller 1031 and the output phase parameter of the linear controller 1032, which includes extending the k-th step gait cycle Time length y ₁ and duration y ₂ are normalized, the method is that when the time reaches the delay time y ₁ calculated by the linear controller 1032, the digital signal 1 is output through the electrical stimulation control module 103, and the digital signal is output when the duration y ₂ is reached The signal 0 controls the linear controller 1032 to output the high and low levels of the phase parameter U _out2 according to the normalized digital signal.

The electrical stimulation control module 103 sends the output intensity parameter U _out1 and the output phase parameter U _out2 to the multi-channel electrical stimulator 104 .

206. The multi-channel electrical stimulator 104 controls the start and end times of each channel and generates electrical stimulation signals of different intensities according to the output intensity parameter U _out1 and the output phase parameter U _out2 sent by the electrical stimulation control module 103, to assist the patient in completing rehabilitation exercises .

Referring to Figure 4, the details are as follows:

(1) The multi-channel electrical stimulator 104 controls the start and end time of the output electrical stimulation pulses of each channel according to the output phase parameter U _out2 sent by the electrical stimulation control module 103 .

The multi-channel electrical stimulator 104 will output the phase parameter U _out2 as one of the input signals. When U _out2 is a low-level output, the multi-channel electrical stimulator 104 has no electrical stimulation pulse output; when U _out2 is a high-level output In flat output mode, the multi-channel electrical stimulator 104 has electrical stimulation pulse output at this time, and the parameters of the output electrical stimulation pulse are specifically determined by the output intensity parameter U _out1 .

As mentioned above, when the output phase parameter U _out2 changes from nothing to time, that is, at the end of the delay period _y1 , the multi-channel electrical stimulator 104 starts electrical stimulation. When the output phase parameter U _out2 changes from existence to non-existence, that is After the duration reaches the duration _y2 , the multi-channel electrical stimulator 104 ends the electrical stimulation.

(2) The multi-channel electrical stimulator 104 controls the output intensity of electrical stimulation pulses according to the output intensity parameter U _out1 sent by the electrical stimulation control module 103 .

The multi-channel electrical stimulator 104 takes the output intensity parameter U _out1 as one of the input signals, and generates electrical stimulation pulse voltages or currents with different intensities according to the output intensity parameter U _out1 , and the output intensity parameter U _out1 can determine the pulse of the output electrical stimulation electrical pulse Amplitude or pulse width, or adjust pulse amplitude and pulse width at the same time, the waveform and frequency of electric stimulation electric pulse can be set in advance. In this embodiment, the output current of each channel is adjustable from 0 to 120 mA, the wave width is adjustable from 100 to 420 μS, and the frequency is adjustable from 1 to 120 Hz, and each channel of the multi-channel electrical stimulator 104 outputs independently, mutually does not affect. The waveform, frequency and pulse width of the electrical stimulation pulses have been set in advance, and the electrical stimulation pulses with different pulse amplitudes are generated according to the output intensity parameter U _out1 .

Specifically, generating electrical stimulation pulses with different pulse amplitudes according to the output intensity parameter U _out1 is a proportional linear process: first, a calibration output intensity parameter value is set according to the patient’s maximum electrical stimulation intensity in a resting state, and the calibration output intensity parameter The output corresponding to the value is the maximum electrical stimulation pulse amplitude. According to the proportional relationship between the actual output intensity parameter U _out1 and the calibration output intensity parameter value, corresponding electrical stimulation electrical pulses with different pulse amplitudes are generated. This conversion process is proportional linear process.

The generated electrical stimulation pulse voltage or current is transmitted to the muscle through the electrode sheet, thereby stimulating the muscle to produce different degrees of contraction.

The embodiment of the present invention can adaptively adjust the time and intensity of electrical stimulation according to the actual contraction and exertion of the patient's muscles by analyzing the characteristics of each signal changing with the speed when the patient is exercising on the treadmill based on the adaptive electrical stimulation training system , has a very good bionic function, can improve the quality of lower limb movement of patients, and help them recover their daily gait function.

The above description is a preferred embodiment of the present invention, and it should be pointed out that for those skilled in the art, without departing from the principle of the present invention, some improvements and modifications can also be made, and these improvements and modifications are also considered Be the protection scope of the present invention.

Claims (4)

1. An adaptive electrical stimulation training system, comprising:

the information acquisition module is used for acquiring kinematic signals and dynamic signals of joints of lower limbs of the patient in the gait walking training process of the patient; the information acquisition module comprises a motion signal acquisition unit for acquiring the motion signals of the joints of the lower limbs of the patient and a pressure signal acquisition unit for acquiring the motion signals of the joints of the lower limbs of the patient; the motion signal acquisition unit is particularly used for acquiring angle signals and motion displacement signals of all joints of the lower limb of the patient in the motion process; the pressure signal acquisition unit is particularly used for acquiring three-dimensional reaction force with the ground, which is generated in the walking process of a patient;

the analog-to-digital conversion module is used for carrying out analog-to-digital conversion on the kinematic signals and the dynamic signals acquired by the information acquisition module, unifying the sampling rates of the kinematic signals and the dynamic signals acquired by the information acquisition module through a down-sampling or over-sampling method, and aligning different kinematic signals and dynamic signals after unifying the sampling rates from the moment according to the set special moment so as to acquire synchronous kinematic signals and dynamic signals, and transmitting the synchronous kinematic signals and dynamic signals to the electric stimulation control module in real time through the serial port communication function of the USB;

the electric stimulation control module comprises an iterative learning controller and a linear controller;

the iterative learning controller is used for acquiring a first angle signal according to the angle signal in the kinematic signals transmitted by the analog-to-digital conversion modulekStep by step timejThe angle error of the angle signal relative to the target angle signal is established by utilizing an iterative learning rule, and the angle error and the first angle error output by the iterative learning controller are establishedkStep by step timejOutputting an iterative learning model between intensity parameters, the firstkStep by step timejThe dynamic signals transmitted by the analog-to-digital conversion module are obtained;

the motion state of the patient is changed, the angle error is caused to change, the iterative learning controller obtains the changed angle error, and the output intensity parameter output by the iterative learning controller is adjusted according to the changed angle error by the iterative learning model;

the linear controller is used for acquiring the longitudinal walking distance in the gait cycle through the motion signal acquisition unitd(k- 1)，d(k-1)The motion displacement signal included in the kinematic signal transmitted by the analog-to-digital conversion module is represented by the formula

Obtain the firstk-1Step speedv(k-1)By then passing the frontNStep-by-step averaging to obtain the firstkStep speeduv(k)WhereinNThe average step number is set; according to the firstkStep speeduv(k)By using the time delay time length and duration established in the prior experimentAcquiring a priori linear model of the linear change of the time length along with the pace speed to obtain the firstkTime delay duration and duration in the step-by-step period;

the electric stimulation control module is to be the firstkNormalizing the time delay duration and the duration in the step-by-step period, wherein the normalization process comprises the following steps of: when the time reaches the time delay duration calculated by the linear controller, outputting a digital signal 1, when the time reaches the time duration calculated by the linear controller, outputting a digital signal 0, controlling the high-low level output of the phase parameter output by the linear controller according to the normalized digital signal, and transmitting the output intensity parameter output by the iterative learning controller and the phase parameter output by the linear controller to a multi-channel electric stimulator;

the multi-channel electric stimulator is used for controlling the starting time and the ending time of each channel and generating electric stimulation signals with different intensities according to the output intensity parameter and the output time phase parameter sent by the electric stimulation control module.

2. The adaptive electro-stimulation training system of claim 1, wherein the multi-channel electro-stimulator is specifically configured to output electro-stimulation electrical pulse voltages or currents with adjustable corresponding waveform frequencies and different pulse widths and amplitudes according to output intensity parameters sent by the electro-stimulation control module, and the electro-stimulation electrical pulse voltages or currents are transmitted to muscles through electrode plates, so that the muscles are stimulated to contract to different extents; and driving a switch of the multi-channel electric stimulator according to the output phase parameter sent by the electric stimulation control module so as to control the starting time and the ending time of each channel output electric stimulation pulse.

3. The adaptive electro-stimulation training system of claim 2, wherein the multi-channel electro-stimulator outputs electro-stimulation electrical pulse voltages or currents of different pulse amplitudes according to the output intensity parameters sent by the electro-stimulation control module, specifically:

the multichannel electric stimulator generates electric stimulation electric pulse voltage or electric current with different pulse amplitudes according to the output intensity parameter sent by the electric stimulation control module, wherein the electric stimulation electric pulse voltage or electric current is in a direct proportion linear process: firstly, setting a calibration output intensity parameter value according to the maximum electric stimulation intensity under the rest state of a patient, wherein the output corresponding to the calibration output intensity parameter value is the maximum electric stimulation electric pulse amplitude, and generating corresponding electric stimulation electric pulses with different pulse amplitudes according to the proportional relation between the actual output intensity parameter and the calibration output intensity parameter value, and the conversion process is a direct-proportion linear process.

4. The adaptive electro-stimulation training system of claim 3 wherein the motion signal acquisition unit is a motion capture system comprised of a high-speed infrared data acquisition camera, and the pressure signal acquisition unit comprises a pressure sensing device and a three-dimensional pressure sensor placed behind the patient's heel.

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