Nerve regulation device and system

Abstract

The embodiment of the invention provides a nerve regulation and control device and system, and relates to the technical field of nerve regulation and control. The nerve regulation and control device comprises a stimulator which is used for being electrically connected with at least one deep electrode and at least one cortex electrode and is configured to obtain an electroencephalogram signal of a target area through at least one collection contact in response to the condition that a preset triggering condition is met, and current stimulation information is adjusted based on the electroencephalogram signal to obtain target stimulation information; the preset triggering condition comprises at least one of the following conditions: outputting the stimulation signal, a first preset time after outputting the stimulation signal, stopping outputting the stimulation signal, and a second preset time after stopping outputting the stimulation signal. According to the embodiment of the invention, the target stimulation information can be adaptively adjusted based on the electroencephalogram signal of the patient, the stimulation signal is output through the contact of the cortical electrode or the contact of the deep electrode and the contact of the cortical electrode, and the accuracy and the treatment effect of nerve regulation and control are improved.

Description

Technical Field

[0001] The present application relates to the technical field of neural regulation, and specifically, to a neural regulation device and system. Background Art

[0002] In the field of neuromodulation, low-frequency envelope waveform stimulation is an important technical means used to treat neurological diseases such as Parkinson's disease and epilepsy.

[0003] At present, the way to perform neuromodulation is generally to determine the stimulation information in advance, and then output a pulse signal to the target area of ​​the patient according to the stimulation information to perform neuromodulation. However, the patient's condition may change during the treatment process and after a certain treatment. The existing stimulation method cannot adjust the stimulation information according to the changes in the patient's condition, thereby reducing the accuracy of neuromodulation and the treatment effect. Summary of the invention

[0004] The embodiments of the present application provide a neuromodulatory device and system for solving the technical problem in the prior art that the accuracy of neuromodulation and the therapeutic effect are reduced due to the use of fixed stimulation information for stimulation.

[0005] In a first aspect, an embodiment of the present application provides a neural regulation device, comprising: A stimulator, for electrically connecting to at least one deep electrode and at least one cortical electrode, configured to acquire an EEG signal of a target area through at least one acquisition contact in response to a predetermined trigger condition being met, adjust current stimulation information based on the EEG signal to obtain target stimulation information; based on the target stimulation information, control at least two target contacts to output stimulation signals to form a target envelope waveform, so as to perform neural regulation on the target area; The predetermined trigger condition includes at least one of the following: outputting a stimulation signal, a first predetermined time after outputting the stimulation signal, stopping outputting the stimulation signal, and a second predetermined time after stopping outputting the stimulation signal; The acquisition contacts include contacts of cortical electrodes and / or contacts of depth electrodes; The target contacts include contacts of cortical electrodes, or contacts of deep electrodes and contacts of cortical electrodes, and the target stimulation information includes target contact information and stimulation parameter information corresponding to each target contact.

[0006] In a possible implementation, the target envelope waveform is formed by the stimulation signals output by each target contact being mutually restrained, and the frequencies of the stimulation signals output by each target contact are different.

[0007] In a possible implementation, the frequency of the target envelope waveform is 5 Hz to 20 kHz; and / or the amplitude of the target envelope waveform is 0 volts to 40 volts.

[0008] In a possible implementation, the amplitude, phase, and frequency of the target envelope waveform are determined based on the amplitude, phase, and frequency of the stimulation signal output by each target contact, respectively.

[0009] In a possible implementation, the stimulation parameter information includes at least one of the following: stimulation frequency, stimulation duration, amplitude, and a stimulation frequency difference between the stimulation frequency and an adjacent target contact point.

[0010] In one possible implementation, the stimulator includes: An acquisition module, configured to acquire an electroencephalogram signal of a target area through at least one acquisition contact in response to satisfying a predetermined trigger condition; A signal processing module is used to determine the distribution information of EEG activity based on the EEG signal, and to determine the target stimulation information based on the distribution information of EEG activity and the position information of each contact point; the distribution information of EEG activity is used to characterize the activity of EEG activity in the target area; The control module is used to control at least two target contacts to output stimulation signals to form a target envelope waveform based on the target stimulation information.

[0011] In a possible implementation, the neuromodulation device further includes at least one of the following: The acquisition module is specifically used to collect the EEG signal of the target area through at least one acquisition contact according to the set sampling parameter information; the sampling parameter information includes at least one of the following: sampling frequency, resolution; The signal processing module is specifically used to pre-process the EEG signal to obtain a processed EEG signal, and determine the EEG activity distribution information based on the processed EEG signal; the pre-processing includes filtering processing.

[0012] In a possible implementation, the signal processing module is specifically used to extract characteristic parameters of the EEG signal based on the EEG signal, and determine the EEG activity distribution information based on the characteristic parameters; the characteristic parameters include power spectrum density, phase information, and entropy information.

[0013] In a possible implementation, the signal processing module includes a back-propagation preview model, and the back-propagation preview model is used to: Based on the distribution information of EEG activities and the position information of each contact point, the stimulus information to be predicted in the target area is determined; Performing a first operation on the stimulus information to be predicted in the target area, and using the stimulus information to be predicted that passes the prediction as the target stimulus information; Among them, the first operation includes: obtaining a prediction result based on the stimulus information to be predicted; adjusting the stimulus information to be predicted based on the prediction result to obtain adjusted stimulus information; using the adjusted stimulus information as the stimulus information to be predicted until the prediction result meets the requirements and the prediction of the stimulus information to be predicted is passed.

[0014] In a possible implementation, the reverse prediction model is specifically used to: Based on the EEG activity distribution information, the target area is divided into at least two sub-areas and the EEG activity information of each sub-area is determined; the EEG activity information is used to characterize the activity of the EEG activity of the sub-area; Based on the EEG activity information of each sub-region and the position information of each contact point, the stimulus information to be predicted of each sub-region is determined; the stimulus information to be predicted of the target region includes the stimulus information to be predicted of each sub-region; The first operation is performed on the stimulus information to be predicted of each sub-region, and the stimulus information to be predicted of all sub-regions that has passed the prediction is used as the target stimulus information.

[0015] In a possible implementation, the EEG activity information includes an energy value, and the prediction result includes an energy change amount, where the energy change amount is a difference between an actual energy value of the sub-region and a predicted energy value; the actual energy value is obtained based on the EEG activity information determined based on the EEG activity distribution information, and the predicted energy value is obtained based on the prediction of the stimulus information to be predicted; The reverse prediction model is specifically used to: if the energy change amount of each sub-region is within a first predetermined range, then determine that the prediction result meets the requirements.

[0016] In a second aspect, an embodiment of the present application provides a neural regulation system, comprising: at least one deep electrode, at least one cortical electrode, and the neural regulation device of the first aspect; Each deep electrode is implanted in a target area of ​​the target subject, and each cortical electrode is attached to a position of the target subject corresponding to the target area; Each depth electrode and each cortical electrode includes at least one contact; Each contact is electrically connected to the stimulator. The contacts of the deep electrodes are used to collect EEG signals and / or output stimulation signals under the control of the stimulator, and the contacts of the cortical electrodes are used to collect EEG signals and / or output stimulation signals under the control of the stimulator.

[0017] The beneficial effects of the technical solution provided by the embodiment of the present application are: The stimulator of the embodiment of the present application can be electrically connected to at least one deep electrode and at least one cortical electrode, and under the triggering conditions of outputting a stimulation signal, a first predetermined time after outputting a stimulation signal, stopping outputting a stimulation signal, and a second predetermined time after stopping outputting a stimulation signal, the EEG signal of the target area is acquired through at least one acquisition contact, and then the current stimulation information is adjusted according to the EEG signal to obtain the target stimulation information, and then based on the target stimulation information, at least two target contacts are controlled to output stimulation signals to form a target envelope waveform to perform neural regulation on the target area. Therefore, the embodiment of the present application can adaptively adjust the target stimulation information based on the patient's EEG signal in application scenarios such as during patient treatment, when the treatment ends, and for a period of time after the treatment ends, and output stimulation signals through the contacts of the cortical electrodes, or the contacts of the deep electrodes and the contacts of the cortical electrodes, so that targeted treatment can be performed according to the patient's current condition, thereby improving the accuracy of neural regulation and the treatment effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in describing the embodiments of the present application are briefly introduced below.

[0019] Figure 1 A schematic diagram of the architecture of a neural regulation system provided in an embodiment of the present application; Figure 2 A schematic diagram of an application scenario in which a contact output stimulation signal of a deep electrode and a cortical electrode forms a target envelope waveform provided in an embodiment of the present application; Figure 3 A schematic diagram of the structure of a first stimulator provided in an embodiment of the present application; Figure 4 A schematic diagram of the structure of a second stimulator provided in an embodiment of the present application; Figure 5 A schematic diagram of a target envelope waveform provided in an embodiment of the present application.

[0020] Reference numerals: Neural regulatory system 1; 11-deep electrode, 110-first contact; 12-cortical electrode, 120-second contact; 13-neural regulation device, 130-stimulator, 131-acquisition module, 132-signal processing module; 1321-reverse rehearsal model, 133-control module. DETAILED DESCRIPTION

[0021] The embodiments of the present application are described below in conjunction with the drawings in the present application. It should be understood that the implementation methods described below in conjunction with the drawings are exemplary descriptions for explaining the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions of the embodiments of the present application.

[0022] It will be understood by those skilled in the art that, unless specifically stated, the singular forms "one", "said", and "the" used herein may also include plural forms. It should be further understood that the terms "including" and "comprising" used in the embodiments of the present application refer to that the corresponding features can be implemented as the presented features, information, data, steps, operations, elements and / or components, but do not exclude the implementation as other features, information, data, steps, operations, elements, components and / or combinations thereof supported by the technical field. It should be understood that when we say that an element is "connected" or "coupled" to another element, the one element may be directly connected or coupled to the other element, or it may refer to that the one element and the other element establish a connection relationship through an intermediate element. In addition, the "connection" or "coupling" used herein may include wireless connection or wireless coupling. The term "and / or" used herein indicates at least one of the items defined by the term, for example, "A and / or B" indicates that it is implemented as "A", or is implemented as "A", or is implemented as "A and B".

[0023] In related technologies, the human brain continuously emits weak bioelectric signals, which are called brain waves, or EEG signals, and are an intuitive reflection of brain activity. By monitoring and studying these weak electrical signals, we can understand the real-time physiological state of the brain. Brain diseases or brain tissue lesions can cause abnormal brain tissue discharges, especially epilepsy, which can cause strong abnormal brain discharges. Monitoring EEG signals can help doctors determine the type of disease and the location of the disease, providing valuable information for determining treatment plans. Brain monitoring technology can collect EEG signals, which helps decode brain functions. With the development of brain monitoring technology, it has also promoted the development of a series of high-tech technologies based on this, such as brain-computer interfaces and neural regulation.

[0024] However, the main problems of traditional neural regulation methods are as follows: 1. Since the existing neuroregulation is based on predetermined stimulation information, the stimulation parameters of the stimulation information are generally fixed and cannot be adjusted in real time according to the patient's condition, resulting in the stimulation being too strong or too weak, causing some side effects and failing to achieve the best therapeutic effect.

[0025] 2. Because the patient's condition is constantly changing, existing neuromodulation cannot accurately stimulate specific brain areas, which can easily lead to unnecessary side effects, such as overstimulation of healthy brain areas or failure to effectively stimulate diseased areas.

[0026] 3. The electrodes used in existing neuromodulation are relatively simple and often use simple electrode configurations, which cannot achieve synergistic effects between electrodes, resulting in limitations in the stimulation effect.

[0027] 4. Since existing neuromodulation generally adopts a single electrode configuration, the output stimulation waveform is relatively fixed and simple, and cannot be adaptively adjusted according to the changes in the activity of the patient's EEG signals, thereby limiting the flexibility and adaptability of the stimulation method and reducing the accuracy and treatment effect of neuromodulation.

[0028] The neuromodulatory device and system provided in this application are intended to solve the above technical problems of the prior art.

[0029] The following is a detailed description of the technical solution of the present application and how the technical solution of the present application solves the above technical problems with specific embodiments. It should be noted that the following implementations can refer to, draw on or combine with each other, and the same terms, similar features and similar implementation steps in different implementations will not be described repeatedly.

[0030] See also Figure 1 As shown, the present embodiment provides a schematic diagram of the framework of a neural regulation system 1. The neural regulation system 1 includes: at least one deep electrode 11, at least one cortical electrode 12, and a neural regulation device 13 of the present embodiment.

[0031] Each deep electrode 11 is implanted in a target area of ​​a target object, and each cortical electrode 12 is attached to a position of the target object corresponding to the target area.

[0032] Each deep electrode 11 and each cortical electrode 12 comprises at least one contact.

[0033] Each contact is electrically connected to the stimulator 130 . The contacts of the deep electrode 11 are used to collect EEG signals and / or output stimulation signals under the control of the stimulator 130 . The contacts of the cortical electrode 12 are used to collect EEG signals and / or output stimulation signals under the control of the stimulator 130 .

[0034] Optionally, the deep electrode 11 includes a catheter, a contact and a wire, wherein the contact is sleeved on the outside of the catheter, and the wire is located on the inside of the catheter and contacts the contact after passing through a hole on the catheter.

[0035] Optionally, the cortical electrode 12 can be set inside the patient's skull (e.g., outside the dura mater or inside the dura mater) or outside the skull (e.g., under the scalp), and the contacts of the cortical electrode 12 can output stimulation signals alone or in conjunction with the contacts of the deep electrode 11 to output stimulation signals, thereby forming a target envelope waveform.

[0036] Optionally, the neuroregulatory system 1 of the embodiment of the present application may be composed of at least one deep electrode 11 and at least one cortical electrode 12. Through the mutual cooperation of the deep electrode 11 and the cortical electrode 12, the flexibility and adaptability of neuroregulation are improved.

[0037] See also Figure 2 As shown, the embodiment of the present application provides a schematic diagram of an application scenario in which the contact output stimulation signals of the deep electrode 11 and the cortical electrode 12 form a target envelope waveform. Figure 2 As shown, the deep electrode 11 is implanted in the brain of the target object, the contact point of the deep electrode 11 is the first contact point 110, and the cortical electrode 12 is attached to the position of the target object corresponding to the target area. The contact point of the cortical electrode 12 is the second contact point 120. At least two first contacts 110 and at least two second contacts 120 output stimulation signals to form a target envelope waveform. The target envelope waveform can be matched with the patient's lesion for treatment, thereby improving the effectiveness and accuracy of the treatment.

[0038] See also Figure 2 As shown, each first contact 110 and second contact 120 can act as a stimulation source when outputting a stimulation signal. The target envelope waveform is a waveform formed by the combination of multiple different stimulation sources. The frequency, amplitude, phase and waveform of the stimulation signal output by each stimulation source can be different.

[0039] Optionally, the deep electrode 11 may be provided with a plurality of annular first contacts 110, and the plurality of first contacts 110 are spaced apart on the deep electrode 11. In some embodiments, a portion of the first contacts 110 may be used to collect EEG signals, and a portion of the first contacts 110 may be used to output stimulation signals; in other embodiments, the first contacts 110 may collect EEG signals and output stimulation signals, and the same first contact 110 may output stimulation signals and collect EEG signals at different times.

[0040] Optionally, the deep electrode 11 is implanted in a target area of ​​a target object, the target object being a patient, and the target area needs to cover an area of ​​the patient that needs to be treated so that the patient can be treated. The target area is determined in advance based on the patient's condition.

[0041] In the embodiment of the present application, the deep electrode 11 can be implanted into a target area (the target area refers to a specific location in a specific area that is actually selected and accurately determined by a doctor for placing electrodes or pacemakers to send electrical stimulation).

[0042] The embodiment of the present application may include at least two deep electrodes 11 and at least one cortical electrode 12. Each deep electrode 11 may be provided with a plurality of first contacts 110, and each cortical electrode 12 may be provided with a plurality of second contacts 120, so as to achieve synergistic effect between the electrodes and solve the technical problem of limitation of stimulation effect.

[0043] The neuromodulator 13 of the embodiment of the present application includes: a stimulator 130. The stimulator 130 is used to be electrically connected to at least one deep electrode 11 and at least one cortical electrode 12. The stimulator 130 is configured to obtain an electroencephalogram signal of a target area through at least one acquisition contact in response to a predetermined trigger condition being met, adjust the current stimulation information based on the electroencephalogram signal, and obtain target stimulation information; based on the target stimulation information, control at least two target contacts to output stimulation signals to form a target envelope waveform, so as to perform neuromodulation on the target area.

[0044] The predetermined trigger condition includes at least one of the following: outputting a stimulation signal, a first predetermined time after outputting the stimulation signal, stopping outputting the stimulation signal, and a second predetermined time after stopping outputting the stimulation signal.

[0045] The acquisition contacts include contacts of the cortical electrode 12 and / or contacts of the deep electrode 11 .

[0046] The target contacts include contacts of the cortical electrode 12, or contacts of the deep electrode 11 and contacts of the cortical electrode 12, and the target stimulation information includes target contact information and stimulation parameter information corresponding to each target contact.

[0047] The stimulator 130 of the embodiment of the present application can be electrically connected to at least one deep electrode 11 and at least one cortical electrode 12, and can obtain the EEG signal of the target area through at least one acquisition contact under trigger conditions such as outputting a stimulation signal, a first predetermined time after outputting the stimulation signal, stopping outputting the stimulation signal, and a second predetermined time after stopping outputting the stimulation signal, and then adjust the current stimulation information according to the EEG signal to obtain target stimulation information, and then, based on the target stimulation information, control at least two target contacts to output stimulation signals to form a target envelope waveform to perform neural regulation on the target area.

[0048] Therefore, the embodiments of the present application can adaptively adjust the target stimulation information based on the patient's EEG signals in application scenarios such as during patient treatment, at the end of the treatment, and for a period of time after the end of the treatment, and output stimulation signals through the contacts of the cortical electrode 12, or the contacts of the deep electrode 11 and the contacts of the cortical electrode 12, so that targeted treatment can be performed according to the patient's current condition, thereby improving the accuracy of neural regulation and the treatment effect.

[0049] Optionally, the first scheduled time and the second scheduled time can be the same or different, for example: 2 minutes, 15 minutes, 30 minutes, etc., and the EEG signal can be obtained after a certain period of time or a period of time after the patient's treatment. The EEG signal obtained in this way is relatively stable and can accurately reflect the patient's current actual condition. The first scheduled time and the second scheduled time listed in the embodiment of the present application are only examples. In actual applications, the specific times of the first scheduled time and the second scheduled time can be adaptively adjusted according to actual conditions.

[0050] Optionally, the collection contacts can be determined based on the target area. The deep electrode 11 can collect EEG signals from a deeper area, and the cortical electrode 12 can collect EEG signals from a shallower area. The collection contacts can be the contacts of the cortical electrode 12 or the contacts of the deep electrode 11, or the contacts of the cortical electrode 12 and the contacts of the deep electrode 11, so that the EEG signals collected by the contacts of the cortical electrode 12 and the contacts of the deep electrode 11 can be combined for comprehensive judgment.

[0051] Optionally, the target stimulation information includes target contact information and stimulation parameter information corresponding to each target contact, so as to determine which contacts output stimulation signals and the stimulation parameters of the stimulation signals output by each contact, and then form the required target envelope waveform through the synergistic effect between the target contacts to achieve neural regulation of the target area.

[0052] This application can determine the specific area where EEG signals need to be collected based on the patient's condition and treatment needs. The specific area refers to the brain area selected by the doctor based on the patient's specific condition and surgical purpose, where electrodes or pacemakers need to be implanted to send electrical stimulation, and the specific area is used as the target area.

[0053] The embodiment of the present application can obtain EEG signals under at least one of the following conditions: outputting a stimulation signal, a first predetermined time after outputting a stimulation signal, stopping outputting the stimulation signal, and a second predetermined time after stopping outputting the stimulation signal. Thus, in various situations such as during treatment or after treatment is stopped, the changes in the patient's EEG signals can be monitored in real time according to actual needs. The target stimulation information can be determined based on the patient's current EEG signal to form a target envelope waveform, thereby providing targeted treatment for the patient's current brain condition.

[0054] Existing stimulation methods ignore the dynamic changes of the patient's current EEG signals during treatment, resulting in the inability to optimize the effectiveness of the stimulation in real time. The embodiments of the present application can optimize the effectiveness of the stimulation in real time.

[0055] Further research has found that the stimulation parameters of the low-frequency envelope waveform in the existing technology are fixed and cannot be adjusted in real time according to the actual activity of the patient's EEG signal. At the same time, since the stimulation information cannot be adjusted according to the patient's real-time situation, it is easy to cause insufficient stimulation accuracy and fail to accurately stimulate specific brain areas, causing unnecessary side effects. At the same time, the existing single electrode method cannot achieve accurate stimulation or inhibition of the entire neural pathway, resulting in technical problems such as limited treatment effects, and cannot achieve synergy between electrodes, further leading to the problem of limited stimulation effects.

[0056] Moreover, the existing system cannot make adaptive adjustments according to changes in the activity of EEG signals, which limits the flexibility and adaptability of the stimulation method, and cannot form an effective, fully covered, and accurate low-frequency envelope waveform stimulation network in the entire target area, and cannot achieve technical problems such as overall regulation of the entire target area. The neuroregulatory device 13 and neuroregulatory system 1 provided in the embodiments of the present application can overcome the above problems.

[0057] In some embodiments, the target envelope waveform is formed by the stimulation signals output by each target contact being mutually coordinated and constrained, and the frequencies of the stimulation signals output by each target contact are different.

[0058] Optionally, the interaction between the target contacts can form a target envelope waveform in the target area, covering the entire target area and achieving full-pathway neural stimulation or inhibition.

[0059] In some embodiments, the frequency of the target envelope waveform is 5 Hz to 20 kHz; and / or the amplitude of the target envelope waveform is 0 volts to 40 volts.

[0060] The stimulation in the embodiment of the present application includes DBS (Deep Brain Stimulation). The stimulation frequency range of DBS for treating epilepsy is relatively wide. According to different studies and clinical practices, the stimulation frequency can range from 8 Hz to 250 Hz. At the same time, after research in the embodiment of the present application, low-frequency stimulation is also used for treatment, such as 5 Hz low-frequency stimulation.

[0061] In practical applications, the stimulation frequency range can be 5Hz-8Hz, 8Hz-25Hz, 25Hz-50Hz, 50Hz-100Hz, 100Hz-170Hz, 170Hz-250Hz, 250Hz-5KHz, 5KHz-10KHz, and 10KHz-20KHz.

[0062] Optionally, the frequency ranges listed in the embodiments of the present application all include endpoint values, and the listed frequency ranges are only used as an example. In actual applications, the frequency ranges can be adaptively adjusted as needed.

[0063] Optionally, the amplitude of the target envelope waveform is 0 volts to 40 volts, which can be selected as needed, for example: 1v-10v, 10v-20v, 20v-30v, 30v-40v, etc. In actual applications, the range can be adaptively adjusted as needed.

[0064] In some embodiments, the stimulation parameter information includes at least one of the following: stimulation frequency, stimulation duration, amplitude, and a stimulation frequency difference between adjacent target contacts.

[0065] In some embodiments, the amplitude, phase, and frequency of the target envelope waveform are determined based on the amplitude, phase, and frequency of the stimulation signal output by each target contact, respectively.

[0066] The embodiment of the present application takes two simplified independent sinusoidal stimulation sources as an example, that is, two target contacts output stimulation signals, one target contact may be the first contact 110, and the other target contact may be the second contact 120. Each independent stimulation source may generate a specific high-frequency sinusoidal waveform, if represented by a×sin(ωt+β), the amplitude of the stimulation waveform is a, the frequency is ω, and the phase is β, and the envelope waveform of the interference waveform also has amplitude, frequency and phase information.

[0067] Among them, the envelope waveform frequency of the interference waveform is affected by the frequency difference of the two independent stimulus source waveforms, the envelope waveform phase is affected by the phase difference of the two independent stimulus source waveforms, and the envelope waveform amplitude is affected by the amplitude difference of the two independent stimulus source waveforms. If A represents the amplitude of the envelope waveform, Ω represents the frequency of the envelope waveform, and B represents the phase of the envelope waveform, it can be expressed in mathematical language as: A=F(Δa), Ω=F(Δω), A=F(Δβ). This means that the frequency, phase and amplitude of the envelope waveform can be modulated by independently adjusting the waveform frequency, phase and amplitude of each stimulus source.

[0068] See also Figure 3 As shown, the embodiment of the present application provides a schematic diagram of the structure of a first stimulator 130. The stimulator 130 includes: an acquisition module 131, a signal processing module 132 and a control module 133.

[0069] The acquisition module 131 is used to acquire the EEG signal of the target area through at least one acquisition contact in response to satisfying a predetermined trigger condition.

[0070] The signal processing module 132 is used to determine the EEG activity distribution information based on the EEG signal, and determine the target stimulation information based on the EEG activity distribution information and the position information of each contact; the EEG activity distribution information is used to characterize the activity of the EEG activity in the target area.

[0071] The control module 133 is used to control at least two target contacts to output stimulation signals to form a target envelope waveform based on the target stimulation information.

[0072] Optionally, the acquisition module 131 can acquire the EEG signal of the target area under the control of the control module 133 .

[0073] The control module 133 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of the present application. The control module 133 may also be a combination that implements a computing function, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc. Similarly, the signal processing module 132 may also be a CPU (Central Processing Unit) and a general-purpose processor, etc.

[0074] The embodiment of the present application can provide a corresponding target envelope waveform according to the activity of the entire neural pathway of the characteristic area, thereby achieving neural stimulation or inhibition of the entire pathway and avoiding damage caused by unnecessary stimulation.

[0075] The embodiment of the present application can avoid unnecessary stimulation of non-target areas by precisely controlling the stimulation waveform, reduce the damage caused by stimulation, achieve overall control of the entire target area, and improve the stimulation efficiency. Moreover, the embodiment of the present application can adjust the target envelope waveform in real time according to the activity of EEG activity, has strong adaptability, is suitable for different neural regulation needs, and has strong adaptability.

[0076] In some embodiments, the neuromodulation device 13 further comprises at least one of the following: The acquisition module 131 is specifically used to collect the EEG signal of the target area through at least one collection contact according to the set sampling parameter information; the sampling parameter information includes at least one of the following: sampling frequency, resolution; The signal processing module 132 is specifically used to pre-process the EEG signal to obtain a processed EEG signal, and determine the EEG activity distribution information based on the processed EEG signal; the pre-processing includes filtering processing.

[0077] The embodiment of the present application can filter the collected EEG signal, remove noise and interference, and extract effective EEG signal. The signal processing module 132 of the embodiment of the present application performs data processing based on the processed EEG signal, and can obtain more accurate target stimulation information.

[0078] The embodiment of the present application can collect EEG signals according to the set parameters such as sampling frequency and resolution of the EEG signals to ensure the accuracy and reliability of the signals and ensure the effectiveness and precision of the treatment.

[0079] In some embodiments, the signal processing module 132 is specifically used to extract characteristic parameters of the EEG signal based on the EEG signal, and determine the EEG activity distribution information based on the characteristic parameters; the characteristic parameters include power spectrum density, phase information, and entropy information.

[0080] The embodiment of the present application can extract characteristic parameters based on EEG signals, such as power spectral density (PSD), phase information, entropy information, etc., so as to facilitate subsequent targeted analysis and processing of EEG signals. Power spectral density refers to the measure of how the power of a signal is distributed with frequency, and is usually used to describe the energy distribution of a signal at different frequencies.

[0081] Specifically, entropy information is used to characterize the entropy of the characteristics of EEG signals, that is, the entropy of EEG characteristics. Entropy information is a quantitative indicator to measure the complexity of EEG signals. It can be used to describe the order and disorder of signals, that is, the complexity of the nonlinear dynamic process of signals. The entropy of EEG characteristics includes many types, such as wavelet entropy, multiscale entropy (MSE), approximate entropy, sample entropy, etc. Wavelet entropy is a quantitative indicator to measure the order and disorder of the multiscale dynamic behavior of nonlinear signals. The multiscale entropy algorithm is suitable for multiscale nonlinear signal analysis. Sample entropy is a nonlinear method used to measure the probability of generating a new pattern in a time series. The equal probability symbolized sample entropy method combines symbolic dynamics with sample entropy. Therefore, entropy information is an important tool for evaluating the complexity of EEG signals. It helps to reveal the dynamic mechanism of brain electrical activity and plays an important role in cognitive function research and disease diagnosis.

[0082] See also Figure 4 As shown, the embodiment of the present application provides a schematic diagram of the structure of the second stimulator 130. The signal processing module 132 includes a reverse prediction model 1321, which is used to: determine the stimulus information to be predicted in the target area based on the distribution information of the brain electrical activity and the position information of each contact point; perform a first operation on the stimulus information to be predicted in the target area, and use the stimulus information to be predicted that passes the prediction as the target stimulus information.

[0083] Among them, the first operation includes: obtaining a prediction result based on the stimulus information to be predicted; adjusting the stimulus information to be predicted based on the prediction result to obtain adjusted stimulus information; using the adjusted stimulus information as the stimulus information to be predicted until the prediction result meets the requirements and the prediction of the stimulus information to be predicted is passed.

[0084] In some embodiments, the reverse prediction model 1321 is specifically used to: Based on the EEG activity distribution information, the target area is divided into at least two sub-areas and the EEG activity information of each sub-area is determined; the EEG activity information is used to characterize the activity of the EEG activity of the sub-area; Based on the EEG activity information of each sub-region and the position information of each contact point, the stimulus information to be predicted of each sub-region is determined; the stimulus information to be predicted of the target region includes the stimulus information to be predicted of each sub-region; The first operation is performed on the stimulus information to be predicted of each sub-region, and the stimulus information to be predicted of all sub-regions that has passed the prediction is used as the target stimulus information.

[0085] In the embodiment of the present application, the target area can be divided into multiple sub-areas. When the prediction result in each sub-area meets the expectations, the prediction result of the entire target area also meets the requirements.

[0086] Specifically, the first operation is performed on each stimulus information to be predicted, and the stimulus effect is predicted based on the stimulus information to be predicted, and then the stimulus information to be predicted is adjusted to obtain the adjusted stimulus information, and the first operation is continued to be performed as the new stimulus information to be predicted, and this cycle is repeated until the prediction results of the stimulus information to be predicted in each sub-area meet the requirements, and each stimulus information to be predicted passes, and the target stimulus information is obtained.

[0087] In some embodiments, the EEG activity information includes an energy value, and the prediction result includes an energy change, wherein the energy change is the difference between the actual energy value of the sub-region and the predicted energy value; the actual energy value is obtained based on the EEG activity information determined based on the EEG activity distribution information, and the predicted energy value is obtained based on the predicted stimulus information.

[0088] The reverse prediction model 1321 is specifically used to: if the energy change in each sub-region is within a first predetermined range, determine that the prediction result meets the requirements.

[0089] Optionally, the first predetermined range can be set according to actual needs, for example, the energy variation is within the range of 2-4 to achieve a stimulation effect.

[0090] Optionally, the energy value is used to analyze brain waves and provide targeted treatment to the target area. The energy value can be the average value of the relative energy of the EEG, which is a method for analyzing the characteristics of brain waves. It evaluates the state of brain activity by calculating the average energy of brain waves in different frequency bands. Brain waves are electrical signals generated when brain neurons are active. By measuring and analyzing brain waves, we can understand the functions and abnormalities of the brain.

[0091] Optionally, the reverse rehearsal model is obtained in advance through learning and training with a large amount of sample data, and can predict the effectiveness of stimulation, and adjust the stimulation parameters in the stimulation information in real time according to the prediction results. The process of determining the target stimulation information using the reverse rehearsal model can include: real-time acquisition of EEG signals in the target area, analysis of the EEG signals using the reverse rehearsal model, prediction of the stimulation effects under different stimulation parameters, and prediction of the activity and change trend of EEG activity; according to the prediction results, dynamically adjust the parameters of the stimulation waveform to achieve accurate low-frequency envelope waveform stimulation network.

[0092] The embodiment of the present application can establish a stimulation waveform reverse prediction model, and calculate key parameters such as target contact, stimulation frequency, stimulation duration, frequency difference, etc. according to the activity of EEG activity and electrode position. Based on the calculated key parameter information, an effective, full-coverage, and accurate low-frequency envelope waveform stimulation network is formed in the entire specific area to improve the patient's overall symptoms and disease status.

[0093] The embodiment of the present application is a low-frequency envelope waveform stimulation method based on adaptive adjustment of EEG signal activity. By real-time acquisition of EEG signals in the target area, and based on the activity of EEG activity and the position of the electrodes, the stimulation waveform is reversely predicted and rehearsed, so that waveforms of different frequencies emitted by each stimulation contact in the envelope waveform are mutually coordinated and restricted, thereby avoiding damage caused by redundant stimulation and achieving overall regulation of the entire target area. The embodiment of the present application not only improves the accuracy of neural regulation, but also achieves adaptive and precise regulation, which has significant advantages.

[0094] The stimulator 120 of the embodiment of the present application may further include a memory for storing various data of the stimulator 120 , such as stimulation information, EEG signals, and a reverse prediction model 1321 .

[0095] The memory may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media, other magnetic storage devices, or any other medium that can be used to carry or store computer programs and can be read by a computer, without limitation herein.

[0096] The memory is used to store the computer program for executing the embodiment of the present application, and the execution is controlled by the control module 133. The control module 133 is used to execute the computer program stored in the memory to realize the function of the control module 133.

[0097] See also Figure 5 As shown, the present application embodiment provides a schematic diagram of a target envelope waveform. Figure 5 As shown, the horizontal axis is time, the vertical axis is amplitude, and the target envelope waveform can be a waveform with both positive and negative polarities in the same period, and the amplitude of the waveform can change periodically. Different amplitudes and frequencies of the envelope waveform mean different activation areas. Multiple different stimulation sources can be combined to form different envelope waveforms to achieve stimulation of a wider area.

[0098] By applying the embodiments of the present application, at least the following beneficial effects can be achieved: 1. The embodiments of the present application can adaptively adjust the target stimulation information based on the patient's real-time EEG signal in application scenarios such as during patient treatment, at the end of the treatment, and for a period of time after the end of the treatment, and output stimulation signals through the contacts of the cortical electrode 12, or the contacts of the deep electrode 11 and the contacts of the cortical electrode 12, so that targeted treatment can be performed according to the patient's current condition, thereby improving the accuracy of neural regulation and the treatment effect.

[0099] 2. The embodiment of the present application can give a corresponding target envelope waveform according to the activity of the entire neural pathway of the target area, thereby achieving full-pathway neural stimulation or inhibition, avoiding damage caused by unnecessary stimulation, and achieving full-pathway neural stimulation or inhibition.

[0100] 3. The embodiments of the present application can accurately control the stimulation waveform through real-time EEG signals, avoid unnecessary stimulation of non-target areas, and reduce the damage caused by stimulation.

[0101] 4. The target envelope waveform formed by the stimulation signal output based on the target stimulation information in the embodiment of the present application realizes the overall regulation of the entire target area and improves the stimulation efficiency.

[0102] 5. The embodiment of the present application can adjust the target envelope waveform in real time according to the activity of EEG activity, has strong adaptability, and is suitable for different neural regulation needs.

[0103] 6. The embodiment of the present application provides a low-frequency envelope waveform stimulation method based on adaptive adjustment of EEG signal activity. By real-time acquisition of EEG signals in the target area, reverse rehearsal of the stimulation waveform is performed to achieve mutual coordinated constraints between waveforms of different frequencies emitted by each stimulation contact in the envelope waveform, thereby achieving overall regulation of the entire target area.

[0104] It should be understood that, although each operation step is indicated by arrows in the flowchart of the embodiment of the present application, the implementation order of these steps is not limited to the order indicated by the arrows. Unless clearly stated herein, in some implementation scenarios of the embodiment of the present application, the implementation steps in each flowchart can be performed in other orders according to demand. In addition, some or all of the steps in each flowchart may include multiple sub-steps or multiple stages based on actual implementation scenarios. Some or all of these sub-steps or stages may be executed at the same time, and each sub-step or stage in these sub-steps or stages may also be executed at different times respectively. In different scenarios of execution time, the execution order of these sub-steps or stages may be flexibly configured according to demand, and the embodiment of the present application does not limit this.

[0105] In the embodiments of the present application, the term "module" or "unit" refers to a computer program or a part of a computer program that has a predetermined function and works together with other related parts to achieve a predetermined goal, and can be implemented in whole or in part by using software, hardware (such as processing circuits or memories), or a combination thereof. Similarly, a processor (or multiple processors or memories) can be used to implement one or more modules or units. In addition, each module or unit can be part of an overall module or unit that includes the function of the module or unit.

[0106] The above is only an optional implementation method for some implementation scenarios of the present application. It should be pointed out that for ordinary technicians in this technical field, without departing from the technical concept of the solution of the present application, other similar implementation methods based on the technical ideas of the present application are also within the protection scope of the embodiments of the present application.

Claims

1. A neural regulation device, characterized in that: include: A stimulator, for electrically connecting to at least one deep electrode and at least one cortical electrode, configured to acquire an EEG signal of a target area through at least one acquisition contact in response to a predetermined trigger condition being met, adjust current stimulation information based on the EEG signal to obtain target stimulation information; based on the target stimulation information, control at least two target contacts to output stimulation signals to form a target envelope waveform, so as to perform neural regulation on the target area; Wherein, the predetermined trigger condition includes at least one of the following: outputting a stimulation signal, a first predetermined time after outputting a stimulation signal, stopping outputting a stimulation signal, and a second predetermined time after stopping outputting a stimulation signal; The acquisition contacts include contacts of the cortical electrodes and / or contacts of the deep electrodes, the target contacts include contacts of the cortical electrodes, or contacts of the deep electrodes and contacts of the cortical electrodes, and the target stimulation information includes target contact information and stimulation parameter information corresponding to each target contact.

2. The neural regulation device according to claim 1, characterized in that: The target envelope waveform is formed by the mutual cooperative constraints of the stimulation signals output by each target contact, and the frequencies of the stimulation signals output by each target contact are different.

3. The neural regulation device according to claim 1, characterized in that: The frequency of the target envelope waveform is 5 Hz to 20 kHz; and / or the amplitude of the target envelope waveform is 0 volts to 40 volts.

4. The neural regulation device according to claim 1, characterized in that: The amplitude, phase and frequency of the target envelope waveform are determined based on the amplitude, phase and frequency of the stimulation signal output by each of the target contacts.

5. The neural regulation device according to claim 1, characterized in that: The stimulation parameter information includes at least one of the following: stimulation frequency, stimulation duration, amplitude, and stimulation frequency difference between adjacent target contacts.

6. The neural regulation device according to claim 1, characterized in that: The stimulator comprises: An acquisition module, configured to acquire an electroencephalogram signal of a target area through at least one acquisition contact in response to satisfying a predetermined trigger condition; A signal processing module, used to determine EEG activity distribution information based on the EEG signal, and determine target stimulation information based on the EEG activity distribution information and position information of each contact point; the EEG activity distribution information is used to characterize the activity of EEG activity in the target area; The control module is used to control at least two target contacts to output stimulation signals to form a target envelope waveform based on the target stimulation information.

7. The neural regulation device according to claim 6, characterized in that: Also includes at least one of the following: The acquisition module is specifically used to collect the EEG signal of the target area through at least one of the acquisition contacts according to the set sampling parameter information; the sampling parameter information includes at least one of the following: sampling frequency, resolution; The signal processing module is specifically used to pre-process the EEG signal to obtain a processed EEG signal, and determine EEG activity distribution information based on the processed EEG signal; the pre-processing includes filtering processing.

8. The neural regulation device according to claim 6, characterized in that: The signal processing module is specifically used to extract characteristic parameters of the EEG signal based on the EEG signal, and determine the EEG activity distribution information based on the characteristic parameters; the characteristic parameters include power spectrum density, phase information, and entropy information.

9. The neural regulation device according to claim 6, characterized in that: The signal processing module includes a back-propagation preview model, which is used to: Determining the stimulus information to be predicted for the target area based on the EEG activity distribution information and the position information of each of the contacts; Performing a first operation on the stimulus information to be predicted in the target area, and using the stimulus information to be predicted that passes the prediction as the target stimulus information; Among them, the first operation includes: obtaining a prediction result based on the stimulus information to be predicted; adjusting the stimulus information to be predicted based on the prediction result to obtain adjusted stimulus information; using the adjusted stimulus information as the stimulus information to be predicted until the prediction result meets the requirements and the prediction of the stimulus information to be predicted is passed.

10. The neural regulation device according to claim 9, characterized in that: The reverse prediction model is specifically used for: Based on the EEG activity distribution information, the target area is divided into at least two sub-areas and EEG activity information of each sub-area is determined; the EEG activity information is used to characterize the activity of the EEG activity of the sub-area; Based on the EEG activity information of each sub-region and the position information of each contact point, determining the stimulus information to be predicted of each sub-region; the stimulus information to be predicted of the target region includes the stimulus information to be predicted of each sub-region; The first operation is performed on the stimulus information to be predicted of each sub-region, and the stimulus information to be predicted that passes the prediction of all the sub-regions is used as the target stimulus information.

11. The neural regulation device according to claim 10, characterized in that: The EEG activity information includes an energy value, and the prediction result includes an energy change amount, where the energy change amount is a difference between an actual energy value of the sub-region and a predicted energy value; The actual energy value is obtained based on the EEG activity information determined based on the EEG activity distribution information, and the predicted energy value is predicted based on the stimulus information to be predicted; The reverse prediction model is specifically used to: if the energy change amount of each sub-region is within a first predetermined range, then determine that the prediction result meets the requirements.

12. A neural regulation system, characterized in that: include: At least one deep electrode, at least one cortical electrode, and a neuromodulatory device as claimed in any one of claims 1 to 11; Each of the deep electrodes is implanted in a target area of ​​a target object, and each of the cortical electrodes is attached to a position of the target object corresponding to the target area; Each of said deep electrodes and each of said cortical electrodes comprises at least one contact; Each of the contacts is electrically connected to the stimulator, the contacts of the deep electrodes are used to collect EEG signals and / or output stimulation signals under the control of the stimulator, and the contacts of the cortical electrodes are used to collect EEG signals and / or output stimulation signals under the control of the stimulator.

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