Stimulation system for treating tremor, and action method and stimulation parameter adjustment method

Abstract

The present application relates to the technical field of medical treatment, and in particular to a stimulation system for treating a tremor, and an action method and a stimulation parameter adjustment method. The stimulation system comprises: an execution part, which is used for applying to at least one target position of a human body a target stimulation action for treating a tremor; a collection part, which is used for collecting a movement state signal of at least one target position of the human body and collecting motor cortex electrocorticogram of the human body; and a control part, which generates target stimulation parameters on the basis of the movement state signal and the motor cortex electrocorticogram, and adjusts, on the basis of the target stimulation parameters, the target stimulation action for treating a tremor that is applied by the execution part. Therefore, the problems in the prior art, such as the effect of drug treatment being poor, a brain pacemaker surgery having a high risk, a high cost and a poor safety, and vibrating gloves treatment having poor comfort and user-friendliness and thus affecting normal daily life of patients, are solved.

Description

Stimulation systems, methods of action, and methods of adjusting stimulation parameters for treating tremor

[0001] Cross-references to related applications

[0002] This application is based on and claims priority to Chinese Patent Application No. 202411695995.8, filed on November 25, 2024, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This application relates to the field of medical technology, and in particular to a stimulation system, method of action, and method of adjusting stimulation parameters for treating tremor. Background Technology

[0004] Pathological tremor is a common movement disorder in neuroscience, encompassing two main categories: resting tremor and action tremor. Resting tremor is more common in Parkinson's disease (PD), while action tremor is more common in essential tremor (ET). Clinically, Parkinson's disease is primarily characterized by resting tremor, bradykinesia, rigidity, and postural instability. Based on different clinical features, it is classified into tremor-predominant type, gait instability and postural abnormality type, and mixed type. Essential tremor is characterized primarily by action tremor, meaning that tremor only occurs during limb movement and does not occur when the limb is at rest.

[0005] Currently, treatment methods mainly include drug therapy and neuromodulation techniques, as detailed below:

[0006] 1) Drug treatment protocols: For essential tremor, early treatment primarily involves medication, including drugs such as aprolol, propranolol, and primidone. For Parkinson's disease, the main medications include levodopa, lidocaine, and selegiline. Parkinson's patients, however, show poor responsiveness to levodopa and levodopa.

[0007] 2) Neuromodulation Techniques: Neuromodulation techniques include invasive and non-invasive methods. Invasive neuromodulation primarily refers to deep brain stimulation, which is expensive, technically demanding, and involves a degree of trauma. Non-invasive neuromodulation mainly involves vibrating gloves, but these methods suffer from poor patient comfort and disruption to daily life. Summary of the Invention

[0008] This application provides a stimulation system, method of action, and method of adjusting stimulation parameters for treating tremor, in order to solve the problems of poor efficacy of existing drug treatments, high risk, high cost, and poor safety of brain pacemaker surgery, and poor comfort and humanization of vibration glove treatment, which affects the normal life of patients.

[0009] The first aspect of this application provides a stimulation system for treating tremor, comprising: an execution unit for applying a target stimulation action for treating tremor to at least one target location of the human body; a acquisition unit for acquiring motion state signals of at least one target location of the human body and acquiring a motor cortical electroencephalogram (EEG) of the human body; and a control unit for generating target stimulation parameters based on the motion state signals and the EEG, and adjusting the target stimulation action for treating tremor applied by the execution unit based on the target stimulation parameters.

[0010] Optionally, the execution unit includes at least one stimulation unit, wherein the at least one stimulation unit applies a corresponding target stimulation action for treating tremor based on target stimulation parameters.

[0011] Optionally, if at least one stimulus unit is multiple stimulus units, then at least one of the wearing methods, target stimulus actions, and combination methods of the multiple stimulus units is different.

[0012] Optionally, the wearing method includes at least one of wearable, adhesive, and external types, the target stimulation action includes at least one of vibration stimulation, mechanical stimulation, electrical stimulation, thermal stimulation, radiation stimulation, magnetic stimulation, light stimulation, chemical stimulation, ultrasound stimulation, and infrared stimulation, and the combination method includes array combination.

[0013] Optionally, the acquisition unit includes at least one of an accelerometer, a gyroscope, an inertial measurement unit, and an EEG cap.

[0014] Optionally, the stimulation system for treating tremor also includes a power source for supplying power to the stimulation system for treating tremor.

[0015] A second aspect of this application provides a medical device including the stimulation system for treating tremors described in the above embodiments.

[0016] The third aspect of this application provides a method for applying a stimulation system to treat tremor, comprising a human body part and a device part; the human body part includes receptors, actuators, and a controller, wherein the receptors include vestibular hair cell units and muscle spindle tendon units, the actuators include spinal cord units and muscle units, and the controller includes lateral cuneus nucleus units, vestibular nucleus units, brainstem units, cerebellum units, and motor cortex units; the device part includes an execution unit, a data acquisition unit, and a control unit, wherein the data acquisition unit sends acquired motion state signals and motor cortex EEG sensor data to the control unit, the control unit generates stimulation parameters based on the acquired motion state signals and motor cortex EEG sensor data, and sends the stimulation parameters to the execution unit, the execution unit applies peripheral stimulation actions to the receptors to generate sensory input according to the stimulation parameters; the method for applying the stimulation system to treat tremor includes the following steps:

[0017] The receptors input peripheral sensory inputs to the vestibular hair cell unit and muscle spindle tendon unit, generating sensory feedback signals. The vestibular hair cell unit and muscle spindle tendon unit send the sensory feedback signals to the lateral cuneus nucleus unit and vestibular nucleus unit. The lateral cuneus nucleus and vestibular nucleus unit send the sensory feedback signals to the cerebellum unit. The cerebral cortex unit sends motor command signals to the cerebellum unit. The cerebellum unit generates motor correction signals based on the motor command signals and sensory feedback signals, and sends the motor correction signals to the brainstem unit. The brainstem unit sends the motor correction signals to the spinal cord unit. The cerebral cortex unit sends the motor state signals to the spinal cord unit. The spinal cord unit generates corrected motor command signals based on the motor correction signals and motor command signals, and sends them to the muscle unit. The muscle unit generates the final motor state signals based on the corrected motor command signals.

[0018] The fourth aspect of this application provides a method for adjusting stimulation parameters in the treatment of tremor. This method is used to adjust the target stimulation parameters of the stimulation system for treating tremor described in the above embodiments, and includes the following steps: acquiring motion state signals at at least one target location of a test subject; acquiring a motor cortical electroencephalogram (ECG) of the test subject; modeling a first network model, using a standard stimulation parameter sequence set and the EEG as inputs to the network model, and the motion state signals as outputs, wherein the first network model simulates the neural pathways and networks related to tremor on the first day of tremor treatment using the stimulation system; testing the first network model by changing the stimulation parameters to transform the motion state signals from a pathological state to a physiological state, obtaining a target stimulation parameter sequence set for the first network model; starting from the first network model, using the EEG and the target stimulation parameter sequence set of the previous network as inputs to the network model, and the motion state signals as outputs, modeling a current network model; changing the stimulation parameters to transform the motion state signals from a pathological state to a physiological state, obtaining a target stimulation parameter sequence set for the current network; and adjusting the target stimulation action applied by the actuator for treating tremor according to the target stimulation parameters.

[0019] Optionally, the network model can be a control model that simulates a neural network related to human tremor. The control model is used to adjust the target stimulus parameters and includes the following steps: using motor cortical electroencephalography (EEG) as input to the control model and motor state signals as output; obtaining the state equations or transfer functions of each part of the control model through system identification and mathematical modeling methods; performing system stability analysis based on the state equations or transfer functions to determine the target stimulus parameters that can make the system tend to stabilize, so that the motor state signals change from a pathological state to a physiological state, thus obtaining the target stimulus parameters; and adjusting the target stimulus action applied by the actuator to treat tremor according to the target stimulus parameters.

[0020] Optionally, the network model can be a neural network model that simulates a neural network related to human tremor. The neural network model is used to adjust the target stimulus parameters, including the following steps: using the motor cortex electroencephalogram as input to the neural network model, adjusting the parameters of the neural network model so that the output of the neural network model is consistent with the motion state signal, wherein the neural network model simulates a neural network related to human tremor; inputting different stimulus parameters into the neural network model so that the motion state signal changes from a pathological state to a physiological state, thereby obtaining the target stimulus parameters.

[0021] Optionally, the network model can be a nonlinear dynamic model, which simulates a neural network related to human tremor. The nonlinear dynamic model is used to adjust the target stimulus parameters, including the following steps: using the motor cortex electroencephalogram as input to the nonlinear dynamic model, adjusting the parameters of the nonlinear dynamic model so that the output of the nonlinear dynamic model and the motion state signal tend to be consistent; wherein, the nonlinear dynamic model simulates the neural network related to human tremor as a nonlinear dynamic system formed by coupling multiple oscillators; inputting different stimulus parameters into the nonlinear dynamic model so that the motion state signal changes from a pathological state to a physiological state, thereby obtaining the target stimulus parameters.

[0022] A fifth aspect of this application provides a computer-readable storage medium having a computer program or instructions stored thereon, which, when executed, are used to implement the stimulation parameter adjustment method for treating tremor as described in the above embodiments.

[0023] A sixth aspect of this application provides a computer program, including computer programs or instructions, which, when executed, are used to implement the stimulation parameter adjustment method for treating tremor as described in the above embodiments.

[0024] Therefore, this application has the following beneficial effects:

[0025] The control unit of this application, based on the human body's motion state signals and motor cortical electroencephalogram (EEG) monitored by the acquisition unit, adjusts the target stimulation parameters of multiple stimulation units in real time to stimulate the target position of the human body to treat tremors, forming a closed-loop control system to better suppress and treat tremors, achieving the best therapeutic effect. This solves the problems of poor drug treatment effects, high risk, high cost, and poor safety of deep brain stimulation surgery, and poor comfort and humanization of vibration glove treatment, which affects the patient's normal daily life.

[0026] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0027] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0028] Figure 1 is a block diagram of a stimulation system for treating tremor according to an embodiment of this application;

[0029] Figure 2 is a detailed example diagram of a stimulation system for treating tremors according to an embodiment of this application;

[0030] Figure 3 is a diagram illustrating the action of a stimulation system for treating tremor according to an embodiment of this application;

[0031] Figure 4 is an example diagram of stimulation parameters provided according to an embodiment of this application;

[0032] Figure 5 is a diagram of the stimulation parameter adjustment method for treating tremor according to an embodiment of this application;

[0033] Figure 6 is an example diagram of a stimulation parameter adjustment method for treating tremor according to an embodiment of this application;

[0034] Figure 7 is an example diagram of adjusting stimulation parameters using a nonlinear dynamic model according to an embodiment of this application. Detailed Implementation

[0035] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0036] The following description, with reference to the accompanying drawings, describes a stimulation system, method of action, and stimulation parameter adjustment method for treating tremors according to embodiments of this application. Addressing the problems mentioned in the background section, this application provides a stimulation system for treating tremors. The control unit dynamically adjusts the target stimulation parameters of multiple stimulation units based on the motion state signals and motor cortical electroencephalogram (EEG) monitored by the acquisition unit to stimulate the target location of the body to treat tremors, forming a closed-loop control system to better suppress and treat tremors, achieving the best therapeutic effect. This solves the problems of poor drug treatment efficacy, high risk, high cost, and poor safety of deep brain stimulation (DBS) surgery, and poor comfort and humanization of vibration glove therapy, which affects the patient's normal daily life.

[0037] Specifically, Figure 1 is a block diagram of a stimulation system for treating tremors according to an embodiment of this application.

[0038] As shown in Figure 1, the stimulation system for treating tremor includes an execution unit 101, a acquisition unit 102, and a control unit 103.

[0039] The execution unit 101 is used to apply a therapeutic tremor target stimulation action to at least one target location of the human body; the acquisition unit 102 is used to acquire motion state signals and motor cortical electroencephalograms of at least one target location of the human body; the control unit 103 generates target stimulation parameters based on the motion state signals and motor cortical electroencephalograms, and adjusts the therapeutic tremor target stimulation action applied by the execution unit 101 according to the target stimulation parameters.

[0040] In this embodiment, the execution unit 101 includes multiple stimulation units, at least one of which applies a corresponding target stimulation action to treat tremor based on target stimulation parameters. The multiple stimulation units differ in at least one of their wearing method, stimulation method, and combination method, and the target stimulation action applied by the multiple stimulation units stimulates at least one target location on the human body to treat tremor.

[0041] Furthermore, the stimulation system for treating tremors in this application embodiment may also be equipped with a power supply to power the stimulation system for treating tremors, or an external power supply may be used, without specific limitations.

[0042] Specifically, as shown in Figure 2, the execution unit 101 in this embodiment includes a first stimulation unit, a second stimulation unit, a third stimulation unit, ..., an Nth stimulation unit. It treats tremors by applying target stimulation parameters to at least one target location on the human body through multiple stimulation units. In this embodiment, these stimulation units can be worn, stimulated, or combined in different ways. Wearing methods can be categorized as wearable, adhesive, or external. Wearable types include wristbands, adhesive types include flexible electronic devices attached to the skin surface, and external types include execution unit 101 in contact with the human body, while control unit 103 is external and does not contact the human body. Target stimulation actions include at least one of vibration stimulation, mechanical stimulation, electrical stimulation, thermal stimulation, radiation stimulation, magnetic stimulation, light stimulation, chemical stimulation, ultrasound stimulation, and infrared stimulation. Combinations can include array combinations, such as wearable stimulation wristbands with multiple stimulation units on the inner side. The array of these stimulation units forms the stimulation application unit, which is an array combination. The specific arrangement of the wristband array is determined based on the patient's symptoms and diagnostic results. The acquisition unit 102 includes an accelerometer, a gyroscope, an inertial measurement unit, and an EEG cap, etc., to acquire motion state signals of at least one target location of the human body, including signals such as acceleration, velocity, position, and frequency of body parts. The control unit 103 mainly generates target stimulation parameters based on the motion state signals and motor cortical EEG obtained by the acquisition unit 102, and adjusts the target stimulation action applied by the execution unit 101 to treat tremor according to the target stimulation parameters. The target stimulation parameters include at least one of stimulation frequency, stimulation amplitude, time interval between multiple stimulation units, and stimulation sequence of multiple stimulation units. In actual execution, this embodiment can transmit the target stimulation parameters to the execution unit 101 to treat tremor. Compared with drug therapy and invasive neuromodulation techniques, the sensory input-based treatment plan is safer and non-invasive, avoiding surgical risks and drug side effects.

[0043] Figure 3 is a block diagram illustrating the action of the stimulation system for treating tremor according to an embodiment of this application. In actual implementation, the stimulation system for treating tremor according to this embodiment regulates cerebellar function through sensory input to treat tremor symptoms caused by essential tremor and Parkinson's disease. The cerebellum is an important component of brain tissue, responsible for coordinating and regulating muscle movement, including fine motor control and motor learning. The cerebellum receives instruction signals from the motor cortex and sensory signals transmitted by sensory neurons, performs complex calculations to generate appropriate motor correction signals, and sends them to the spinal cord, thereby regulating and correcting movement in real time.

[0044] Further, as shown in Figure 3, with the cerebellum as the core, the cerebellum in this embodiment is located in the feedback loop of motor control, receiving motor command signals from the motor cortex and sensory signals transmitted by sensory neurons. Calculations are performed in the cerebellum, and motor correction signals are output to the spinal cord, thereby influencing the motor control of the spinal cord and ultimately correcting the abnormal tremor. The stimulation system's action method includes the actions of both the human body and the device. The action pathway demonstrates how the device adjusts stimulation parameters based on the human body's motion state signals and sensory data from the motor cortex's electroencephalogram (EEG), applying sensory input to the human body. The sensory signals include: touch, proprioception, vestibular sensation, and vision, while the motion state signals include: acceleration, velocity, position, and frequency of body parts.

[0045] In this embodiment, as shown in Figure 3, the human body portion includes receptors, actuators, and controllers. The receptors include vestibular hair cell units and muscle spindle tendon units; the actuators include spinal cord units and muscle units; and the controllers include lateral cuneus nucleus units, vestibular nucleus units, brainstem units, cerebellum units, and cerebral cortex units. The spinal cord and muscle units transmit motion state signals to each other. The vestibular hair cell units and muscle spindle tendon units transmit sensory feedback signals to the cerebellum units. The motor cortex units transmit motion command signals to the spinal cord units. The cerebellum units generate motion correction signals based on the motion command signals and sensory feedback signals. The spinal cord units generate final motion command signals based on the motion correction signals and motion command signals and transmit them to the muscle units. The muscle units determine the target stimulation parameters based on the final motion command signals.

[0046] Specifically, in this embodiment, the controller of the human body is mainly the brain, the actuators are the spinal cord and muscles, and the controlled object is the actual movement state, which is represented by a movement state signal. The motor cortex transmits movement commands to the spinal cord, which in turn transmits them to the muscles, generating the actual movement state. Simultaneously, the motor cortex also transmits movement commands to the cerebellum. The movement commands are compared and calculated in the cerebellar cortex with sensory feedback signals. These sensory feedback signals originate from proprioceptive signals generated by the muscle spindle and transmitted to the lateral cuneus nucleus, and vestibular sensory signals generated by the hair cells of the vestibular organ and transmitted to the vestibular nucleus. The cerebellum obtains the difference between the actual and desired movement states through the sensory feedback signals, calculates the difference, and outputs a movement correction signal to the brainstem. This correction signal is compared and calculated in the spinal cord with the movement commands directly transmitted from the motor cortex, and the corrected movement commands are then output to the muscles to generate the corrected actual movement state.

[0047] According to the stimulation system for treating tremors proposed in this application, the control unit, based on the motion state signals and motor cortical electroencephalogram (EEG) monitored by the acquisition unit, adjusts the target stimulation parameters of multiple stimulation units in real time to stimulate the target location of the body to treat tremors, forming a closed-loop control system to better suppress and treat tremors, achieving the best therapeutic effect. This solves the problems of poor efficacy of drug treatment, high risk, high cost, and poor safety of deep brain stimulation surgery, and poor comfort and humanization of vibration glove treatment, which affects the patient's normal life.

[0048] Because the nervous system possesses plasticity—the ability of the brain and nervous system to alter its structure and function in response to environmental changes or experiential learning—it means that if the nervous system is continuously given specific types of stimulation, it can retain and utilize these newly learned patterns or information even after the stimulation ceases. Utilizing the principles of neural plasticity in the treatment of tremors can achieve long-term symptom improvement.

[0049] It is understood that the embodiments of this application can treat tremor by applying target stimulation parameters to the target location of the human body through multiple stimulation units. This can effectively intervene in the activity of the cerebellum and related neural networks, utilize the body's natural neural feedback mechanism to correct abnormal motor control signals, thereby reducing tremor symptoms and achieving long-term tremor relief, as detailed below:

[0050] 1. Compared with drug treatment, this application reduces the risk of drug side effects, especially drug resistance and other adverse reactions that may result from long-term drug use.

[0051] 2. Compared with invasive neuromodulation devices, the sensory input-based treatment method provided in this application does not require surgical implantation, avoiding related surgical risks and possible complications, and is safer.

[0052] 3. Utilizing the plasticity of the nervous system, long-term sensory input may produce a lasting therapeutic effect, which may continue even after the stimulation is stopped.

[0053] 4. Once the physical equipment required for sensory input is industrialized, the cost will be very low because it applies physical stimulation and acts on the body surface. The generation of stimulation and the manufacturing of the equipment are cheaper than deep brain stimulation therapy. In addition, the cost is significantly reduced compared to drug therapy.

[0054] 5. For patients with essential tremor and Parkinson's disease, this application may significantly improve their quality of life, reduce inconvenience in work and life, increase life satisfaction and well-being, increase the number of available labor forces in society, and promote the improvement of social efficiency.

[0055] As shown in Figure 4, the target stimulus parameters may include stimulus frequency, stimulus amplitude, time interval between multiple stimulus units, and stimulation order of multiple stimulus units. As an example, the horizontal axis represents time, and the vertical axis represents stimulus units. This embodiment uses four stimulus units as an example; the dashed line represents one stimulus cycle, and the wavy line represents the stimulation of a single stimulus unit. The stimulus parameters of a single stimulus unit include: stimulus frequency and stimulus amplitude. The stimulus parameters of multiple stimulus units include: time interval between multiple stimulus units and stimulation order of multiple stimulus units.

[0056] The method for adjusting stimulation parameters for treating tremor according to an embodiment of this application is described with reference to the accompanying drawings. This method is used to adjust the target stimulation parameters of the stimulation system for treating tremor as described above.

[0057] Figure 5 is a flowchart illustrating a method for adjusting stimulation parameters to treat tremor, as provided in an embodiment of this application.

[0058] As shown in Figure 5, the method for adjusting the stimulation parameters for treating tremor includes the following steps:

[0059] In step S501, the motion state signal of at least one target location of the test subject and the motor cortex electroencephalogram of the test subject are acquired.

[0060] The motion state signal may include the acceleration, velocity, position and frequency of body parts. In this application embodiment, the body parts related to the treatment of tremor may be selected as the target location, such as the body area closely related to cerebellar function, or the muscles and joints directly related to tremor.

[0061] In step S502, a first network model is modeled by taking the standard stimulus parameter sequence set and the motor cortex EEG as inputs to the network model and the motion state signal as outputs to the network model. The first network model simulates the neural pathways and networks related to tremor in the human body on the first day of tremor treatment using the stimulation system.

[0062] In step S503, the first network model is tested, and the stimulation parameters are changed so that the motion state signal changes from a pathological state to a physiological state, thereby obtaining the target stimulation parameter sequence set of the first network model.

[0063] In step S504, starting from the first network model, the motor cortical electroencephalogram and the target stimulus parameter sequence set of the previous network of the current network are used as inputs to the network model, and the motor state signal is used as the output of the network model to model the current network model; the stimulus parameters are changed so that the motor state signal changes from a pathological state to a physiological state, and the target stimulus parameters of the current network are obtained.

[0064] Specifically, as shown in Figure 6, the first step is data acquisition: EEG signals from the motor cortex are collected during fixed motor behaviors, such as writing a fixed string of text. Simultaneously, a stimulation sequence with standard stimulation parameters is applied to the human sensory system, and motion state information of the tremor site is collected, including tremor amplitude and frequency. The second step is network modeling: The motor cortex EEG and the standard stimulation sequence are used as inputs to the network, and the motion state information is used as the network output. If the network output can well simulate the actual motion state signal for different stimulation parameter sequences, then the modeling of the first network is stopped. The third step is network testing: The parameters of the modeled network are fixed, and the stimulation parameters are changed. The stimulation sequence and the motor cortex EEG obtained in the first step are input, and different stimulation parameters are tested to reduce the tremor frequency and amplitude output by the network. These stimulation parameters that reduce the tremor frequency and amplitude are recorded as stimulation sequence set 1 and will be used for treatment the next day. On the second day, using the stimulation sequence set 1 obtained from the test simulation, steps one and two are repeated to model network 2. Since this network is used to simulate human tremor-related networks, based on the plasticity of human neurons, the specific parameters of the network will change. After modeling, step three is executed. This process continues until day N (where N is typically two weeks and can be adjusted based on the patient's condition), when the patient's motion status information shows a decrease in both the amplitude and frequency of their tremors, thus alleviating the tremors.

[0065] In one embodiment of this application, the network model is a control model used to adjust target stimulus parameters, including: using the motor cortical electroencephalogram as input to the control model, using the motion state signal as output to the control model, obtaining the state equation or transfer function of each unit of the control model through system identification and mathematical modeling methods, wherein the control model simulates a neural network related to human tremor; performing system stability analysis based on the state equation or transfer function to determine the target stimulus parameters that can make the system tend to stabilize, thereby changing the motion state signal from a pathological state to a physiological state, and obtaining the target stimulus parameters.

[0066] Based on the aforementioned tremor-related control model, this embodiment of the application can use the EEG of the motor cortex of the brain as input and the motion state signal (actual motion state) as the model output. The transfer function and state equation of the control model can be obtained using system identification or direct modeling methods to analyze the controllability and observability of the system. Stability analysis is performed on the phase plane to identify the unstable state of the tremor patient, and stimulation strategies are designed to apply stimulation to the peripheral related links of the system, enabling the system to return to a stable state, alleviating tremor symptoms, and ensuring the effectiveness and safety of the treatment.

[0067] The control model includes a state equation and a transfer function. Target stimulation parameters for multiple stimulation units are determined based on the state equation and transfer function. The specific method for adjusting the stimulation parameters is as follows: For tremor patients, their transfer function or state equation is in a pathological state of critical stable oscillation or instability on the phase plane. The stimulus is located at the output of the control model, and stimulation parameters that can bring the system back to a stable physiological state are calculated based on the transfer function.

[0068] In one embodiment of this application, the network model is a neural network model, which is used to adjust the target stimulus parameters, including: using the motor cortex electroencephalogram as input to the neural network model, adjusting the parameters of the neural network model so that the output of the neural network model and the motion state signal tend to be consistent, wherein the neural network model simulates a neural network related to human tremor; inputting different stimulus parameters into the neural network model so that the motion state signal changes from a pathological state to a physiological state, thereby obtaining the target stimulus parameters.

[0069] In this application embodiment, any neural network that enables the input-output relationship can be used, and the neural network structure will differ for different patients. Neural network structures include LSTM (Long Short-Term Memory), RNN (Recurrent Neural Network), CNN (Convolutional Neural Network), etc. This application embodiment can adjust the target stimulus parameters of multiple stimulus units using a neural network model. Utilizing a large amount of physiological data, including EEG (Electroencephalography) of the patient's motor cortex and tremor-related motion state information, the neural network model is trained to predict and optimize stimulus parameters to achieve the best tremor relief effect.

[0070] In one embodiment of this application, the network model is a nonlinear dynamic model, which is used to adjust the target stimulus parameters, including: using the motor cortex electroencephalogram as input to the nonlinear dynamic model, adjusting the parameters of the nonlinear dynamic model so that the output of the nonlinear dynamic model and the motion state signal tend to be consistent; wherein, the nonlinear dynamic model simulates the neural network related to human tremor as a nonlinear dynamic system formed by coupling multiple oscillators; inputting different stimulus parameters into the nonlinear dynamic model so that the motion state signal changes from a pathological state to a physiological state, thereby obtaining the target stimulus parameters.

[0071] In this embodiment, the nervous system associated with tremor can be simulated as a nonlinear dynamic system formed by the coupling of multiple oscillators. A nonlinear dynamic model is established by creating differential equations for each oscillator, with dependencies between variables in these equations. As shown in Figure 7, nonlinear dynamic models such as attractor models and the Kuramoto model can be used. The wearer's motor cortex EEG is used as the input to the nonlinear dynamic model, and tremor-related motion state signals are used as the output. Further, a synchronization index within the network is established. Applying different stimuli reduces the synchronization index, causing the system to move from an unfavorable attractor to a favorable attractor, thereby alleviating tremor symptoms. Stimulation parameters that reduce the system's synchronization index are simulated using the nonlinear dynamic model, and the actual stimulation parameters are adjusted based on these simulated parameters.

[0072] It should be noted that some steps in the stimulation parameter adjustment methods for treating tremors in the embodiments of this application can be referenced from each other. To avoid redundancy, they will not be described here.

[0073] The stimulation parameter adjustment method for treating tremor proposed in this application monitors the electroencephalogram (EEG) of the motor cortex and motor state signals of the human body. It then generates target stimulation parameters by combining any one of a neural network model, a control model, or a nonlinear dynamic model. These parameters are then used to adjust the target stimulation action applied by the actuator to treat tremor, thereby better suppressing the tremor and achieving the best therapeutic effect. This solves the problems of poor efficacy of drug treatment and the high risks, high costs, and poor safety of deep brain stimulation (DBS) surgery.

[0074] Furthermore, this application also provides a medical device, including the stimulation system for treating tremors described in the above embodiments.

[0075] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described method for adjusting stimulation parameters to treat tremors.

[0076] This application also provides a computer program, including computer programs or instructions, which, when executed, are used to implement the stimulation parameter adjustment method for treating tremor as described in the above embodiments.

[0077] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0078] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0079] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0080] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any of the following techniques known in the art, or a combination thereof: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (FPGAs), field-programmable gate arrays (FPGAs), etc.

[0081] Those skilled in the art will understand that all or part of the steps of the methods implementing the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0082] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A stimulation system for treating tremor, characterized in that include: The actuator is used to apply a targeted stimulus action for treating tremor to at least one target location on the human body; The acquisition unit is used to acquire motion state signals at at least one target location of the human body and to acquire electroencephalograms of the human body's motor cortex. The control unit generates target stimulation parameters based on the motion state signal and the motor cortex electroencephalogram, and adjusts the target stimulation action for treating tremor applied by the execution unit according to the target stimulation parameters.

2. The stimulation system for treating tremor according to claim 1, characterized in that, The actuator includes at least one stimulation unit, wherein the at least one stimulation unit applies a corresponding target stimulation action for treating tremor based on the target stimulation parameters.

3. A stimulation system for the treatment of tremor according to claim 2, characterized in that, If the at least one stimulation unit is multiple stimulation units, then at least one of the multiple stimulation units is different in terms of wearing method, target stimulation action, and combination method.

4. A stimulation system for the treatment of tremor according to claim 3, characterized in that, The wearing method includes at least one of wearable, adhesive, and external types; the target stimulation action includes at least one of vibration stimulation, mechanical stimulation, electrical stimulation, thermal stimulation, radiation stimulation, magnetic stimulation, light stimulation, chemical stimulation, ultrasound stimulation, and infrared stimulation; and the combination method includes array combination.

5. The tremor therapy stimulation system according to claim 1, characterized in that, The acquisition unit includes at least one of an accelerometer, a gyroscope, an inertial measurement unit, and an EEG cap.

6. A medical device, characterized by The stimulation system for treating tremor as described in any one of claims 1-5.

7. A method of treating tremor with a stimulation system, characterized in that, The system comprises a human body part and a device part. The device part is the stimulation system for treating tremor as described in any one of claims 1-5. The human body part includes a receptor, an actuator, and a controller. The receptor includes a vestibular hair cell unit and a muscle spindle tendon unit. The actuator includes a spinal cord unit and a muscle unit. The controller includes a lateral cuneus nucleus unit, a vestibular nucleus unit, a brainstem unit, a cerebellum unit, and a cerebral cortex unit. The device part includes an execution unit, a data acquisition unit, and a control unit. The data acquisition unit sends the acquired motion state signals and motor cortex EEG sensor data to the control unit. The control unit generates stimulation parameters based on the acquired motion state signals and motor cortex EEG sensor data and sends the stimulation parameters to the execution unit. The execution unit applies peripheral stimulation actions to the receptors to generate sensory input based on the stimulation parameters. The method of action of the stimulation system for treating tremor includes the following steps: The vestibular organ hair cell unit and the muscle spindle tendon unit send sensory input to the lateral cuneus nucleus unit and the vestibular nucleus unit to generate sensory feedback signals; The lateral cuneus and vestibular nucleus units send the sensory feedback signals to the cerebellar units; The cerebral cortex unit sends motion command signals to the cerebellum unit; The cerebellum unit generates a motion correction signal based on the motion command signal and the sensory feedback signal, and sends the motion correction signal to the brainstem unit. The brainstem unit sends the motion correction signal to the spinal cord unit; The cerebral cortex unit sends motion command signals to the spinal cord unit; The spinal cord unit generates a corrected motion command signal based on the motion correction signal and the motion command signal, and sends it to the muscle unit. The muscle unit generates the motion state signal based on the corrected motion command signal.

8. A method of adjusting stimulation parameters for treating tremor, characterized by, The method is used to adjust the target stimulation parameters of the stimulation system for treating tremor according to any one of claims 1-5, wherein the method includes the following steps: Acquire motion state signals at at least one target location of the test subject and the test subject's motor cortex electroencephalogram; A first network model is modeled by taking the standard stimulus parameter sequence set and the motor cortex EEG as inputs to the network model and the motor state signal as outputs to the network model. The first network model simulates the neural pathways and networks related to tremor in the human body on the first day of tremor treatment using the stimulation system. The first network model is tested by changing the stimulus parameters so that the motion state signal changes from a pathological state to a physiological state, thereby obtaining the target stimulus parameter sequence set of the first network model. Starting with the first network model, the motor cortex EEG and the target stimulus parameter sequence set of the previous network of the current network are used as inputs to the network model, and the motor state signal is used as the output of the network model to model the current network model; the stimulus parameters are changed so that the motor state signal changes from a pathological state to a physiological state, and the target stimulus parameters of the current network are obtained. The target stimulus action for treating tremor is adjusted by the actuator according to the target stimulus parameters of the current network.

9. The method of adjusting stimulation parameters for treating tremor according to claim 8, wherein, The network model is a control model, which is used to adjust the target stimulus parameters, including: The motor cortical electroencephalogram is used as the input to the control model, and the motion state signal is used as the output of the control model. The state equations or transfer functions of each unit of the control model are obtained through system identification and mathematical modeling methods. The control model simulates a neural network related to human tremor. Based on the state equation or transfer function, system stability analysis is performed to determine the target stimulus parameters that can make the system tend to stabilize, so that the motion state signal changes from a pathological state to a physiological state, and the target stimulus parameters are obtained.

10. The method of adjusting stimulation parameters for treating tremor of claim 8, wherein, The network model is a neural network model, which is used to adjust the target stimulus parameters, including: The motor cortex electroencephalogram (EEG) is used as the input to a neural network model. The parameters of the neural network model are adjusted so that the output of the neural network model is consistent with the motion state signal. The neural network model simulates a neural network related to human tremor. By inputting different stimulus parameters into a neural network model, the motion state signal is transformed from a pathological state to a physiological state, thereby obtaining the target stimulus parameters.

11. The method of adjusting stimulation parameters for treating tremor of claim 8, wherein, The network model is a nonlinear dynamic model, which is used to adjust the target stimulus parameters, including: The motor cortex electroencephalogram (EEG) is used as input to the nonlinear dynamic model. The parameters of the nonlinear dynamic model are adjusted so that the output of the nonlinear dynamic model is consistent with the motion state signal. The nonlinear dynamic model simulates the neural network related to human tremor as a nonlinear dynamic system formed by the coupling of multiple oscillators. By inputting different stimulus parameters into a nonlinear dynamic model, the motion state signal is transformed from a pathological state to a physiological state, thus obtaining the target stimulus parameters.

12. A computer readable storage medium having stored thereon a computer program or instructions, characterized in that, The computer program or instructions, when executed, implement the stimulation parameter adjustment method for treating tremor according to any one of claims 7-11.

13. A computer program product comprising computer programs or instructions, characterized in that, The computer program or instructions, when executed, implement the stimulation parameter adjustment method for treating tremor according to any one of claims 7-11.

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