CN111659005A - A foot drop rehabilitation device based on myoelectric signals - Google Patents

Abstract

The invention discloses a foot drop rehabilitation device based on myoelectric signals. The whole device includes three parts: acquisition module, control module and stimulation module. The function of the acquisition module is to collect the motion signal characteristics of the patient's lower limbs. The control module has two working modes: acquisition and stimulation. The two modes can only have one kind of work at the same time. Its function is to correct the required electrical stimulation feedback parameters according to the characteristics of the patient's lower extremity motion signal. The function of the electrical stimulation module is to receive the signal from the control module to perform electrical stimulation on the patient. The invention also discloses a personalized electrical stimulation technology based on the gait characteristics of the patient's lower limbs. The device of the present invention not only realizes the closed-loop feedback control of electrical stimulation, but also considers the coupling between the electrical stimulation pulse and the patient's gait, and matches the electrical stimulation type, action time and action electrode according to the pre-trained data set, thereby improving the wearer's comfort. Use comfort.

Description

A foot drop rehabilitation device based on myoelectric signals

technical field

The invention relates to an intelligent foot and ankle orthosis based on feature matching in human-computer interaction, belonging to the fields of sports medicine, rehabilitation medicine and biomedical engineering

Background technique

Stroke refers to the damage to the local brain tissue caused by the interruption of blood supply to the brain. According to the statistics of the World Health Organization, 5.78 million deaths were caused by stroke worldwide in 2016, and it has been the highest fatality rate in the world in the past 15 years. one of the diseases. Stroke can cause many abnormal nervous system functions, which brings a lot of inconvenience to the daily life of patients, among which foot drop is the most widespread. Foot drop can prevent patients from lifting their toes during the swing phase of walking, causing inconvenience to daily life and the risk of falls. Although foot drop is a common neurological manifestation in stroke patients, it is also present in other neurological disorders, including multiple sclerosis (MS), spinal cord injury (SCI), cerebral palsy and traumatic brain injury.

A large number of experimental data and clinical practice show that rehabilitation after stroke is the best method to restore the motor function of stroke patients and improve the quality of life of patients. Functional electrical stimulation can help muscles contract and compensate for nerve function. In 1961, the Liberson team reported the use of a portable functional electrical stimulation device to correct foot drop. Since then, many teams have developed electrical stimulation equipment, but most of the current equipment is too large and cannot be used flexibly anytime, anywhere. However, some existing portable devices have a single stimulation mode, which is not effective in rehabilitation treatment.

SUMMARY OF THE INVENTION

The purpose of the present invention is to solve the problems existing in the prior art, and to provide a portable foot drop rehabilitation device based on myoelectric signals, which has two working modes. Not only can the electrical stimulation parameters be changed according to the gait characteristics, but also the patient's own gait sample set can be accumulated to train a personalized classifier. The classifier can predict the patient's different synchrony through regression analysis, and then change the application delay of the stimulation pulse to predict the time of the next electrical stimulation. The invention improves the coupling between the patient and the rehabilitation device, optimizes the interface of human-computer interaction, and improves the efficiency of rehabilitation training.

The concrete technical scheme of the present invention is as follows:

A device for rehabilitating foot drop based on myoelectric signals, comprising an acquisition module, a control module and a stimulation module, wherein:

The acquisition module includes a first wireless transmission unit, an electromyography acquisition unit and an inertial sensing unit that are worn on the lower limb of the patient in use, and are used to collect the gait data of the lower limb of the patient and send it to the control module; the gait data Including the eigenvalues extracted from the electromyographic signals collected by the electromyography acquisition unit, and the eigenvalues extracted from the acceleration signals collected by the inertial sensing unit;

The control module includes a data processing unit, a data storage unit, a user interaction unit, and a second wireless transmission unit. The user interaction unit is used for a user to select a working mode, and the working mode includes an acquisition mode and a stimulus selected for operation. mode; the second wireless transmission unit is configured to form a communication connection with the first wireless transmission unit; in the acquisition mode, the second wireless transmission unit locally stores the gait data sent by the acquisition module in a time sequence in the In the data storage unit, the sample gait data pre-stored in the data storage unit is used as the template data; in the stimulation mode, after the second wireless transmission unit receives the real-time gait data sent by the acquisition module, it is combined with the sample gait data. The gait data at the same time in the gait cycle stored in the local template data are compared to obtain the revised electrical stimulation parameters, which are sent to the electrical stimulation module through the wireless transmission unit.

The electrical stimulation module includes a third wireless transmission unit, a controller and electrodes that are worn on the patient's lower limbs in a use state, the third wireless transmission unit and the second wireless transmission unit form a communication connection, and the controller communicates with the second wireless transmission unit. After receiving the electrical stimulation parameters sent by the second wireless transmission unit, the third wireless transmission unit correspondingly adjusts the output characteristics of the current pulses according to the parameters, and outputs stimulation pulses to the lower limbs of the patient.

Preferably, in the acquisition module, the electromyography acquisition unit includes an electrode array, a first microprocessor and a first wireless transmission chip, and the electrical signals collected in the electrode array are subjected to eigenvalue calculation in the first microprocessor, and then passed through the first microprocessor. The first wireless transmission chip sends the calculation result to the control module; the electrode array is preferably composed of positive and negative two collection electrodes and a reference electrode, which is attached to the skin surface of the lower extremity for collecting the EMG signal at the attachment position .

Preferably, in the acquisition module, the inertial sensing unit includes an inertial sensor, a second microprocessor and a second wireless transmission chip, and the acceleration electrical signal collected by the inertial sensor is eigenvalue calculated in the second microprocessor, and then passed through the second microprocessor. The second wireless transmission chip sends the calculation result to the control module.

Preferably, the control module is a wearable device worn on the wrist, wherein the user interaction unit is in the form of a touch screen with a mode selection function; the control module is preferably a smart bracelet.

Preferably, the feature value extracted from the EMG signal collected by the EMG acquisition unit is the EMG root mean square value, and its calculation formula is:

Among them, N represents the number of sampling points in the time window, and sign _i represents the signal amplitude of the ith sampling point;

The eigenvalue extracted from the acceleration signal collected by the inertial sensing unit is the acceleration modulus value, and its calculation formula is:

Among them, a _x , a _y and _az are the acceleration components of the x, y, and z axes, respectively.

Preferably, the electrodes in the collection module are provided with three groups, which are respectively placed on the tibialis anterior muscle, the medial head of the gastrocnemius muscle, and the soleus muscle.

Preferably, the electrical stimulation module includes a third wireless transmission chip, a memory, a third microprocessor, a waveform superposition circuit, a boost circuit and an output unit, and the third wireless transmission chip receives the electrical stimulation parameters sent by the control module Then, the corresponding bidirectional pulse is generated by the ADC of the third microprocessor, which is integrated by the waveform superposition circuit and sent to the booster circuit to reach the stimulation threshold, and finally the stimulation pulse is output by the electrode of the output unit; the memory is used for local storage. The stimulation parameters are used for electrical stimulation using locally stored stimulation parameters when the wireless receiving unit does not receive the signal from the control module.

Preferably, the electrodes in the output unit and the acquisition module are multiplexed or independently provided.

Preferably, a remote data management platform is also included, and the control module transmits the data it receives and sends to the remote data management platform through the data transmission module, and establishes a patient database for easy management by doctors.

Preferably, the electrical stimulation parameters include the target muscle and the frequency, pulse width and amplitude parameters of the electrical stimulation.

Preferably, the sample gait data in the data storage unit is the gait data collected when the lower limb gait of a normal person or patient is normal.

Preferably, the data processing unit is provided with a gait pattern classifier based on a BP neural network, and the classifier is trained by using the gait data of the patient's lower limbs collected by the acquisition module, and is used for gait classification of the patient. The gait pattern is classified; in the template data, the time series of all gait data are classified and stored according to the gait cycle;

In the stimulation mode, if the template data stores the gait data of the unaffected lower extremity collected by the patient in the collection mode, the second wireless transmission unit receives the real-time gait data of the lower extremity on the affected side sent by the collection module. , compare the EMG root mean square value with the EMG root mean square value at the same moment in the gait cycle of the unaffected lower limb gait data to obtain the revised electrical stimulation parameters, and send them through the wireless transmission unit Give the electrical stimulation module; if the template data does not store the unaffected lower limb gait data collected by the patient itself in the collection mode, but only the sample gait data is stored, the second wireless transmission unit receives the affected side sent by the collection module. After the real-time gait data of the lower limbs, the EMG root mean square value in it is compared with the EMG root mean square value at the same moment in the gait cycle in the sample gait data to obtain the revised electrical stimulation parameters, and then pass The wireless transmission unit sends to the electrical stimulation module.

Compared with the prior art, the technical effect of the present invention is as follows:

Compared with the prior art, the present invention integrates two functions of data collection and feedback treatment at the same time, and provides a carrier for establishing a database of foot drop patients in the future; the present invention adopts an intelligent wristband-type main control device, which is convenient for patients to operate, and The appearance is beautiful and generous, and the psychological burden of the patient is reduced; the present invention stores the gait data of the normal person, the gait data of the healthy side of the patient or the gait data of the patient when the patient is normal in the control module, which can not only reduce the delay of the whole system , improve the real-time performance, and at the same time use the patient's personal characteristic data to train the classifier, the treatment is more targeted, and the rehabilitation effect is greatly improved.

Description of drawings

Fig. 1 is the overall schematic diagram of the hardware system of the present invention;

2 is a schematic diagram of an electromyography collection unit of the present invention;

3 is a schematic diagram of a control module of the present invention;

4 is a schematic diagram of an electrical stimulation module of the present invention;

5 is a schematic diagram of an embodiment of the present invention;

6 is a schematic flow chart of the acquisition mode of the present invention;

7 is a schematic flow chart of the stimulation mode of the present invention;

Figure 8 is a schematic diagram of stimulation pulses.

Detailed ways

In order to facilitate the understanding of the technical solutions of the present invention, the practical examples of the present invention are described in detail below with reference to the accompanying drawings, and detailed embodiments and specific operation processes are given, but the embodiments do not limit the present invention.

The present invention provides a foot drop rehabilitation equipment based on myoelectric signals. FIG. 1 illustrates the overall hardware system of this embodiment, which mainly includes three parts: a collection module, a control module and a stimulation module. The system can provide two functions of sampling mode and stimulation mode, compare the eigenvalues of EMG and acceleration signals with the stored eigenvalues, and correct the output parameters of electrical stimulation. It can not only use the pre-stored characteristic parameters, but also use the collected EMG and acceleration parameters of the patient's unaffected leg or healthy lower extremity to achieve a better recovery effect, improve the compliance of electrical stimulation and reduce fatigue.

The specific structure and function of each module will be described in detail below.

The acquisition module in this embodiment includes a first wireless transmission unit, an electromyography acquisition unit, and an acceleration acquisition unit, which are used to acquire gait data of the patient's lower limbs and send them to the control module. The gait data includes the eigenvalues extracted from the electromyographic signals collected by the electromyography acquisition unit, and the eigenvalues extracted from the acceleration signals collected by the inertial sensing unit.

As shown in FIG. 2 , the EMG acquisition unit used in this embodiment is a multi-channel wireless surface EMG acquisition unit, which includes: a plurality of EMG electrode arrays, a signal modulation circuit, a first microprocessor, and a first wireless transmission chip . The EMG electrode array is attached to the corresponding muscles of the lower limbs for EMG signal acquisition. The electrode array is composed of positive and negative acquisition electrodes and a reference electrode, which are attached to the skin surface of the lower limbs for electrical signal acquisition. The signal collected by the electrode array is transmitted to the signal modulation module after pre-amplification processing. The signal modulation module filters the EMG signal, and after the post-stage amplification and analog-to-digital conversion processing, the signal characteristic value is calculated in the first microprocessor, and then It is sent to the control module through the first wireless transmission chip. Among them, the EMG electrode, the signal modulation circuit, the first microprocessor, and the first wireless transmission chip are physically connected in sequence, and the first wireless transmission chip and the control module transmit EMG data through Wi-Fi, which is finally carried out by the control module. Storage of characteristic parameters and output of electrical stimulation parameters.

Similarly, the inertial sensing unit used in this embodiment includes an inertial sensor, a second microprocessor, and a second wireless transmission chip. The inertial sensor can be placed at the ankle of the patient's affected leg to perform acceleration electrical signals on the lower limb during walking. collection. The acceleration electrical signal collected by the inertial sensor is used for eigenvalue calculation in the second microprocessor, and then the calculation result is sent to the control module through the second wireless transmission chip.

In the acquisition module, both the EMG signal and the acceleration signal need to select appropriate eigenvalues that can reflect the characteristics of gait. In this embodiment, the characteristic value extracted from the EMG signal is the EMG root mean square value, and its calculation formula is:

Among them, N represents the number of sampling points in the time window, and sign _i represents the signal amplitude of the ith sampling point;

The eigenvalue extracted from the acceleration signal is the acceleration modulus value, and its calculation formula is:

Among them, a _x , a _y and _az are the acceleration components of the x, y, and z axes, respectively.

In addition, in order to accurately acquire the EMG data of the patient and conduct electrical stimulation, the electrodes in the acquisition module can be provided with three groups, which are respectively placed at the positions of the tibialis anterior muscle, the medial head of the gastrocnemius muscle, and the soleus muscle.

As shown in FIG. 3 , the control module used in this embodiment includes: a data processing unit, a data storage unit, a user interaction unit, and a second wireless transmission unit. The user interaction unit is used for the user to select the working mode, and the working mode of the present invention includes the acquisition mode and the stimulation mode, which can be selected for operation, and only one can be selected at the same time. The second wireless transmission unit is configured to form a communication connection with the first wireless transmission unit in the acquisition module, and the signal characteristic value obtained in the acquisition module can be sent to the second wireless transmission unit through the first wireless transmission unit. The two working modes of the present invention have different running processes, as follows:

In the acquisition mode, the second wireless transmission unit locally stores the gait data sent by the acquisition module in the data storage unit, and the acquisition time with the data is required during storage, thereby forming a time sequence sequence. The sample gait data pre-stored in the data storage unit are collectively used as template data. The sample gait data in the data storage unit is the gait data collected when the gait of the lower limbs of a normal person or patient is normal, which is also stored in the form of time series.

In the stimulation mode, after receiving the real-time gait data sent by the acquisition module, the second wireless transmission unit compares it with the gait data at the same moment in the gait cycle stored in the local template data, and uses the eigenvalues of the healthy side. The difference between the envelope curve and the characteristic envelope curve of the affected side is mapped to the modified electrical stimulation parameters, and sent to the electrical stimulation module through the wireless transmission unit.

Since the gait data needs to be compared according to the gait cycle, a classifier needs to be set in the data processing unit to classify the data according to the gait cycle. In this embodiment, the classifier is a gait pattern classifier based on BP neural network, which classifies the gait pattern (the gait pattern includes 5 periods of early support, mid support, late support, early swing, and late swing). Three-layer BP neural network classifier (input layer, hidden layer and output layer), the input is EMG root mean square value, EMG absolute mean value and acceleration modulus value, and the output is gait recognition. The gait data of the patient's lower limbs collected by the acquisition module is classified according to the pattern, and 60% is the training sample set, 20% is the test sample set, and 20% is the identification sample set. The BP neural network is trained and the parameters are adjusted using the training set data and the test set data, and the recognition accuracy is tested using the recognition sample set, so that the model can be used to classify the gait pattern of the patient. In the aforementioned template data, the time series of all gait data are classified and stored according to the gait cycle, so as to facilitate subsequent calls and comparisons.

In the stimulation mode, if the template data stores the gait data of the unaffected lower extremity collected by the patient in the acquisition mode, after the second wireless transmission unit receives the real-time gait data of the affected lower extremity sent by the acquisition module, it will The root mean square value of EMG is compared with the root mean square value of EMG at the same moment in the gait cycle in the locally stored gait data of the unaffected lower limb to obtain the modified electrical stimulation parameters, which are sent to the electrical machine through the wireless transmission unit. Stimulation module; if the gait data of the unaffected lower extremity collected by the patient in the acquisition mode is not stored in the template data, but only the sample gait data is stored, the second wireless transmission unit receives the real-time gait of the lower extremity on the affected side sent by the acquisition module. After the gait data is obtained, the RMS value of EMG in it is compared with the RMS value of EMG at the same moment in the gait cycle in the locally stored sample gait data to obtain the revised electrical stimulation parameters, which are transmitted wirelessly. The unit is sent to the electrical stimulation module.

In a preferred implementation form, the parameter correction method is as follows: if the patient uses the acquisition module first and then the stimulation module, the gait data of the unaffected lower extremity collected by the patient in the acquisition mode is preferentially used for comparison. The RMS value N _RMS of the affected side obtained by the signal acquisition module is less than the RMS value H _RMS of the unaffected side at the same time in a cycle, and the output intensity of the electrical stimulation pulse is increased. The RMS value of the unaffected side at time, reducing the output intensity of the electrical stimulation pulse. When the patient uses the stimulation module directly, the sample gait data stored in the controller is used for comparison. The specific stimulation parameters are adjusted as follows:

Pulse frequency: f=f _N -α*(N _RMS -H _RMS ), where f is the pulse frequency adjustment value combined with the difference information of EMG eigenvalues, and f _N is the pulse frequency setting value (determined according to gait recognition) , α is the proportional coefficient, α>0.

Pulse amplitude: u=β*u _N *H _RMS /N _RMS , where u is the pulse amplitude adjustment, u _N is the pulse amplitude setting value (determined according to gait recognition), β is the proportional coefficient, 0<β <1.

The electrical stimulation module adopted in the present invention includes a third wireless transmission unit, a controller and electrodes which are worn on the lower limbs of the patient in use state. The third wireless transmission unit forms a communication connection with the second wireless transmission unit and is capable of receiving the second wireless transmission unit. delivered electrical stimulation parameters. The function of the electrical stimulation module is that after receiving the electrical stimulation parameters sent by the second wireless transmission unit, the controller adjusts the output characteristics of the current pulses according to the parameters, and outputs stimulation pulses to the lower limbs of the patient through electrodes to help the patient return to normal gait. . The electrical stimulation parameters include the target muscle and the frequency, pulse width and amplitude parameters of the electrical stimulation.

In this embodiment, the electrical stimulation module includes a third wireless transmission chip, a memory, a third microprocessor, a waveform superposition circuit, a booster circuit, and an output unit (ie, an electrical stimulation electrode), and the third wireless transmission chip receives the control module After the electrical stimulation parameters sent by the second wireless transmission chip in the device, the ADC of the third microprocessor generates corresponding bidirectional pulses, which are integrated by the waveform superposition circuit and then sent to the booster circuit to reach the stimulation threshold, and finally sent to the booster circuit by the output unit's ADC. The electrodes output stimulation pulses; the memory is used for locally storing stimulation parameters, so that when the wireless receiving unit does not receive a signal from the control module, the locally stored stimulation parameters are used for electrical stimulation.

The waveform superposition circuit of this embodiment adopts an adder circuit, which is composed of three operational amplifiers and several resistors, and realizes the function of superimposing two-channel signal waveforms. The boost circuit includes +35v boost and -35v boost. The +35v boost is composed of the MCP1650 boost controller circuit, using the classic dc-dcboost circuit, and the -35v boost is composed of the MAX749 chip and its affiliated circuits. The principle is the same as that of the positive voltage circuit. The electrical stimulation output unit uses a combination of a voltage-controlled current source and a Wilson current source, which can provide a stable output voltage and achieve the desired stimulation intensity.

The power supply of the stimulation module is provided by a battery, taking 6 AA batteries as an example. After 5V voltage regulation, it is output to the 3V voltage regulator input terminal, the -5V generation chip input terminal and the boost circuit input terminal. The dc-dc boost circuit of the boost circuit uses the MCP1650 and MAX749 chips to output a maximum +35v and a minimum -35v voltage. The 3V regulated output provides the working voltage of the third microprocessor. The third microprocessor adjusts the output waveform according to the parameters sent by the control module, and outputs a bidirectional square wave through the DAC. The waveform superposition circuit uses an operational amplifier to superimpose the waveform of the bidirectional waveform output by the single-chip microcomputer, and the +5V and -5V regulated outputs provide the power supply of the operational amplifier. The electrical stimulation output unit uses voltage-controlled constant current source circuit and Wilson constant current source circuit to provide adjustable +35V and -35V stimulation voltage.

It should be noted that the electrodes in the output unit and the acquisition module of the present invention can be multiplexed, or can be set independently, or can be used independently according to the part of the muscle to be stimulated.

For each wireless transmission unit in the present invention, the transmission form can be Bluetooth, WIFI, 5G, etc., which is not limited, as long as it can realize the function of data transmission.

As shown in FIG. 5 , a wearable form of the electromyographic signal-based foot drop rehabilitation device of the present invention is provided. The signal acquisition module is composed of an EMG acquisition unit attached to the calf and an acceleration acquisition unit tied to the ankle. The main body of the control module is a smart bracelet worn on the wrist, which includes a watch core and a watch strap, reducing the psychological burden of patients. . The watch core is the aforementioned control module with a touch screen. Its main function is to provide electrical stimulation parameters according to the characteristic values of EMG and acceleration signals, to select the working mode of the system (acquisition mode and electrical stimulation mode), and to display time. . The touch screen is fixed on a strap worn on the patient's wrist and can be used as a watch every day.

As shown in FIG. 6 , the present invention provides a flow chart of an acquisition mode. The method includes the following steps:

Step 1, place the electromyography acquisition unit on the calf of the patient's healthy leg, and place the acceleration acquisition unit on the ankle of the patient's healthy leg.

In step 2, the acquisition mode is selected by the interaction unit of the control module, and the acquisition of the electromyography signal and the acceleration signal is started.

Step 3: Calculate the corresponding eigenvalues from the collected signals. The eigenvalue of the EMG signal is the root mean square of EMG, and the eigenvalue of the acceleration signal is the acceleration modulus value.

Step 4, the control module receives the characteristic value transmitted from the acquisition module, and stores the characteristic value in the storage module.

Step 5. Repeat steps 1-4 until the patient or physician selection is complete.

As shown in Figure 7, the present invention provides a flow chart of an electrical stimulation mode, and the method includes the following steps:

Step 1, place the electromyography acquisition unit and the electrical stimulation module on the patient's affected calf, and place the acceleration acquisition unit on the patient's affected leg and ankle.

Step 2, select the electrical stimulation mode through the interaction unit of the control module, and start to collect the electromyographic signal and the acceleration signal.

Step 3: Calculate the corresponding eigenvalue of the collected signal, wherein the eigenvalue of the EMG signal is the root mean square of EMG, and the eigenvalue of the acceleration signal is the acceleration modulus value.

Step 4, the control module receives the characteristic value transmitted by the acquisition module, compares it with the data in the storage module, corrects the electrical stimulation parameters, and sends the electrical stimulation parameters to the electrical stimulation module.

Step 5, the electrical stimulation module adjusts the output pulse according to the electrical stimulation parameters sent by the control module, and outputs the electrical stimulation pulse.

Step 6, repeat steps 1-5 until the patient or physician selection ends.

As shown in FIG. 8 , in a preferred embodiment of the present invention, a bidirectional square wave electrical stimulation pulse mode formed in the electrical stimulation module is provided, which can eliminate the charge accumulated in the patient's legs and can significantly prevent fatigue. Taking Figure 8 as an example, a negative pulse is used for stimulation. The positive pulse provides a positive charge to eliminate the accumulated negative charge. The amplitude of the positive pulse is 1/4 of the negative pulse, and the pulse width is 4 times that of the negative pulse.

In addition, in the present invention, a remote data management platform can also be set up, and the control module can send data to the remote data management platform through bluetooth, WIFI and 5G, etc., and establish a patient database to facilitate the management of doctors.

The above-mentioned embodiment is only a preferred solution of the present invention, but it is not intended to limit the present invention. Various changes and modifications can also be made by those of ordinary skill in the relevant technical field without departing from the spirit and scope of the present invention. Therefore, all technical solutions obtained by means of equivalent replacement or equivalent transformation fall within the protection scope of the present invention.

Claims (10)

1. The utility model provides a drop foot rehabilitation device based on flesh electrical signal which characterized in that, includes collection module, control module and stimulation module, wherein:

the acquisition module comprises a first wireless transmission unit, a myoelectricity acquisition unit and an inertia sensing unit which are worn on the lower limb of the patient in a use state, and is used for acquiring gait data of the lower limb of the patient and sending the gait data to the control module; the gait data comprises a characteristic value extracted from an electromyographic signal collected by an electromyographic collecting unit and a characteristic value extracted from an acceleration signal collected by an inertial sensing unit;

the control module comprises a data processing unit, a data storage unit, a user interaction unit and a second wireless transmission unit, wherein the user interaction unit is used for a user to select a working mode, and the working mode comprises an acquisition mode and a stimulation mode which are selected to run; the second wireless transmission unit is used for forming communication connection with the first wireless transmission unit; in the acquisition mode, the second wireless transmission unit locally stores the gait data sent by the acquisition module in a time sequence form in the data storage unit, and the gait data and the sample gait data stored in the data storage unit in advance are used as template data together; in the stimulation mode, after receiving the real-time gait data sent by the acquisition module, the second wireless transmission unit compares the real-time gait data with the gait data stored in the local template data at the same moment in a gait cycle to obtain corrected electrical stimulation parameters, and sends the corrected electrical stimulation parameters to the electrical stimulation module through the wireless transmission unit.

The electric stimulation module comprises a third wireless transmission unit, a controller and an electrode, wherein the third wireless transmission unit, the controller and the electrode are worn on the lower limb of a patient in a use state, the third wireless transmission unit is in communication connection with the second wireless transmission unit, and after the controller receives electric stimulation parameters sent by the second wireless transmission unit through the third wireless transmission unit, the output characteristics of current pulses are correspondingly adjusted according to the parameters, and stimulation pulses are output to the lower limb of the patient.

2. The foot drop rehabilitation device based on the electromyographic signals according to claim 1, wherein in the collection module, the electromyographic collection unit comprises an electrode array, a first microprocessor and a first wireless transmission chip, the electrical signals collected in the electrode array are subjected to characteristic value calculation in the first microprocessor, and then the calculation results are sent to the control module through the first wireless transmission chip; the electrode array preferably comprises a positive collecting electrode, a negative collecting electrode and a reference electrode, and is attached to the surface of the skin of the lower limb and used for collecting the electromyographic signals of the attached position.

3. The foot drop rehabilitation device based on the electromyographic signals according to claim 1, wherein in the acquisition module, the inertial sensing unit comprises an inertial sensor, a second microprocessor and a second wireless transmission chip, the acceleration electric signal acquired by the inertial sensor is subjected to characteristic value calculation in the second microprocessor, and then the calculation result is sent to the control module through the second wireless transmission chip; preferably, the electrodes in the acquisition module are provided with three groups which are respectively arranged on tibialis anterior muscle, gastrocnemius medial head and soleus muscle.

4. The foot drop rehabilitation device based on electromyographic signals according to claim 1, wherein the control module is a wearable device worn on the wrist, and wherein the user interaction unit is in the form of a touch screen with a mode selection function; the control module is preferably a smart bracelet.

5. The foot drop rehabilitation device based on electromyographic signals according to claim 1, wherein the characteristic value extracted from the electromyographic signals collected by the electromyographic signal collecting unit is an electromyographic root mean square value, and the calculation formula is as follows:

wherein N represents the number of samples in the time window, sign_iSignal amplitude representing the ith sample point;

the characteristic value extracted from the acceleration signal collected by the inertial sensing unit is an acceleration module value, and the calculation formula is as follows:

wherein, a_x、a_yAnd a_zAcceleration components of the x, y, and z axes, respectively.

6. The foot drop rehabilitation device based on the electromyographic signals according to claim 1, wherein the electrical stimulation module comprises a third wireless transmission chip, a memory, a third microprocessor, a waveform superposition circuit, a voltage boost circuit and an output unit, wherein after the third wireless transmission chip receives the electrical stimulation parameters sent by the control module, a DAC (digital-to-analog converter) of the third microprocessor generates corresponding bidirectional pulses, the bidirectional pulses are integrated by the waveform superposition circuit and then sent to the voltage boost circuit to reach a stimulation threshold value, and finally, the electrodes of the output unit output stimulation pulses; the memory is used for locally storing stimulation parameters so as to perform electrical stimulation by using the locally stored stimulation parameters when the wireless receiving unit does not receive the signal of the control module;

the output unit and the electrodes in the acquisition module are multiplexed or are respectively and independently arranged.

7. The foot drop rehabilitation device based on electromyographic signals according to claim 1, further comprising a remote data management platform, wherein the control module transmits the data received and sent by the control module to the remote data management platform through the data transmission module, and establishes a database of the patient for the convenience of management of a doctor.

8. The drop foot rehabilitation device according to claim 1, wherein the electrical stimulation parameters include target acting muscles and parameters of frequency, pulse width and amplitude of electrical stimulation.

9. The apparatus according to claim 1, wherein the sample gait data in the data storage unit is gait data collected when the gait of the lower limb of the normal person or the patient is normal.

10. The device for recovering foot drop based on electromyographic signals according to claim 9, wherein a gait pattern classifier based on a BP neural network is arranged in the data processing unit, and the classifier is trained by using the gait data of the lower limb of the patient collected by the collecting module and is used for classifying the gait pattern of the patient; in the template data, all the time sequence sequences of the gait data are classified and stored according to gait cycles;

in the stimulation mode, if healthy-side lower limb gait data acquired by a patient in the acquisition mode is stored in the template data, the second wireless transmission unit compares the myoelectricity root mean square value with the myoelectricity root mean square value at the same time in a gait cycle in the healthy-side lower limb gait data after receiving the affected-side lower limb real-time gait data transmitted by the acquisition module to obtain a corrected electrical stimulation parameter, and transmits the corrected electrical stimulation parameter to the electrical stimulation module through the wireless transmission unit; if the gait data of the healthy lower limbs of the patient collected in the collection mode is not stored in the template data, and only the sample gait data is stored, the second wireless transmission unit compares the myoelectric root mean square value with the myoelectric root mean square value of the affected lower limbs at the same moment in the gait cycle in the sample gait data after receiving the real-time gait data of the affected lower limbs sent by the collection module to obtain the corrected electrical stimulation parameters, and sends the corrected electrical stimulation parameters to the electrical stimulation module through the wireless transmission unit.

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