Closed-loop noninvasive spinal cord electrical stimulation regulation and control method and system based on motion data

Abstract

The invention discloses a closed-loop noninvasive spinal cord electrical stimulation regulation and control method and system based on motion data, and the system is provided with a flexible electrode array patch which is attached to the skin surface of a to-be-tested human body; the sensing module is used for collecting electromyographic signals or acceleration signals of a user; the signals are processed, and characteristic values related to actions and motions are extracted; the closed-loop feedback module compares the characteristic value with a model set characteristic / threshold value, and judges whether to start stimulation site and stimulation parameter adjustment or not; automatically selecting an optimal electrode unit and a corresponding stimulation parameter based on a judgment result; the dynamic regulation and control module controls the optimal electrode unit to output stimulation current, and regulates the activity of corresponding spinal cord neurons; and continuously performing closed-loop adjustment on the electrode unit and the stimulation parameters according to the motion feedback data. According to the method and system, precise stimulation and closed-loop regulation and control based on the motion response of the patient are achieved, and the problems that stimulation target positioning depends on artificial experience, parameter adjustment is not timely, and individualized and closed-loop feedback capacity is lacked are solved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of neuromodulation and rehabilitation engineering, and more particularly relates to a closed-loop non-invasive spinal cord electrical stimulation regulation method and system based on motion data, which is suitable for non-invasive treatment and rehabilitation of patients with motor dysfunction, has good individualized adjustment capability and remote home adaptability, and is particularly suitable for post-stroke motor function rehabilitation, post-spinal cord injury motor function rehabilitation, and treatment of neuropathic pain in clinical and home scenarios. BACKGROUND

[0002] Spinal Cord Stimulation (SCS) technology is an important means in the field of neural function rehabilitation that has attracted much attention in recent years. Traditional spinal cord stimulation is mostly implantable devices, which have achieved certain results in clinical practice, but still have the following technical defects:

[0003] (1) High invasiveness: requires surgical implantation of electrodes and pulse generators, which has postoperative risks such as infection and rejection.

[0004] (2) High cost: high equipment manufacturing and surgical costs limit its application in a wide range of people.

[0005] In contrast, non-invasive electrical stimulation methods are more suitable for rehabilitation treatment, home rehabilitation, and preclinical trials for mild and moderate patients due to their high safety and portability. However, current non-invasive spinal cord stimulation usually applies continuous stimulation, which cannot apply stimulation at specific time points, making it impossible to specifically enhance the plasticity of neural circuits and limiting the treatment effect. On the other hand, non-invasive spinal cord stimulation relies on professional personnel to constantly adjust parameters, which is time-consuming and labor-intensive, making it difficult to apply at home. SUMMARY

[0006] To solve the problems of stimulation target positioning relying on artificial experience, parameter adjustment not being timely, lack of individualization and closed-loop feedback capability in the prior art, the present application provides a closed-loop non-invasive spinal cord electrical stimulation regulation method and system based on motion data.

[0007] The technical solutions adopted are as follows:

[0008] On the one hand, the present application provides a closed-loop non-invasive spinal cord electrical stimulation regulation method based on motion data, which comprises the following steps:

[0009] Step 1, configure a flexible electrode array patch composed of a plurality of independently controlled electrode units, and attach it to the skin surface of the person to be tested;

[0010] Step 2, collect the user's electromyographic signal or acceleration signal;

[0011] Step 3: Process the collected signals and extract feature values ​​related to actions and movements;

[0012] Step 4: Compare the feature values ​​with the features / thresholds set in the model to determine whether to activate the stimulation site and adjust the stimulation parameters.

[0013] Step 5: Automatically select the optimal electrode unit and corresponding stimulation parameters based on the judgment result;

[0014] Step 6: Control the output stimulation current of the optimal electrode unit to regulate the activity of spinal cord neurons;

[0015] Step 7: Repeat steps 2 to 6 to continuously optimize and adjust the electrode unit and stimulation parameters in a closed loop based on motion feedback data.

[0016] Preferably, in step 1, multiple flexible electrode units are arranged in a two-dimensional or three-dimensional matrix structure, and modulation or interference methods are used to implement corresponding stimulation parameters to optimize the therapeutic effect at different time points and different stimulation locations.

[0017] Preferably, the electromyographic signals in step 2 are acquired by surface electromyographic electrodes or accelerometers.

[0018] On the other hand, the present invention also provides a closed-loop non-invasive spinal cord electrical stimulation modulation system based on motion data, the system comprising:

[0019] A flexible electrode array patch comprising multiple flexible independent electrode units arranged in a two-dimensional or three-dimensional matrix structure;

[0020] The high-frequency stimulation module is provided with electrode channels corresponding to the multiple electrode units. Each electrode channel outputs a high-frequency modulated square wave / sine wave current from 1kHz to 20kHz. The high-frequency sine waves can be superimposed to form an interference frequency of 1Hz-150Hz.

[0021] The sensing module is used to collect the user's electromyography and acceleration signals in real time;

[0022] The closed-loop feedback module collects electromyographic and acceleration data from the sensing module in real time, extracts feature values ​​related to action and movement, compares the feature values ​​with the model-set features / thresholds, determines whether to initiate closed-loop control of stimulation site and stimulation parameter adjustment, and outputs parameter control instructions.

[0023] The dynamic control module is connected to the closed-loop feedback module and the high-frequency stimulation module, receives parameter control commands output by the closed-loop feedback module, and adjusts the frequency, output intensity, and electrode activation position of each channel in the high-frequency stimulation module in real time.

[0024] Furthermore, the sensing module includes:

[0025] Electromyography (EMG) sensors are surface electromyographic electrodes placed on the target muscle group.

[0026] Inertial sensors, which integrate 6-axis or 9-axis sensor modules, can detect three-axis acceleration, angular velocity and attitude changes of limb movements;

[0027] The data acquisition and preprocessing module is used to perform preprocessing on the acquired signals, including filtering, baseline drift correction, and preliminary feature extraction.

[0028] The communication module transmits data with the closed-loop feedback module and the dynamic control module, respectively.

[0029] Furthermore, the closed-loop feedback module includes:

[0030] A data buffer receives and temporarily stores the electromyographic data and acceleration motion data from the sensing module.

[0031] Signal processing and decoding are used for real-time online analysis and processing of electromyographic and acceleration data, and for decoding motion intent from acceleration data;

[0032] The comparator combines model-defined features / thresholds with electromyography and acceleration motion data responses to determine whether closed-loop regulation is needed to adjust the initiation stimulus, switch target points, or enhance output.

[0033] The controller generates a parameter adjustment instruction based on the comparator's determination result and transmits it to the dynamic control module to perform the parameter adjustment.

[0034] Furthermore, the controller is loaded with a muscle strength feedback strategy model, a tremor control feedback strategy model, and a pain relief feedback strategy model.

[0035] Furthermore, the dynamic control module includes a manual setting module and an adaptive control module. The manual setting module is used by professionals to preset parameters on the interface. The adaptive control module automatically adjusts the optimal stimulation scheme based on real-time collected motion feedback data using a preset algorithm.

[0036] Furthermore, the flexible electrode array patch, high-frequency stimulation module, sensing module, closed-loop feedback module, and dynamic control module are integrated into a portable device, and the outer shell of the portable device is made of antibacterial medical silicone.

[0037] The technical solution of the present invention has the following advantages:

[0038] A. The method system of the present invention, by configuring a multi-point flexible electrode array patch, a high-frequency stimulation module, a sensing module and a dynamic control module, decodes the collected electromyographic signals and acceleration signals and extracts relevant features to achieve continuous monitoring and analysis of the motion state. Based on the motion data, the stimulation position and intensity are automatically adjusted to achieve precise stimulation and closed-loop control based on the patient's motion response.

[0039] B. This invention combines a closed-loop feedback module with a dynamic control module to automate target localization and parameter optimization without relying on manual settings by professionals. The system can automatically determine the optimal stimulation position and frequency based on electromyography and acceleration data. Through real-time closed-loop feedback control based on real-time motion data, the treatment responsiveness is improved.

[0040] C. This invention can achieve multi-parameter stimulation of multiple target points and coordinated control of multiple electrode stimulation channels based on the various feedback strategy models provided by the closed-loop feedback module, thereby achieving deeper and more precise neuromodulation.

[0041] D. This invention integrates multiple modules to form an integrated wearable design, which is convenient for patients to use in their homes or daily environments for a long time, enhancing rehabilitation compliance and treatment effects. It is applicable to multiple application scenarios such as stroke rehabilitation, neurological function recovery after spinal cord injury, and neuropathic pain control. It has significant intelligent, portable, personalized, and precise technical features, and has broad prospects for clinical application and industrialization. Attached Figure Description

[0042] To more clearly illustrate the specific embodiments of the present invention, the accompanying drawings used in the specific embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0043] Figure 1 This is a block diagram of the control method provided by the present invention;

[0044] Figure 2 This is a diagram of the flexible electrode array patch structure provided by the present invention.

[0045] Figure 3 This is a system composition diagram provided by the present invention.

[0046] The meanings of the symbols shown in the image are as follows:

[0047] 1-Flexible electrode array patch; 2-Electrode unit. Detailed Implementation

[0048] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] like Figure 1 As shown, this invention provides a closed-loop non-invasive spinal cord electrical stimulation modulation method based on motion data, comprising the following steps:

[0050]

S01

[0051]

S02

[0052]

S03

[0053]

S04

[0054] Simultaneously monitor all muscles to which the electromyographic electrodes are attached, observe whether they produce movement, set an activation threshold for each muscle, and determine that the muscle activity is active movement after reaching the set threshold, and further stimulate it.

[0055]

S05

[0056] Based on a pre-set model, the model determines the spinal cord segments involved in the active muscles and the appropriate stimulation parameters, and then transmits the control information to the subsequent dynamic control module (central controller).

[0057]

S06

[0058] The electrode array is controlled to output a high-frequency modulated square wave current or a high-frequency sinusoidal current. The high-frequency sinusoidal current can create an interference frequency between multiple electrode units. The interference frequency is formed by superimposing high-frequency signals of different frequencies output by at least two electrode units, and is used to stimulate deep spinal cord nerve tissue.

[0059]

S07

S02

S06

[0060] like Figure 3 As shown, this invention also provides a closed-loop non-invasive spinal cord electrical stimulation modulation system based on motion data. The system includes: a flexible electrode array patch, a high-frequency stimulation module, a sensing module, a closed-loop feedback module, and a dynamic control module. This invention integrates a multi-point flexible electrode array patch, a high-frequency stimulation module, and a sensing module, combined with signal decoding and dynamic parameter optimization algorithms in the closed-loop feedback module, to achieve continuous monitoring and analysis of the motion state. Then, the dynamic control module automatically adjusts the stimulation position and intensity, achieving precise stimulation and closed-loop control based on the patient's motion response.

[0061] like Figure 2 As shown, the flexible electrode array patch includes multiple flexible independent electrode units arranged in a two-dimensional or three-dimensional matrix structure. With the help of modulation / interference technology, different electrode units can be superimposed to form a spatial interference electric field, thereby stimulating deep nerve tissue. The electrode array structure can support simultaneous activation of multiple points, constructing a multi-target synergistic regulation mechanism.

[0062] The electrode array patch is made of medical-grade flexible material, which has excellent skin adhesion and breathability; each electrode unit has independent signal output capability, and the controller in the closed-loop feedback module selectively activates different electrode units to achieve current output to specific body surface / spinal cord target points.

[0063] Meanwhile, the electrode array patch also has modular expansion capabilities. The array structure can be expanded or reduced in the number of electrodes according to different clinical needs, enhancing the versatility of the system.

[0064] Each independent electrode unit on the flexible electrode array patch has identification and positioning functions. Each electrode unit is equipped with a number and location information label, which is matched with the corresponding muscle. Combined with the corresponding spinal cord segment of each muscle, precise target selection can be achieved.

[0065] The high-frequency stimulation module is equipped with electrode channels corresponding to multiple electrode units. Each electrode channel outputs a high-frequency modulated square wave / sine wave current from 1kHz to 20kHz. The square wave modulated at 1Hz to 150Hz can influence deep spinal cord stimulation activity, and this frequency can be adjusted in real time. Sine wave output channels of different frequencies can generate interference frequencies from 1Hz to 150Hz in deep tissues. The interference frequency can be changed by the frequency difference between two sets of electrode units and can be adjusted in real time, enabling the simultaneous construction of multiple independent interference target points between multiple sets of electrode units, thus achieving multi-target stimulation.

[0066] The carrier frequency, modulation frequency, waveform type, and output intensity of the signal generated by the high-frequency stimulation module can be adjusted in real time. All parameters can be controlled by the dynamic control module to achieve dynamic and individualized stimulation. The dynamic control module supports rapid switching of different stimulation targets or simultaneous joint stimulation strategies for multiple regions.

[0067] The high-frequency stimulation module in this invention has an output current limiting protection function, which outputs only at the set maximum safe current. In case of abnormalities such as electrode detachment, poor contact, or sudden change in skin impedance, the system can automatically interrupt the output to ensure safe use.

[0068] The sensing module in this invention is responsible for real-time acquisition of patient motion state data, including electrical muscle activity (EMG) and body motion characteristics (acceleration, posture), providing key input signals for subsequent stimulation parameter determination and closed-loop control. The sensing module is suitable for wearable environments and includes the following components:

[0069] (1) Electromyography (EMG) sensor: It adopts high-sensitivity surface electromyography electrodes, which are placed on the target muscle group (such as wrist flexor, biceps brachii, and rectus femoris). It supports dual-channel or multi-channel parallel acquisition, with a sampling frequency of ≥200Hz. It is suitable for high-frequency muscle activity detection, and has noise suppression and drift correction mechanisms to adapt to different skin resistance changes.

[0070] (2) Inertial Measurement Unit (IMU): integrates a 6-axis or 9-axis sensor module (accelerometer + gyroscope + magnetometer); it can detect the three-axis acceleration, angular velocity and attitude changes of limb movement, with a sampling frequency of 100Hz, and is used to determine the start, direction and amplitude of movement in real time.

[0071] (3) Data acquisition and preprocessing module: On-chip analog-to-digital converter (ADC) + pre-filter amplification circuit is used to ensure signal quality; a local preprocessing module is provided at the sensing end, including filtering (bandpass filtering to remove power frequency interference), baseline drift correction, and preliminary feature extraction (such as RMS value, integral EMG, motion energy threshold, etc.).

[0072] (4) Communication module: Supports multiple communication methods, including wired: UART, SPI; wireless: Bluetooth 4.0 / 5.0, Wi-Fi, TCP / IP protocol stack; data transmission has a timestamp alignment mechanism to ensure synchronization with the system and form a stable closed loop.

[0073] The sensing module is wearable and easy to use. All sensors are either adhesive or wristband-style, offering good comfort and reusability. The sensor housing is made of medical-grade silicone, which is sweat-proof, antibacterial, and supports cleaning and disinfection. It can be used without interfering with the patient's daily activities and is suitable for home rehabilitation environments.

[0074] The collected electromyographic and acceleration signals are transmitted to the closed-loop feedback module, which will be used to determine the movement intention and force intensity, and to trigger or adjust the stimulation output. At the same time, the collected data participates in post-stimulation feedback analysis and automatic parameter optimization, and serves as physiological response data during the treatment process for efficacy evaluation.

[0075] The closed-loop feedback module provided by this invention is a key functional module for achieving autonomous adjustment of stimulation targets and parameters. Based on real-time acquired electromyographic and acceleration data, combined with signal analysis algorithms and control strategies, it constructs a "sensing-judgment-regulation" closed-loop circuit, improving the system's personalized response capability and therapeutic effect. Its components include:

[0076] (1) Data buffer: used to temporarily store real-time transmitted data, with time alignment and packet management capabilities to ensure stable and smooth system processing.

[0077] (2) Signal processing and decoder: used for real-time online analysis and processing of electromyography and acceleration motion data (such as RMS value, integral EMG, spectral energy distribution), and decoding of motion intent of acceleration data (such as initiation determination, action recognition);

[0078] (3) Comparator: Combine the model setting features / thresholds with electromyography and acceleration motion data responses to determine whether closed-loop regulation is needed to adjust the initiation stimulus, switch the target point, or enhance the output.

[0079] Thresholds include adaptive thresholds or static thresholds. Based on electromyography and acceleration motion data, stimulation parameters are automatically optimized to determine whether stimulation adjustment, target switching, or output enhancement is needed, thereby achieving closed-loop control.

[0080] (4) Controller: Generates parameter adjustment instructions based on the judgment results, and works with the dynamic parameter control module to achieve precise and automatic stimulation output correction; it can load different feedback strategy models (such as strengthening muscle strength, controlling tremor, relieving pain, etc.).

[0081] The closed-loop logic flow adopted is as follows:

[0082] a. Signal acquisition: Acquiring EMG and IMU data;

[0083] b. Real-time feature analysis: such as sudden changes in electromyography peak value, acceleration direction change, and judgment of movement initiation;

[0084] c. Threshold comparison or model determination: Adaptive threshold algorithm (dynamically changing over time) or fixed threshold + individual baseline correction method are used;

[0085] d. Output control commands: If a certain characteristic threshold is met (e.g., EMG peak increases by 30%), the system will automatically increase the stimulation frequency or intensity; if a specific action initiation signal is detected (e.g., acceleration fluctuation is greater than the set value), the system will activate a specific electrode target.

[0086] e. Stimulus feedback and result reassessment, then proceed to the next cycle.

[0087] The optimization strategy of the closed-loop feedback module is flexibly configurable and has learning and adaptive capabilities. Its contents include:

[0088] It supports multiple preset optimization goals, including but not limited to: enhancing muscle activation efficiency; improving the completion of a certain movement (such as grabbing or raising the leg); controlling overactivation or excessive muscle tone; and gradually increasing stimulation according to the user's rehabilitation progress.

[0089] Different optimized templates can be set for different diseases (such as stroke patients, spinal cord injury patients, Parkinson's patients, etc.).

[0090] Learning and adaptive capabilities: Individualized stimulus strategies can be gradually optimized based on long-term user data; cloud-based models can be connected for cross-individual data training and upgrades.

[0091] The dynamic control module equipped in this invention is used to adjust various key parameters (such as frequency, intensity, electrode position, etc.) in real time and in a personalized manner during nerve stimulation to adapt to changes in the patient's motor state and treatment response, forming a complete closed-loop control core function. The dynamic control module can adjust the frequency, output intensity, and electrode activation position of each electrode channel in real time during stimulation; at the same time, a digital control chip is embedded in the module to continuously adjust the stimulation parameters through a central controller.

[0092] The dynamic control module includes a manual setting module and an adaptive control module, supporting both manual setting and automatic optimization modes respectively.

[0093] Manual setting mode: Professionals can preset parameters through the configuration interface, such as modulation frequency, electrode activation point, stimulation intensity, etc., which is suitable for pre-trial debugging and control scenarios under doctor supervision.

[0094] Automatic optimization mode: Based on real-time collected motion feedback data (such as changes in electromyography peak value and acceleration pattern recognition), the system automatically adjusts the optimal stimulation scheme using a preset algorithm to achieve a fully automatic closed-loop adjustment process from "detection-analysis-optimization-output".

[0095] The parameter optimization objectives in the dynamic control module can be set based on preset strategies, including but not limited to: maximizing the enhancement of electromyographic response, optimizing the increase in the amplitude of movement after stimulation, and minimizing the pain score (for neuropathic pain).

[0096] The dynamic control module communicates with the sensing module and control module via SPI / I2C / UART or wireless BLE protocol; the dynamic control module can connect to an external control software interface via Bluetooth / USB to read and adjust parameters, and supports interface with a cloud platform for remote parameter updates and data uploads.

[0097] Based on functional integration, this invention further enhances the ease of use, comfort, and adaptability of the entire system through wearable integrated design, making it suitable for clinical medical institutions as well as meeting the needs of patients in various scenarios such as home rehabilitation and self-training.

[0098] The entire system integrates the following modules into a single host unit via wired / wireless connection: a multi-point flexible electrode array patch, a high-frequency stimulation module, a sensing module (EMG+IMU), a closed-loop feedback module, and a wireless communication and power supply module; it has a suitable wearable form and adaptability.

[0099] Both the flexible electrode array patch and the sensing module are made of hypoallergenic medical-grade flexible silicone or thermoplastic elastomer (TPE), which has good skin fit and breathability, and supports multiple fixation methods such as Velcro, elastic straps, and clothing embedding, making it suitable for use on different body parts (such as upper arms, back, and legs). The overall device is lightweight, easy to wear for a long time, and has no significant foreign body sensation.

[0100] The flexible electrode array patch is reusable and supports cleaning and disinfection with alcohol or hypochlorous acid spray; the control unit has an IPX4 or higher splash-proof rating and can cope with sweaty or slightly humid environments; the internal electrode interface and circuit are waterproof and oxidation-proof encapsulated.

[0101] The system supports human-computer interaction and remote control:

[0102] a. Supports parameter setting and mode switching via APP, Bluetooth controller, and PC software;

[0103] b. It can remotely interact with doctors / technicians to upload treatment data or receive personalized configurations (such as cloud platform interfaces);

[0104] c. It provides one-button start / stop, status indicator lights, and multi-language prompts, making it suitable for the elderly and people with mobility impairments.

[0105] Example 1: Personalized electromyographic-triggered closed-loop stimulation in upper limb functional rehabilitation of stroke patients

[0106] Target audience: Stroke rehabilitation patients with mild to moderate upper limb motor dysfunction who have basic active grasping ability and need to improve muscle strength and nerve response efficiency.

[0107] Implementation plan: The wrist flexor muscle is fitted with an electromyography (EMG) sensor to detect the upper limb grasping ability, decode the electromyographic characteristics of the grasping force, and when a specific threshold is reached, individualized parameter stimulation is given to enhance the neural connection and plasticity changes from the spinal cord to the muscle.

[0108] Example 2: Automatic selection of optimal stimulation target and parameters

[0109] Suitable for: Patients with motor dysfunction caused by various diseases.

[0110] Implementation plan: An electromyography (EMG) sensor is applied to the wrist flexor muscles to detect the upper limb grasping ability. Low-frequency stimulation is applied sequentially at different electrode points to monitor the effect on electromyography. The stimulation site with the greatest impact on the amplitude of electromyography is automatically selected as the stimulation target. At the same time, burst stimulation from 1Hz to 150Hz is applied sequentially at 55Hz intervals, with the frequency within the burst fixed at 10kHz. The stimulation frequency with the greatest impact on the amplitude of electromyography is automatically selected as the stimulation parameter.

[0111] Example 3: Motor function assistance for patients with spinal cord injury

[0112] Target audience: Spinal cord injury patients, especially those with partial thoracolumbar spinal cord injury who can perform basic upper limb movements and need to restore upper limb-hand coordination.

[0113] Implementation plan: Inertial sensors (such as accelerometers) are attached to the upper arm, lower arm, and back of the hand to sense the initiation and amplitude of movements such as grasping, gripping, and gross motor movements of the upper limbs. The accelerometers capture the movement initiation signal, and based on the set personalized threshold, the system selects an appropriate electrode combination according to the movement and outputs stimulation, thereby outputting individualized parameter stimulation to enhance the neural connection and plasticity changes from the spinal cord to the muscles.

[0114] Any aspects not covered in this invention are applicable to existing technologies.

[0115] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A closed-loop non-invasive spinal cord electrical stimulation modulation method based on motion data, characterized in that, The method includes the following steps: Step 1: Configure a flexible electrode array patch consisting of multiple independently controlled electrode units and attach it to the surface of the human skin to be tested; Step 2: Collect the user's electromyography (EMG) or acceleration signals; Step 3: Process the collected signals and extract feature values ​​related to actions and movements; Step 4: Compare the feature values ​​with the features / thresholds set in the model to determine whether to activate the stimulation site and adjust the stimulation parameters. Step 5: Automatically select the optimal electrode unit and corresponding stimulation parameters based on the judgment result; Step 6: Control the output stimulation current of the optimal electrode unit to regulate the activity of the corresponding spinal cord neurons; Step 7: Repeat steps 2 to 6 to continuously optimize and adjust the electrode unit and stimulation parameters in a closed loop based on motion feedback data.

2. The closed-loop non-invasive spinal cord electrical stimulation modulation method based on motion data according to claim 1, characterized in that, In step 1, multiple flexible electrode units are arranged into a two-dimensional or three-dimensional matrix structure, and modulation or interference methods are used to implement corresponding stimulation parameters to optimize the treatment effect at different time points and different stimulation positions.

3. The closed-loop non-invasive spinal cord electrical stimulation modulation method based on motion data according to claim 1, characterized in that, The electromyographic signals in step 2 are acquired by surface electromyographic electrodes or accelerometers.

4. A closed-loop non-invasive spinal cord electrical stimulation modulation system based on motion data, characterized in that, The system includes: A flexible electrode array patch comprising multiple flexible independent electrode units arranged in a two-dimensional or three-dimensional matrix structure; The high-frequency stimulation module is provided with electrode channels corresponding to the multiple electrode units. Each electrode channel outputs a high-frequency modulated square wave / sine wave current from 1kHz to 20kHz. The high-frequency sine waves can be superimposed to form an interference frequency of 1Hz to 150Hz. The sensing module is used to collect the user's electromyography and acceleration signals in real time; The closed-loop feedback module collects electromyographic and acceleration data from the sensing module in real time, extracts feature values ​​related to action and movement, compares the feature values ​​with the model-set features / thresholds, determines whether to initiate closed-loop control of stimulation site and stimulation parameter adjustment, and outputs parameter control instructions. The dynamic control module is connected to the closed-loop feedback module and the high-frequency stimulation module, receives parameter control commands output by the closed-loop feedback module, and adjusts the frequency, output intensity, and electrode activation position of each channel in the high-frequency stimulation module in real time.

5. The closed-loop non-invasive spinal cord electrical stimulation modulation system based on motion data according to claim 4, characterized in that, The sensing module includes: Electromyography (EMG) sensors are surface electromyographic electrodes placed on the target muscle group. Inertial sensors, which integrate 6-axis or 9-axis sensor modules, can detect three-axis acceleration, angular velocity and attitude changes of limb movements; The data acquisition and preprocessing module is used to perform preprocessing on the acquired signals, including filtering, baseline drift correction, and preliminary feature extraction. The communication module transmits data with the closed-loop feedback module and the dynamic control module, respectively.

6. The closed-loop non-invasive spinal cord electrical stimulation modulation system based on motion data according to claim 4, characterized in that, The closed-loop feedback module includes: A data buffer receives and temporarily stores the electromyographic data and acceleration motion data from the sensing module. Signal processing and decoding are used for real-time online analysis and processing of electromyographic and acceleration data, and for decoding motion intent from acceleration data; The comparator combines model-defined features / thresholds with electromyography and acceleration motion data responses to determine whether closed-loop regulation is needed to adjust the initiation stimulus, switch target points, or enhance output. The controller generates a parameter adjustment instruction based on the comparator's determination result and transmits it to the dynamic control module to perform the parameter adjustment.

7. The closed-loop non-invasive spinal cord electrical stimulation modulation system based on motion data according to claim 6, characterized in that, The controller is loaded with a muscle strength feedback strategy model, a tremor control feedback strategy model, and a pain relief feedback strategy model.

8. The closed-loop non-invasive spinal cord electrical stimulation modulation system based on motion data according to claim 7, characterized in that, The dynamic control module includes a manual setting module and an adaptive control module. The manual setting module is used by professionals to preset parameters on the interface. The adaptive control module automatically adjusts the optimal stimulation scheme based on real-time collected motion feedback data using a preset algorithm.

9. The closed-loop non-invasive spinal cord electrical stimulation modulation system based on motion data according to any one of claims 4-8, characterized in that, The flexible electrode array patch, high-frequency stimulation module, sensing module, closed-loop feedback module and dynamic control module are integrated into a portable device, and the outer shell of the portable device is made of antibacterial medical silicone.

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