Closed-loop brain deep electrical stimulation regulation and control method, device, equipment and medium

Abstract

The invention discloses a closed-loop deep brain stimulation regulation and control method, device and equipment and a medium, relates to the technical field of medical equipment and instruments, and is applied to a regulation and control system, and the regulation and control system comprises parameter acquisition host equipment, a target sensor and deep brain stimulation equipment; the method comprises the following steps: controlling deep brain stimulation equipment to send a current electrical stimulation signal to a stimulation target of a target object; using a target sensor to collect a current feedback signal after the target object receives the current electrical stimulation signal; wherein the current feedback signal is a kinematics and dynamics signal generated when the target object executes the Parkinson's action normal form, and the target sensor is located at a target detection part of the target object; and controlling parameter acquisition host equipment connected with the target sensor to send the current feedback signal to brain deep electrical stimulation equipment, so that the brain deep electrical stimulation equipment sends a next electrical stimulation signal to the stimulation target based on the current feedback signal. And more scientific deep brain electrical stimulation regulation and control can be realized.

Description

Technical Field

[0001] The present invention relates to the field of medical equipment and instrument technology, and in particular to closed-loop deep brain electrical stimulation control methods, devices, equipment and media. Background Art

[0002] Parkinson's disease patients may experience symptoms such as tremors, muscle rigidity, and bradykinesia. These symptoms can be treated with DBS (Deep Brain Stimulation). DBS stimulates the brain with microcurrents, altering the permeability and ion concentration of nerve cell membranes, thereby affecting cell function. Specifically, electrical stimulation pulses inhibit brain cell activity while stimulating brain cells, reducing the number of neurotransmitters and dopamine breakdown, thereby effectively controlling the disease. Most Parkinson's disease patients experience limb movement disorders, and tests such as finger pointing, fist clenching, and wrist flipping are routinely used during outpatient follow-up and intraoperative assessments. Currently, wearable devices such as watches and bracelets that can record sports information cannot be flexibly worn on suitable detection parts such as fingers, and therefore cannot evaluate finger movements such as pointing and clenching fists. Therefore, doctors currently control the deep brain stimulation device to send stimulation signals to the patient's brain after making subjective judgments on the patient. The evaluation of conventional doctors depends to a certain extent on the doctor's experience and subjective judgment, that is, the control of the stimulation signal of the deep brain stimulation device is too subjective, and the control may not be suitable for the patient.

[0003] In summary, how to achieve more scientific deep brain electrical stimulation regulation is a problem to be solved in this field. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a closed-loop deep brain stimulation control method, device, equipment and medium to achieve more scientific deep brain stimulation control. The specific scheme is as follows:

[0005] In a first aspect, the present application discloses a closed-loop deep brain stimulation control method, which is applied to a control system, wherein the control system includes a parameter acquisition host device, a target sensor, and a deep brain stimulation device; wherein the method includes:

[0006] Controlling the deep brain stimulation device to send a current electrical stimulation signal to a stimulation target point of the target subject;

[0007] Using the target sensor to collect a current feedback signal after the target object receives the current electrical stimulation signal; wherein the current feedback signal is a kinematic and dynamic signal generated when the target object performs a Parkinson's movement paradigm, and the target sensor is located at a target detection site of the target object;

[0008] Control the parameter acquisition host device connected to the target sensor to send the current feedback signal to the deep brain stimulation device, so that the deep brain stimulation device sends the next electrical stimulation signal to the stimulation target based on the current feedback signal.

[0009] Optionally, the target sensor is connected to the parameter acquisition host device via a cable, and the parameter acquisition host device includes a controller, a local storage, an external synchronization interface, and a sensor interface;

[0010] Accordingly, controlling the parameter acquisition host device connected to the target sensor to send the current feedback signal to the deep brain stimulation device includes:

[0011] The parameter acquisition host device receives the current feedback signal through the sensor interface and saves the current feedback signal to the local storage;

[0012] The controller sends the current feedback signal in the local storage to the deep brain stimulation device through the external synchronization interface.

[0013] Optionally, the control system further includes a signal regulator;

[0014] The controller sends the current feedback signal in the local storage to the deep brain stimulation device through the external synchronization interface, including:

[0015] The controller sends the current feedback signal in the local storage to the signal regulator through the external synchronization interface, so that the signal regulator processes the current feedback signal and sends the obtained processed signal and the current feedback signal to the deep brain stimulation device.

[0016] Optionally, the signal conditioner processes the current feedback signal to send the obtained processed signal and the current feedback signal to the deep brain stimulation device, including:

[0017] The signal conditioner filters the current feedback signal based on a preset frequency band to obtain a filtered signal, and removes abnormal data points in the filtered signal using a sliding window statistical method to obtain a removed signal;

[0018] Extracting motion features from the signal after elimination; wherein the motion features include tremor-related features, bradykinesia-related features, and myotonia-related features;

[0019] Determining a target feature conversion logic from each preset feature conversion logic; wherein each of the preset feature conversion logics includes a conversion logic based on threshold matching and a conversion logic based on machine learning;

[0020] The motion feature is quantized using the target feature conversion logic to obtain a processed signal, and the processed signal and the current feedback signal are sent to the deep brain stimulation device.

[0021] Optionally, the deep brain electrical stimulation device sends a next electrical stimulation signal to the stimulation target based on the current feedback signal, including:

[0022] The deep brain electrical stimulation device determines a target stimulation signal adjustment mode according to the processed signal and the current feedback signal, adjusts the current stimulation signal according to the target stimulation signal adjustment mode to obtain a next electrical stimulation signal, and then sends the next electrical stimulation signal to the stimulation target point;

[0023] The target stimulation signal adjustment mode includes any one or more of a stimulation position adjustment mode, a stimulation intensity adjustment mode, a stimulation range adjustment mode, a stimulation direction adjustment mode, and a stimulation shape adjustment mode.

[0024] Optionally, the controller sends the current feedback signal in the local storage to the signal conditioner through the external synchronization interface, including:

[0025] The controller sends the current feedback signal in the local storage to the signal conditioner via the external synchronization interface based on a wireless transmission method;

[0026] Accordingly, the signal conditioner processes the current feedback signal to send the obtained processed signal and the current feedback signal to the deep brain stimulation device, including:

[0027] The signal conditioner processes the current feedback signal to obtain a processed signal, and sends the processed signal and the current feedback signal to the deep brain stimulation device based on a wireless transmission method or an Ethernet interface.

[0028] Optionally, the cable is a flexible wire, the target detection part is the fingertips, wrists and legs of the target object, and the parameter acquisition host device is placed within a preset range of the target object or worn on the target object.

[0029] In a second aspect, the present application discloses a closed-loop deep brain stimulation control device, which is applied to a control system, wherein the control system includes a parameter acquisition host device, a target sensor, and a deep brain stimulation device; wherein the device includes:

[0030] a stimulation signal sending module, configured to control the deep brain electrical stimulation device to send a current electrical stimulation signal to a stimulation target point of a target subject;

[0031] a feedback signal acquisition module, configured to use the target sensor to acquire a current feedback signal generated by the target object after receiving the current electrical stimulation signal; wherein the current feedback signal is a kinematic and dynamic signal generated when the target object performs a Parkinson's movement paradigm, and the target sensor is located at a target detection site of the target object;

[0032] A stimulation signal control module is used to control the parameter acquisition host device connected to the target sensor to send the current feedback signal to the deep brain electrical stimulation device, so that the deep brain electrical stimulation device sends the next electrical stimulation signal to the stimulation target based on the current feedback signal.

[0033] In a third aspect, the present application discloses an electronic device, comprising:

[0034] Memory, used to store computer programs;

[0035] A processor is used to execute the computer program to implement the steps of the aforementioned closed-loop deep brain electrical stimulation control method.

[0036] In a fourth aspect, the present application discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the steps of the aforementioned closed-loop deep brain electrical stimulation control method are implemented.

[0037] The beneficial effects of the present application are: the present application is applied to a control system, the control system includes a parameter acquisition host device, a target sensor and a deep brain electrical stimulation device; wherein, the method includes: controlling the deep brain electrical stimulation device to send a current electrical stimulation signal to the stimulation target point of the target object; using the target sensor to collect a current feedback signal after the target object receives the current electrical stimulation signal; wherein, the current feedback signal is a kinematic and dynamic signal generated when the target object performs a Parkinson's movement paradigm, and the target sensor is located at the target detection part of the target object; controlling the parameter acquisition host device connected to the target sensor to send the current feedback signal to the deep brain electrical stimulation device, so that the deep brain electrical stimulation device sends the next electrical stimulation signal to the stimulation target point based on the current feedback signal. It can be seen that the control system of the present application includes a parameter acquisition host device, a target sensor and a deep brain stimulation device, that is, the parameter acquisition host device does not include a target sensor. The traditional parameter acquisition host device includes a sensor. Because the parameter acquisition host device is large in size, it cannot be placed at the target detection site to be detected. The present application separates the target sensor from the parameter acquisition host device. The target sensor is smaller in size, so the target sensor can be flexibly located at the target detection site of the target object; further, the deep brain stimulation device sends a current electrical stimulation signal to the stimulation target point of the target object, and uses the target sensor to collect the kinematic and dynamic signals generated by the target object after receiving the current electrical stimulation signal and performing the Parkinson's movement paradigm, that is, collects the current feedback signal, and then controls the parameter acquisition host device connected to the target sensor to send the current feedback signal to the deep brain stimulation device. Then, the deep brain stimulation device can send the next electrical stimulation signal to the stimulation target point based on the current feedback signal. That is, the deep brain stimulation device adjusts the stimulation signal according to the current feedback signal, thereby sending the next electrical stimulation signal to the stimulation target point. In this way, a more scientific deep brain stimulation control is achieved, and there is no need for the doctor to make subjective judgments to control the stimulation signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without any creative work.

[0039] Figure 1 This is a flow chart of a closed-loop deep brain stimulation control method disclosed in this application;

[0040] Figure 2 This is a schematic diagram of a specific sensor and host device connection disclosed in this application;

[0041] Figure 3 This is a schematic diagram of a specific target sensor placement disclosed in this application;

[0042] Figure 4 This is a schematic diagram of the internal connections of a specific control system disclosed in this application;

[0043] Figure 5 A specific closed-loop communication schematic diagram disclosed in this application;

[0044] Figure 6 This is a schematic structural diagram of a closed-loop deep brain electrical stimulation control device disclosed in this application;

[0045] Figure 7 This is a structural diagram of an electronic device disclosed in this application. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0047] Parkinson's disease patients may experience symptoms such as tremors, muscle rigidity, and bradykinesia. These symptoms can be treated with DBS. DBS stimulates the brain with microcurrents, altering the permeability and ion concentration of nerve cell membranes, thereby affecting cell function. Specifically, the electrical stimulation pulses inhibit brain cell activity while stimulating them, reducing the amount of neurotransmitters and reducing the breakdown of dopamine, thereby effectively controlling the disease. Parkinson's disease patients often experience limb movement disorders. Patient assessments using tests such as finger pointing, fist clenching, and wrist rotation are routinely used during outpatient follow-up and intraoperative follow-up. Currently, wearable devices that record movement data, such as watches and bracelets, are not flexible enough to be worn on suitable monitoring sites, such as fingers. Therefore, assessment of finger movements like finger pointing and fist clenching is impossible. Therefore, doctors currently control the stimulation signals delivered to the brain by deep brain stimulation devices based on their subjective judgment. Conventional physician assessments rely to a certain extent on their experience and subjective judgment, making the control of the stimulation signals from deep brain stimulation devices highly subjective and potentially inconsistent with the patient's needs.

[0048] To this end, this application provides a closed-loop deep brain electrical stimulation control solution to achieve more scientific deep brain electrical stimulation control.

[0049] See also Figure 1As shown, the embodiment of the present application discloses a closed-loop deep brain electrical stimulation control method, which is applied to a control system, wherein the control system includes a parameter acquisition host device, a target sensor, and a deep brain electrical stimulation device; wherein the method includes:

[0050] Step S11: controlling the deep brain electrical stimulation device to send a current electrical stimulation signal to the stimulation target point of the target object.

[0051] A stimulation target is set in the target subject's brain, and the electrodes of the deep brain stimulation device contact the stimulation target. High-frequency electrical stimulation is delivered through the electrodes to regulate abnormal neural activity in the target subject's brain, so that the motor control loop or disordered neurotransmitters can be restored to a relatively normal functional state, thereby improving Parkinson's-related symptoms such as tremor, rigidity and bradykinesia, thereby alleviating the patient's movement disorder symptoms and improving their quality of life.

[0052] Currently, it is necessary to rely on doctors to determine the size, range, position, etc. of the electrical stimulation signal emitted by the deep brain stimulation device, which is subjective. In addition, during the entire process of the deep brain stimulation device emitting the electrical stimulation signal, the doctor cannot dynamically and adaptively adjust the signal, and unreasonable treatment may occur later. However, this embodiment can dynamically and adaptively adjust the electrical stimulation signal, that is, to regulate the next electrical stimulation signal according to the current electrical stimulation signal, so first control the deep brain stimulation device to send the current electrical stimulation signal to the stimulation target of the target object, and the current electrical stimulation signal can be the initial electrical stimulation signal.

[0053] In this embodiment, the target sensor is connected to the parameter acquisition host device via a cable, and the parameter acquisition host device includes a controller, a local storage, an external synchronization interface, and a sensor interface. Figure 2 A specific schematic diagram of connecting a sensor and a host device is shown, in which the target sensor is connected to the parameter acquisition host device via a cable. The parameter acquisition host device does not include the target sensor, but rather includes a controller, local storage, an external synchronization interface, and a sensor interface. It can be understood that the parameter acquisition host device also includes a power supply, which is used to power the target sensor and the parameter acquisition host device. That is to say, compared with the traditional parameter acquisition host device that includes a sensor, this embodiment separates the target sensor from the parameter acquisition host device. On the one hand, the target sensor can be miniaturized, and on the other hand, the parameter acquisition host device can be placed near the patient or worn on the patient. In this way, the control system has fewer restrictions on the activities of the target object.

[0054] Step S12: using the target sensor to collect a current feedback signal after the target object receives the current electrical stimulation signal; wherein, the current feedback signal is a kinematic and dynamic signal generated when the target object performs a Parkinson's movement paradigm, and the target sensor is located at a target detection site of the target object.

[0055] The target subject receives the current electrical stimulation signal and executes the Parkinson's movement paradigm. The movement paradigm of Parkinson's disease mainly involves rehabilitation training movements for symptoms such as bradykinesia, muscle stiffness, and postural balance disorders. It mainly includes neck and trunk activities, upper limb and shoulder exercises, lower limb and balance training, and facial movement exercises. When executing the movement paradigm, the target subject's fingers need to bend, straighten, and clench a fist, the wrist needs to rotate, and the legs need to bend and straighten.

[0056] In this embodiment, the cable is a flexible wire, the target detection part is the fingertips, wrists and legs of the target object, and the parameter acquisition host device is placed within a preset range of the target object or worn on the target object. After the target sensor is separated from the parameter acquisition host device, the target sensor is very small and thin, so it can be flexibly worn or attached to various target detection parts, such as the fingertips, wrists, legs, etc. of the target object. Figure 3 A specific target sensor placement diagram is shown. In order to obtain the information of the target object more accurately, the target sensor ( Figure 3 The target sensor is worn on the end of the index finger and can be used to test patients flexibly and conveniently. The target sensor does not affect or restrict the patient's movement paradigm. The target sensor can be connected to the parameter acquisition host device ( Figure 3 The length of the flexible wire can be set according to the actual situation.

[0057] When the target object receives the current electrical stimulation signal and performs the Parkinson's movement paradigm, the target sensor is used to collect the current feedback signal after the target object receives the current electrical stimulation signal. The current feedback signal is the kinematic and dynamic signal generated when the target object performs the Parkinson's movement paradigm, such as finger movement trajectory, movement frequency and amplitude, movement completion time, muscle tension (myotonia) data, micro-tremor signals, multi-joint coordination, movement stability, etc. The current feedback signal can not only reflect the movement status of the target object, but also reflect whether the current electrical stimulation signal is suitable for the target object.

[0058] Step S13: Control the parameter acquisition host device connected to the target sensor to send the current feedback signal to the deep brain stimulation device, so that the deep brain stimulation device sends the next electrical stimulation signal to the stimulation target based on the current feedback signal.

[0059] The target sensor is connected to the parameter acquisition host device. The target sensor sends the current feedback signal to the parameter acquisition host device, and controls the parameter acquisition host device to send the current feedback signal to the deep brain stimulation device. In this way, the deep brain stimulation device can send the next stimulation signal to the stimulation target based on the current feedback signal, thereby realizing closed-loop deep brain stimulation control.

[0060] In this embodiment, the parameter acquisition host device connected to the target sensor is controlled to send the current feedback signal to the deep brain stimulation device, including: the parameter acquisition host device receives the current feedback signal through the sensor interface and saves the current feedback signal to the local storage; the controller sends the current feedback signal in the local storage to the deep brain stimulation device through the external synchronization interface.

[0061] The parameter acquisition host device includes a controller, local storage, an external synchronization interface and a sensor interface. The sensor interface is used to receive the current feedback signal, the local storage is used to save the current feedback signal, and the controller is used to control the external synchronization interface to send the current feedback signal to the deep brain stimulation device. The parameter acquisition host device is separated from the target sensor. The parameter acquisition host device can be fixed to the user's arm with a strap or placed in a clothes pocket or placed on a stable surface.

[0062] In this embodiment, the control system further includes a signal regulator. Figure 4 The schematic diagram of the internal connection of a specific control system is shown. The control system includes not only a parameter acquisition host device ( Figure 4 Middle yellow part), target sensor ( Figure 4 The deep brain stimulation device also includes a signal conditioner, which can be a central control computer. The deep brain stimulation device sends a signal to the stimulation target ( Figure 4 The green part in the middle) sends an electrical stimulation signal.

[0063] In this embodiment, the controller sends the current feedback signal in the local storage to the deep brain stimulation device through the external synchronization interface, including: the controller sends the current feedback signal in the local storage to the signal regulator through the external synchronization interface, so that the signal regulator processes the current feedback signal to send the obtained processed signal and the current feedback signal to the deep brain stimulation device.

[0064] A signal conditioner can also be set between the parameter acquisition host device and the deep brain electrical stimulation device. The signal conditioner is used to process the current feedback signal to send the obtained processed signal and the current feedback signal to the deep brain electrical stimulation device, so that the deep brain electrical stimulation device can determine the next electrical stimulation signal based on the processed signal and the current feedback signal.

[0065] In this embodiment, the signal conditioner processes the current feedback signal to send the obtained processed signal and the current feedback signal to the deep brain stimulation device, including: the signal conditioner filters the current feedback signal based on a preset frequency band to obtain a filtered signal, and uses a sliding window statistical method to eliminate abnormal data points in the filtered signal to obtain a eliminated signal; extracts motion features in the eliminated signal; wherein the motion features include tremor-related features, bradykinesia-related features, and muscle rigidity-related features; determines the target feature conversion logic from each preset feature conversion logic; wherein each preset feature conversion logic includes a conversion logic based on threshold matching and a conversion logic based on machine learning; uses the target feature conversion logic to quantize the motion features to obtain a processed signal, and sends the processed signal and the current feedback signal to the deep brain stimulation device.

[0066] There may be interference signals or abnormal signals in the current feedback signal, so the signal conditioner filters the current feedback signal based on the preset frequency band to obtain a filtered signal. The interference signal is filtered out of the filtered signal, and then the sliding window statistics method is used to eliminate abnormal data points in the filtered signal to obtain a eliminated signal, thereby filtering out the abnormal values. Further, the motion features in the eliminated signal are extracted, that is, tremor-related features, bradykinesia-related features, and muscle rigidity-related features that can reflect the strength of Parkinson's symptoms of the target object are extracted, and then the target feature conversion logic is determined from each preset feature conversion logic, that is, the appropriate conversion logic is selected as the target feature conversion logic from the conversion logic based on threshold matching and the conversion logic based on machine learning, wherein the conversion logic based on threshold matching refers to quantitative processing based on the matching relationship between each preset threshold and the motion feature, such as motion feature. If the sign is greater than the second preset threshold but less than the third preset threshold, the processed signal characterizes the target object's Parkinson's symptoms as level two. The machine learning-based conversion logic refers to pre-training the deep learning model with historical data, and then inputting the motion features into the trained model. The model can output the target object's Parkinson's symptom level. The higher the level, the higher the degree of Parkinson's disease in the target object and the more serious the condition. In other words, the processed signal can quantify the severity of the target object's Parkinson's disease, making the target object's condition more intuitive and accurately represented. Then the next electrical stimulation signal determined by the deep brain stimulation device based on the processed signal and the current feedback signal is also more accurate and reasonable. For example, the processed signal characterizes that the target object's Parkinson's symptoms are more severe, and the current feedback signal indicates that the target object has a smaller response to the current electrical stimulation signal, then the deep brain stimulation device can increase the intensity of the next electrical stimulation signal.

[0067] Furthermore, the controller can also send all feedback signals stored in the local storage to the signal conditioner, and the signal conditioner draws a trend curve based on each feedback signal. The trend curve can reflect the patient's response pattern to the electrical stimulation signal, and adjusts the processed signal according to the trend curve to obtain an adjusted signal. Then, the processed signal, the adjusted signal and the current feedback signal are all sent to the deep brain stimulation device, so that the deep brain stimulation device adjusts the current electrical stimulation signal according to the processed signal, the adjusted signal and the current feedback signal to obtain the next electrical stimulation signal. In this way, the progressive deterioration or improvement trend of Parkinson's symptoms can be identified through each feedback signal, rather than relying solely on instantaneous signals (that is, not only relying on the current feedback signal). By combining long-term trends and instantaneous states, "prediction + response" dual-mode control is realized, thereby improving the accuracy and reliability of electrical stimulation signal control.

[0068] In this embodiment, the deep brain electrical stimulation device sends the next electrical stimulation signal to the stimulation target based on the current feedback signal, including: the deep brain electrical stimulation device determines the target stimulation signal adjustment mode according to the processed signal and the current feedback signal, and adjusts the current stimulation signal according to the target stimulation signal adjustment mode to obtain the next electrical stimulation signal, and then sends the next electrical stimulation signal to the stimulation target; wherein, the target stimulation signal adjustment mode includes any one or more adjustment modes of stimulation position adjustment mode, stimulation intensity adjustment mode, stimulation range adjustment mode, stimulation direction adjustment mode and stimulation shape adjustment mode.

[0069] When the deep brain stimulation device adjusts the next electrical stimulation signal according to the processed signal and the current feedback signal, it determines the target stimulation signal adjustment mode and selects one or more appropriate modes from the stimulation position adjustment mode, stimulation intensity adjustment mode, stimulation range adjustment mode, stimulation direction adjustment mode and stimulation shape adjustment mode as the target stimulation signal adjustment mode. For example, if the electrical stimulation direction and intensity need to be adjusted, then the stimulation intensity adjustment mode and the stimulation direction adjustment mode are the target stimulation signal adjustment modes. For example, if the electrical stimulation range and shape need to be adjusted, then the stimulation range adjustment mode and the stimulation shape adjustment mode are the target stimulation signal adjustment modes. In other words, selecting the target stimulation signal adjustment mode is to determine which attributes of the electrical stimulation signal need to be adjusted. After determining the attributes that need to be adjusted, the target values ​​of each attribute are determined, that is, the current stimulation signal is adjusted according to the target stimulation signal adjustment mode to obtain the next electrical stimulation signal. In this way, the next electrical stimulation signal is sent to the stimulation target.

[0070] In this embodiment, the controller sends the current feedback signal in the local storage to the signal conditioner via the external synchronization interface, including: the controller sends the current feedback signal in the local storage to the signal conditioner via the external synchronization interface based on wireless transmission. Figure 4 As shown, the controller can send the current feedback signal in the local storage to the signal conditioner based on a wireless transmission method and through an external synchronization interface. Specifically, the current feedback signal can be sent to the signal conditioner in the form of Wi-Fi.

[0071] In this embodiment, the signal regulator processes the current feedback signal to send the obtained processed signal and the current feedback signal to the deep brain stimulation device, including: the signal regulator processes the current feedback signal to obtain a processed signal, and sends the processed signal and the current feedback signal to the deep brain stimulation device based on a wireless transmission method or an Ethernet interface.

[0072] After the signal conditioner processes the current feedback signal, it obtains a processed signal. If the signal conditioner and the deep brain stimulation device are connected wirelessly, the signal conditioner sends the processed signal and the current feedback signal to the deep brain stimulation device based on wireless transmission. If the signal conditioner and the deep brain stimulation device are connected by wire, the signal conditioner can send the processed signal and the current feedback signal to the deep brain stimulation device based on the Ethernet interface. Furthermore, if there is a problem with the communication link between the signal conditioner and the deep brain stimulation device, that is, the processed signal and the current feedback signal cannot be sent to the deep brain stimulation device wirelessly or by wire, then the doctor can manually adjust to the next stimulation signal to be sent by the deep brain stimulation device based on the processed signal and the current feedback signal.

[0073] The beneficial effects of the present application are: the present application is applied to a control system, the control system includes a parameter acquisition host device, a target sensor and a deep brain electrical stimulation device; wherein, the method includes: controlling the deep brain electrical stimulation device to send a current electrical stimulation signal to the stimulation target point of the target object; using the target sensor to collect a current feedback signal after the target object receives the current electrical stimulation signal; wherein, the current feedback signal is a kinematic and dynamic signal generated when the target object performs a Parkinson's movement paradigm, and the target sensor is located at the target detection part of the target object; controlling the parameter acquisition host device connected to the target sensor to send the current feedback signal to the deep brain electrical stimulation device, so that the deep brain electrical stimulation device sends the next electrical stimulation signal to the stimulation target point based on the current feedback signal. It can be seen that the control system of the present application includes a parameter acquisition host device, a target sensor and a deep brain stimulation device, that is, the parameter acquisition host device does not include a target sensor. The traditional parameter acquisition host device includes a sensor. Because the parameter acquisition host device is large in size, it cannot be placed at the target detection site to be detected. The present application separates the target sensor from the parameter acquisition host device. The target sensor is smaller in size, so the target sensor can be flexibly located at the target detection site of the target object; further, the deep brain stimulation device sends a current electrical stimulation signal to the stimulation target point of the target object, and uses the target sensor to collect the kinematic and dynamic signals generated by the target object after receiving the current electrical stimulation signal and performing the Parkinson's movement paradigm, that is, collects the current feedback signal, and then controls the parameter acquisition host device connected to the target sensor to send the current feedback signal to the deep brain stimulation device. Then, the deep brain stimulation device can send the next electrical stimulation signal to the stimulation target point based on the current feedback signal. That is, the deep brain stimulation device adjusts the stimulation signal according to the current feedback signal, thereby sending the next electrical stimulation signal to the stimulation target point. In this way, a more scientific deep brain stimulation control is achieved, and there is no need for the doctor to make subjective judgments to control the stimulation signal.

[0074] Below is Figure 5Taking a specific closed-loop communication schematic diagram shown as an example, the present application is described accordingly. The control system includes a parameter acquisition host device, a target sensor, a deep brain electrical stimulation device and a signal regulator, wherein the deep brain electrical stimulation device sends a current electrical stimulation signal to the stimulation target of the target object, and the target sensor is connected to the parameter acquisition host device through a flexible wire. The target sensor is small and very thin, so it can be flexibly worn alone or fixed to the target detection part in the form of an adhesive, such as the end of the finger, wrist and leg. The target sensor collects the current feedback signal after the target object receives the current electrical stimulation signal. The parameter acquisition host device includes a controller, local storage, an external synchronization interface and a sensor interface. The parameter acquisition host device is used to receive the current feedback signal collected by the target sensor and send the current feedback signal to the signal regulator. The signal regulator receives and processes the current feedback signal sent by the parameter acquisition host device, and then sends the processed signal and the current feedback signal to the deep brain electrical stimulation device, thereby realizing closed-loop control. The specific process is as follows:

[0075] 1) Control the deep brain stimulation device to send the current electrical stimulation signal to the stimulation target of the target subject.

[0076] 2) After the target object receives the current electrical stimulation signal, the target sensor is used to collect the kinematic and dynamic signals generated when the target object performs the Parkinson's movement paradigm to obtain the current feedback signal.

[0077] 3) The parameter acquisition host device receives the current feedback signal through the sensor interface and saves the current feedback signal to local storage, such as an SD (Memory Card). Furthermore, the controller sends the current feedback signal in the local storage to the signal conditioner through an external synchronization interface based on wireless transmission.

[0078] 4) The signal conditioner processes the current feedback signal to obtain a processed signal, and sends the processed signal and the current feedback signal to the deep brain stimulation device based on wireless transmission or an Ethernet interface.

[0079] 5) The deep brain stimulation device determines the target stimulation signal adjustment mode based on the processed signal and the current feedback signal, adjusts the current stimulation signal according to the target stimulation signal adjustment mode, obtains the next stimulation signal, and then sends the next stimulation signal to the stimulation target.

[0080] The above process is repeated continuously. It can be understood that the next electrical stimulation signal may be the same as or different from the current electrical stimulation signal. The electrical stimulation signal needs to be regulated according to the processed signal and the current feedback signal.

[0081] See also Figure 6As shown, the embodiment of the present application discloses a closed-loop deep brain electrical stimulation control device, which is applied to a control system, wherein the control system includes a parameter acquisition host device, a target sensor, and a deep brain electrical stimulation device; wherein the device includes:

[0082] A stimulation signal sending module 11 is used to control the deep brain electrical stimulation device to send a current electrical stimulation signal to the stimulation target point of the target object;

[0083] a feedback signal acquisition module 12, configured to use the target sensor to acquire a current feedback signal generated by the target object after receiving the current electrical stimulation signal; wherein the current feedback signal is a kinematic and dynamic signal generated when the target object performs a Parkinson's movement paradigm, and the target sensor is located at a target detection site of the target object;

[0084] The stimulation signal control module 13 is used to control the parameter acquisition host device connected to the target sensor to send the current feedback signal to the deep brain electrical stimulation device, so that the deep brain electrical stimulation device sends the next electrical stimulation signal to the stimulation target based on the current feedback signal.

[0085] The beneficial effects of the present application are: the present application is applied to a control system, the control system includes a parameter acquisition host device, a target sensor and a deep brain electrical stimulation device; wherein, the method includes: controlling the deep brain electrical stimulation device to send a current electrical stimulation signal to the stimulation target point of the target object; using the target sensor to collect a current feedback signal after the target object receives the current electrical stimulation signal; wherein, the current feedback signal is a kinematic and dynamic signal generated when the target object performs a Parkinson's movement paradigm, and the target sensor is located at the target detection part of the target object; controlling the parameter acquisition host device connected to the target sensor to send the current feedback signal to the deep brain electrical stimulation device, so that the deep brain electrical stimulation device sends the next electrical stimulation signal to the stimulation target point based on the current feedback signal. It can be seen that the control system of the present application includes a parameter acquisition host device, a target sensor and a deep brain stimulation device, that is, the parameter acquisition host device does not include a target sensor. The traditional parameter acquisition host device includes a sensor. Because the parameter acquisition host device is large in size, it cannot be placed at the target detection site to be detected. The present application separates the target sensor from the parameter acquisition host device. The target sensor is smaller in size, so the target sensor can be flexibly located at the target detection site of the target object; further, the deep brain stimulation device sends a current electrical stimulation signal to the stimulation target point of the target object, and uses the target sensor to collect the kinematic and dynamic signals generated by the target object after receiving the current electrical stimulation signal and performing the Parkinson's movement paradigm, that is, collects the current feedback signal, and then controls the parameter acquisition host device connected to the target sensor to send the current feedback signal to the deep brain stimulation device. Then, the deep brain stimulation device can send the next electrical stimulation signal to the stimulation target point based on the current feedback signal. That is, the deep brain stimulation device adjusts the stimulation signal according to the current feedback signal, thereby sending the next electrical stimulation signal to the stimulation target point. In this way, a more scientific deep brain stimulation control is achieved, and there is no need for the doctor to make subjective judgments to control the stimulation signal.

[0086] Furthermore, an embodiment of the present application also provides an electronic device. Figure 7 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content in the diagram should not be considered as any limitation to the scope of application of the present application.

[0087] Figure 7This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Specifically, the device may include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 is used to store a computer program, which is loaded and executed by the processor 21 to implement the relevant steps of the closed-loop deep brain stimulation control method performed by the electronic device disclosed in any of the aforementioned embodiments.

[0088] In this embodiment, the power supply 23 is used to provide operating voltage for various hardware devices on the electronic device; the communication interface 24 can create a data transmission channel between the electronic device and external devices. The communication protocol it follows is any communication protocol that can be applied to the technical solution of this application and is not specifically limited here; the input and output interface 25 is used to obtain external input data or output data to the outside world. Its specific interface type can be selected according to specific application needs and is not specifically limited here.

[0089] Among them, the processor 21 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 21 can be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 21 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 21 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 21 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0090] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or CD, etc. The resources stored thereon include an operating system 221, a computer program 222 and data 223, etc. The storage method can be temporary storage or permanent storage.

[0091] The operating system 221 is used to manage and control the hardware devices and computer programs 222 on the electronic device to enable the processor 21 to calculate and process the massive data 223 in the memory 22. It can be Windows, Unix, Linux, etc. In addition to including computer programs that can be used to implement the closed-loop deep brain stimulation control method performed by the electronic device disclosed in any of the aforementioned embodiments, the computer program 222 can further include computer programs that can be used to perform other specific tasks. In addition to data transmitted by external devices received by the electronic device, the data 223 can also include data collected by its own input and output interface 25.

[0092] Furthermore, this application discloses a computer-readable storage medium for storing a computer program; wherein, when executed by a processor, the computer program implements the aforementioned closed-loop deep brain stimulation control method. The specific steps of this method can be referred to the corresponding contents disclosed in the aforementioned embodiments and will not be repeated here.

[0093] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from the other embodiments. Reference can be made to the descriptions of the identical or similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple, and the relevant parts can be referred to the descriptions of the methods.

[0094] Professionals may further appreciate that the units and algorithmic steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application. The steps of the method or algorithm described in conjunction with the embodiments disclosed herein can be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module can be placed in random access memory (RAM), memory, read-only memory (ROM), electrically programmable EPROM (Erasable Programmable Read Only Memory), electrically erasable programmable EEPROM (Electrically Erasable Programmable read only memory), registers, hard disk, removable disk, CD-ROM (Compact Disc Read-Only Memory), or any other form of storage medium known in the technical field.

[0095] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or device comprising the element.

[0096] The above is a detailed introduction to the closed-loop deep brain electrical stimulation control method, device, equipment and medium provided by the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core ideas. At the same time, for those skilled in the art, according to the ideas of the present invention, there may be changes in the specific implementation methods and application scopes. In summary, the contents of this specification should not be understood as limiting the present invention.

Claims

1. A closed-loop deep brain electrical stimulation control method, characterized in that: Applied to a control system, the control system includes a parameter acquisition host device, a target sensor, and a deep brain stimulation device; wherein the method includes: Controlling the deep brain stimulation device to send a current electrical stimulation signal to a stimulation target point of the target subject; Using the target sensor to collect a current feedback signal after the target object receives the current electrical stimulation signal; wherein the current feedback signal is a kinematic and dynamic signal generated when the target object performs a Parkinson's movement paradigm, and the target sensor is located at a target detection site of the target object; Control the parameter acquisition host device connected to the target sensor to send the current feedback signal to the deep brain stimulation device, so that the deep brain stimulation device sends the next electrical stimulation signal to the stimulation target based on the current feedback signal.

2. The closed-loop deep brain stimulation control method according to claim 1, characterized in that: The target sensor is connected to the parameter acquisition host device via a cable, and the parameter acquisition host device includes a controller, a local storage, an external synchronization interface, and a sensor interface; Accordingly, controlling the parameter acquisition host device connected to the target sensor to send the current feedback signal to the deep brain stimulation device includes: The parameter acquisition host device receives the current feedback signal through the sensor interface and saves the current feedback signal to the local storage; The controller sends the current feedback signal in the local storage to the deep brain stimulation device through the external synchronization interface.

3. The closed-loop deep brain stimulation control method according to claim 2, characterized in that: The control system further includes a signal regulator; The controller sends the current feedback signal in the local storage to the deep brain stimulation device through the external synchronization interface, including: The controller sends the current feedback signal in the local storage to the signal regulator through the external synchronization interface, so that the signal regulator processes the current feedback signal and sends the obtained processed signal and the current feedback signal to the deep brain stimulation device.

4. The closed-loop deep brain electrical stimulation control method according to claim 3, characterized in that: The signal conditioner processes the current feedback signal to send the obtained processed signal and the current feedback signal to the deep brain stimulation device, comprising: The signal conditioner filters the current feedback signal based on a preset frequency band to obtain a filtered signal, and removes abnormal data points in the filtered signal using a sliding window statistical method to obtain a removed signal; Extracting motion features from the signal after elimination; wherein the motion features include tremor-related features, bradykinesia-related features, and myotonia-related features; Determining a target feature conversion logic from each preset feature conversion logic; wherein each of the preset feature conversion logics includes a conversion logic based on threshold matching and a conversion logic based on machine learning; The motion feature is quantized using the target feature conversion logic to obtain a processed signal, and the processed signal and the current feedback signal are sent to the deep brain stimulation device.

5. The closed-loop deep brain electrical stimulation control method according to claim 4, characterized in that: The deep brain electrical stimulation device sends a next electrical stimulation signal to the stimulation target based on the current feedback signal, comprising: The deep brain electrical stimulation device determines a target stimulation signal adjustment mode according to the processed signal and the current feedback signal, adjusts the current stimulation signal according to the target stimulation signal adjustment mode to obtain a next electrical stimulation signal, and then sends the next electrical stimulation signal to the stimulation target point; The target stimulation signal adjustment mode includes any one or more of a stimulation position adjustment mode, a stimulation intensity adjustment mode, a stimulation range adjustment mode, a stimulation direction adjustment mode, and a stimulation shape adjustment mode.

6. The closed-loop deep brain electrical stimulation control method according to claim 3, characterized in that: The controller sends the current feedback signal in the local storage to the signal conditioner through the external synchronization interface, including: The controller sends the current feedback signal in the local storage to the signal conditioner via the external synchronization interface based on a wireless transmission method; Accordingly, the signal conditioner processes the current feedback signal to send the obtained processed signal and the current feedback signal to the deep brain stimulation device, including: The signal conditioner processes the current feedback signal to obtain a processed signal, and sends the processed signal and the current feedback signal to the deep brain stimulation device based on a wireless transmission method or an Ethernet interface.

7. The closed-loop deep brain electrical stimulation control method according to any one of claims 2 to 6, characterized in that: The cable is a flexible wire, the target detection part is the fingertips, wrists and legs of the target object, and the parameter acquisition host device is placed within a preset range of the target object or worn on the target object.

8. A closed-loop deep brain electrical stimulation control device, characterized in that: Applied to a control system, the control system includes a parameter acquisition host device, a target sensor, and a deep brain stimulation device; wherein the device includes: a stimulation signal sending module, configured to control the deep brain electrical stimulation device to send a current electrical stimulation signal to a stimulation target point of a target subject; a feedback signal acquisition module, configured to use the target sensor to acquire a current feedback signal generated by the target object after receiving the current electrical stimulation signal; wherein the current feedback signal is a kinematic and dynamic signal generated when the target object performs a Parkinson's movement paradigm, and the target sensor is located at a target detection site of the target object; A stimulation signal control module is used to control the parameter acquisition host device connected to the target sensor to send the current feedback signal to the deep brain electrical stimulation device, so that the deep brain electrical stimulation device sends the next electrical stimulation signal to the stimulation target based on the current feedback signal.

9. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor is configured to execute the computer program to implement the steps of the closed-loop deep brain stimulation control method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that Used to store computer programs; wherein, when the computer program is executed by a processor, the steps of the closed-loop deep brain electrical stimulation control method according to any one of claims 1 to 7 are implemented.

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