Signal acquisition and nerve stimulation method based on wireless implantable brain-computer interface

Abstract

The invention discloses a signal acquisition and nerve stimulation method based on a wireless implantable brain-computer interface, and the method comprises the steps: building communication connection with an upper computer, and obtaining a stimulation current parameter and a signal acquisition parameter set by the upper computer; generating bipolar stimulation current according to the stimulation current parameter, and performing brain wave stimulation processing on a target object according to the bipolar stimulation current; performing signal acquisition processing on the electroencephalogram signal after electroencephalogram stimulation processing according to the signal acquisition parameter to obtain a target electroencephalogram signal; performing action potential signal detection processing and fragmentation processing on the target electroencephalogram signal to obtain a target electroencephalogram data packet, and uploading the target electroencephalogram data packet to the upper computer. According to the invention, real-time electrical stimulation control and electroencephalogram data acquisition and return can be supported, and the real-time regulation and control of animal robot behaviors by researchers and the synchronization of electroencephalogram signal research can be effectively ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of brain wave signal processing, and in particular to a signal acquisition and neural stimulation method, system, terminal and computer-readable storage medium based on a wireless implantable brain-computer interface. Background Art

[0002] Brain-computer interface technology directly acts on specific brain regions (nuclei) or nervous systems of animal carriers by simulating neural signals, inducing neuronal activity in related functional brain regions, thereby achieving control over animal movement behaviors. This animal-machine hybrid system developed by regulating animal neural information is an animal robot. The functional realization and information transmission of the nervous system mainly rely on the transmission of action potentials between neurons. Recording neuronal signals is an important method for exploring the basic functions of the nervous system. Cell-level electrical signal recording is essential for understanding the deep structure and function of the brain, and is also the key to controlling the movement of animal robots.

[0003] However, the currently developed remote-control stimulation systems for animal robots cannot simultaneously support real-time electrical stimulation control and the collection and transmission of EEG data, which makes it impossible for researchers to conduct real-time behavior regulation and EEG signal research on animal robots.

[0004] Therefore, the prior art still needs to be improved and developed. Summary of the invention

[0005] The main purpose of the present invention is to provide a signal acquisition and neural stimulation method, system, terminal and computer-readable storage medium based on a wireless implantable brain-computer interface, aiming to solve the problem that the prior art cannot simultaneously support real-time electrical stimulation control and the acquisition and transmission of EEG data, thereby making it impossible for researchers to perform real-time behavior regulation and EEG signal research on animal robots.

[0006] To achieve the above object, the present invention provides a signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface, and the signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface comprises the following steps:

[0007] Establishing a communication connection with a host computer and obtaining stimulation current parameters and signal acquisition parameters set by the host computer;

[0008] generating a bipolar stimulation current according to the stimulation current parameters, and performing brain wave stimulation processing on the target object according to the bipolar stimulation current;

[0009] Performing signal acquisition processing on the EEG signal after the EEG stimulation processing according to the signal acquisition parameters to obtain a target EEG signal;

[0010] The target EEG signal is subjected to action potential signal detection processing and segmentation processing to obtain a target EEG data packet, and the target EEG data packet is uploaded to the host computer.

[0011] Optionally, the signal acquisition and neural stimulation method based on the wireless implantable brain-computer interface, wherein the step of establishing a communication connection with a host computer and obtaining stimulation current parameters and signal acquisition parameters set by the host computer, specifically includes:

[0012] When receiving a connection instruction issued by a user, generating a communication connection request according to the connection instruction, and sending the communication connection request to a preset network transparent transmission tool;

[0013] The communication connection request is sent to the host computer through the preset network transmission tool. When the authorization instruction of the host computer is received, a communication connection with the host computer is established, and the stimulation current parameters and signal acquisition parameters set by the host computer are obtained.

[0014] Optionally, in the signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface, the stimulation current parameters include stimulation current amplitude, stimulation current pulse spacing, and a preset number of pulses;

[0015] The step of generating a bipolar stimulation current according to the stimulation current parameter, and performing brain wave stimulation processing on the target object according to the bipolar stimulation current, specifically includes:

[0016] Acquire a target stimulation current, perform level segmentation processing on the target stimulation current to obtain multiple segment levels, and set the stimulation current amplitude and the stimulation current pulse interval of the multiple segment levels according to the stimulation current parameters;

[0017] When the stimulation current amplitudes and stimulation current pulse intervals of the multiple segment levels are set, the number of pulses corresponding to the target stimulation current is increased by one, and when the number of pulses reaches the preset number of pulses, a bipolar stimulation current is obtained;

[0018] A target object is determined, and brain wave stimulation processing is performed on the target object according to the bipolar stimulation current.

[0019] Optionally, in the signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface, the signal acquisition parameters include digital signal processing, sliding window, and action potential detection threshold;

[0020] The step of performing signal acquisition processing on the EEG signal after the EEG stimulation processing according to the signal acquisition parameters to obtain the target EEG signal specifically includes:

[0021] Performing signal acquisition and processing on the EEG signal after the EEG stimulation process at each preset time interval of the sliding window to obtain an electrophysiological signal;

[0022] The electrophysiological signal is subjected to the digital signal processing to obtain a target electroencephalogram signal, wherein the digital signal processing includes filtering processing, amplification processing and analog-to-digital conversion processing.

[0023] Optionally, the signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface, wherein the target EEG signal is subjected to action potential signal detection and slicing processing to obtain a target EEG data packet, and the target EEG data packet is uploaded to the host computer, specifically comprising:

[0024] Using a threshold detection method to perform action potential signal detection processing on the collected target EEG signal within a preset time of the sliding window to obtain a target action potential signal;

[0025] Slice processing is performed according to the target action potential signal to obtain a target EEG data packet, and the target EEG data packet is uploaded to the host computer.

[0026] Optionally, the signal acquisition and neural stimulation method based on the wireless implantable brain-computer interface, wherein the threshold detection method is used to perform action potential signal detection processing on the collected target EEG signal within a preset time of the sliding window to obtain the target action potential signal, specifically includes:

[0027] Acquire multiple target EEG signals collected within a preset time of the sliding window, and determine whether the multiple target EEG signals are greater than the action potential detection threshold;

[0028] If yes, then determining the EEG signal greater than the action potential detection threshold among the multiple target EEG signals as the target action potential signal;

[0029] If not, the EEG signals whose values ​​are less than or equal to the action potential detection threshold among the multiple target EEG signals are discarded.

[0030] Optionally, the signal acquisition and neural stimulation method based on the wireless implantable brain-computer interface, wherein the target action potential signal is processed in slices to obtain a target EEG data packet, specifically includes:

[0031] Acquiring the number of acquisitions of the target EEG signal, and when the number of acquisitions reaches a first preset value, performing field potential signal acquisition to obtain a target field potential signal;

[0032] When the number of acquisitions reaches a second preset value, Beidou positioning signal acquisition is performed to obtain a target Beidou positioning signal, wherein the second preset value is greater than the first preset value;

[0033] The target action potential signal, the target field potential signal and the target Beidou positioning signal are combined and processed to obtain a target data frame;

[0034] When the number of the target data frames reaches the preset number of data frames, the target data frames are packaged into data packets to obtain target EEG data packets.

[0035] In addition, to achieve the above-mentioned purpose, the present invention also provides a signal acquisition and neural stimulation system based on a wireless implantable brain-computer interface, wherein the signal acquisition and neural stimulation system based on a wireless implantable brain-computer interface comprises:

[0036] A parameter acquisition module is used to establish a communication connection with a host computer and obtain stimulation current parameters and signal acquisition parameters set by the host computer;

[0037] A brain wave stimulation module, used for generating a bipolar stimulation current according to the stimulation current parameters, and performing brain wave stimulation processing on the target object according to the bipolar stimulation current;

[0038] A signal acquisition module, used for performing signal acquisition processing on the EEG signal after the EEG stimulation processing according to the signal acquisition parameters to obtain a target EEG signal;

[0039] The signal processing module is used to perform action potential signal detection processing and segmentation processing on the target EEG signal to obtain a target EEG data packet, and upload the target EEG data packet to the host computer.

[0040] In addition, to achieve the above-mentioned purpose, the present invention also provides a terminal, wherein the terminal includes: a memory, a processor, and a signal acquisition and neural stimulation program based on a wireless implantable brain-computer interface stored in the memory and executable on the processor, wherein the signal acquisition and neural stimulation program based on a wireless implantable brain-computer interface, when executed by the processor, implements the steps of the signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface as described above.

[0041] In addition, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a signal acquisition and neural stimulation program based on a wireless implantable brain-computer interface, and when the signal acquisition and neural stimulation program based on a wireless implantable brain-computer interface is executed by a processor, the steps of the signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface as described above are implemented.

[0042] In the present invention, a communication connection is established with a host computer, and stimulation current parameters and signal acquisition parameters set by the host computer are obtained; a bipolar stimulation current is generated according to the stimulation current parameters, and brain wave stimulation processing is performed on the target object according to the bipolar stimulation current; signal acquisition processing is performed on the EEG signal after the brain wave stimulation processing according to the signal acquisition parameters to obtain a target EEG signal; action potential signal detection processing and fragmentation processing are performed on the target EEG signal to obtain a target EEG data packet, and the target EEG data packet is uploaded to the host computer. The present invention can realize the real-time feedback and storage of the target EEG signal through an implantable bipolar brain-computer interface device, and can also support controllable brain wave stimulation of the target object. The present invention integrates remote control, data acquisition and electrical stimulation functions, which makes up for the shortcomings of existing research equipment and has an important role in promoting the application research of animal robots and the exploration of the nervous system. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a flow chart of a preferred embodiment of the signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface of the present invention;

[0044] Figure 2 It is a schematic diagram of a pigeon robot and its flight control according to a preferred embodiment of the signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface of the present invention;

[0045] Figure 3 It is a schematic diagram of the connection of the implantable bipolar brain-computer interface device end of a preferred embodiment of the signal acquisition and neural stimulation method based on the wireless implantable brain-computer interface of the present invention;

[0046] Figure 4 It is a schematic diagram of the process of establishing connection between a PC end and a bipolar brain-computer interface device end of a preferred embodiment of the signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface of the present invention;

[0047] Figure 5 It is a bipolar pulse schematic diagram of a preferred embodiment of the signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface of the present invention;

[0048] Figure 6 It is a schematic diagram of the initialization setting interface of bipolar pulse stimulation on the host computer side of a preferred embodiment of the signal acquisition and neural stimulation method based on the wireless implantable brain-computer interface of the present invention;

[0049] Figure 7 It is a schematic diagram of a controllable bipolar pulse stimulation implementation process of a preferred embodiment of a signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface of the present invention;

[0050] Figure 8It is a schematic diagram of the bipolar pulse phase control setting interface of the host computer end of the preferred embodiment of the signal acquisition and neural stimulation method based on the wireless implantable brain-computer interface of the present invention;

[0051] Fig. 9 It is a schematic diagram of a sampling cycle chain for a threshold detection algorithm of a preferred embodiment of the signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface of the present invention;

[0052] Fig.10 It is a schematic diagram of the format of a real-time return function data packet of a preferred embodiment of the signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface of the present invention;

[0053] Fig.11 It is a schematic diagram of the upper computer's real-time EEG collection and feedback function implementation of a preferred embodiment of the signal collection and neural stimulation method based on a wireless implantable brain-computer interface of the present invention;

[0054] Fig.12 It is a schematic diagram of a Beidou positioning trajectory displayed in real time by a host computer of a preferred embodiment of the signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface of the present invention;

[0055] Fig.13 It is a schematic diagram of sampling effect of acquisition and storage function of a preferred embodiment of the signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface of the present invention;

[0056] Fig.14 It is a structural diagram of a preferred embodiment of the signal acquisition and neural stimulation system based on a wireless implantable brain-computer interface of the present invention;

[0057] Fig.15 It is a structural diagram of a preferred embodiment of the terminal of the present invention. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solution and advantages of the present invention clearer and more specific, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0059] Brain-computer interface technology directly acts on specific brain areas (nuclei) or nervous systems of animal carriers by simulating neural signals, inducing neuronal activity in related functional brain areas, thereby achieving control of animal movement behavior. This animal-machine hybrid system developed by regulating animal neural information is an animal robot. Animal robots are a special type of life-like robots that deeply and organically integrate life with traditional micro-electromechanical systems to form a new type of robot system. It has the advantages of both life and micro-electromechanical systems, integrating the perception, drive and autonomous intelligence capabilities of animal carriers, as well as the high precision, repeatability and controllability of micro-electromechanical systems. Animal robots have natural and significant advantages in terms of motion stability, flexibility, environmental adaptability and self-motion energy supply, overcoming the difficulties of traditional bionic robots in distributed drive, environmental perception and energy supply. It not only has forward-looking scientific value, but also has broad application prospects, and is expected to complete many tasks that traditional bionic robots or humans cannot complete. Such robots can perform tasks such as counter-terrorism, search and rescue, and temporal perception in the field of public safety; they are widely used in environmental surveys and narrow space detection in the civilian field; in the field of scientific research, they can be used as research tools to explore unknown areas such as the structure of motor neural networks and the laws of neural information interaction, neural plasticity, and functional repair.

[0060] The brain is a highly integrated organizational structure composed of many different types of neurons, which are interconnected through axons and dendrites. Neurons transmit excitement to another cell through axons (signal output end) and receive signals from other neurons through multiple dendrites (signal input end). The function realization and information transmission of the nervous system mainly rely on the transmission of action potentials between neurons. Recording neuronal signals is an important method to explore the basic functions of the nervous system. Cell-level electrical signal recording is crucial to understanding the deep structure and function of the brain, and is also the key to controlling the movement of animal robots.

[0061] The animal robot remote control stimulation system currently developed is mainly based on wireless communication technologies such as infrared technology (infrared data association, IrDA), radio frequency transceiver chips, Bluetooth, Zigbee (a short-range, low-complexity, low-power, low-rate, low-cost two-way wireless communication technology), star network communication and 3G network to achieve the reception and transmission of stimulation signals. The advantages and disadvantages of the above technologies are as follows: 1. Infrared technology has strong anti-interference ability, but it requires point-to-point directional transmission, cannot be networked, and has a short transmission distance, so it is rarely used now. 2. The remote control range of radio frequency communication is less than 500 meters, which is easily affected by obstacles, has poor anti-interference performance, is easy to lose instructions, and has insufficient reliability. 3. Bluetooth communication has a faster communication rate and less delay, but its communication distance and networking capabilities are limited, which limits its application in animal behavior regulation research. 4. Zigbee star network communication rate is low, but the network capacity is large and the working frequency band is flexible. Its unique wireless networking communication technology can realize the coordinated regulation of multiple animal robots. It is currently the most widely used wireless communication method in animal behavior regulation research in small-scale environments. 5. In outdoor large-scale environments, the animal robot motion control system designed in the prior art generally transmits data through base stations using the civilian 3G communication network. The related devices in the prior art can either only send electrical stimulation control instructions or perform program control, or can only perform low-sampling-rate real-time EEG acquisition or store EEG signals, but cannot combine the two.

[0062] To solve the above problems, the present invention provides an implantable bipolar brain-computer interface device based on a 4G network, which can realize the real-time feedback of 32-channel EEG signals and Beidou positioning data (used to locate animals with implanted brain-computer interfaces installed), support 16 channels of controllable electrical stimulation, and store 32 channels of original EEG signals. The present invention integrates remote control, data acquisition and electrical stimulation functions, making up for the shortcomings of existing research equipment, and plays an important role in promoting the application research of animal robots and the exploration of the nervous system.

[0063] The present invention can achieve the functions of efficient neural remote control stimulation and real-time collection, storage and feedback of EEG signals during the implementation of implantable bipolar brain-computer interface. Among them, the functions implemented by the present invention are as follows: 1. Remote control stimulation function: provide controllable output pulse frequency, pulse width, stimulation channel and stimulation time; 2. Real-time feedback function of EEG signals: support real-time feedback of field potential signals with a sampling rate of 1kHz and action potential signals after 10kHz sampling processing; 3. Subject positioning: real-time feedback of 1Hz Beidou positioning signal; 4. EEG signal storage and recording function: the sampled signal can be recorded in a storage card (TF), supporting up to 15KHz sampling. The present invention integrates remote control, data acquisition and electrical stimulation, makes up for the shortcomings of existing research equipment, plays an important role in promoting animal robot research and nervous system exploration, and provides strong support for animal robot research and nervous system exploration.

[0064] The signal acquisition and neural stimulation method based on the wireless implantable brain-computer interface described in the preferred embodiment of the present invention is as follows: Figure 1 As shown, the signal acquisition and neural stimulation method based on the wireless implantable brain-computer interface includes the following steps:

[0065] Step S10, establishing a communication connection with a host computer, and obtaining stimulation current parameters and signal acquisition parameters set by the host computer.

[0066] Brain-computer interface technology directly acts on specific brain regions (nuclei) or nervous systems of animal carriers by simulating neural signals, inducing neuronal activity in related functional brain regions, thereby achieving control over animal movement behavior. This animal-machine hybrid system developed by regulating animal neural information is an animal robot. Figure 2 The following is a schematic diagram of the pigeon robot and its flight control ( Figure 2 (a) in the figure is a pigeon robot. Figure 2 (b) is a flight control schematic).

[0067] The present invention consists of two modules, namely the implantable brain-computer interface device and the host computer, which transmit signals through the 4G network and ultimately realize the functions of stimulation, signal collection and positioning. Figure 3 As shown in the figure, the implantable brain-computer interface device is composed of an embedded microprocessor, a power module, a digital electrophysiological acquisition module, a digital electrophysiological stimulation module, a 4G communication positioning module and a storage module, while the host computer is deployed on a computer, and through 4G communication with the implantable brain-computer interface device, it realizes the functions of issuing stimulation instructions, receiving electrophysiological and positioning signals, etc., among which, Figure 3 No schematic diagram of the host computer is given.

[0068] Specifically, when a connection instruction issued by the user is received, a communication connection request is generated according to the connection instruction, and the communication connection request is sent to a preset network transmission tool; the communication connection request is sent to a host computer through the preset network transmission tool, and when an authorization instruction from the host computer is received, a communication connection with the host computer is established, and the stimulation current parameters and signal acquisition parameters set by the host computer are obtained.

[0069] Regarding the 4G communication process between the implanted brain-computer interface and the host computer: since the two are not in the same local area network, it is impossible to directly establish a wireless connection. In the present invention, the connection function is mainly realized through network transparent transmission. Figure 4 As shown, first, the 4G communication module in the implanted brain-computer interface sends a TCP connection request, and the network transparent transmission tool (i.e. Figure 4 After receiving the request, the server maps the connection to the network transmission tool ( Figure 4 The Peanut Shell app in the system will send a TCP connection request to the host computer. When the host computer detects the connection request, it will still establish a TCP connection with the 4G communication module through the above network transparent transmission tool. After the connection is completed, the two can conduct real-time network communication on a large spatial scale. The functions of sending stimulation instructions, signal collection and transmission, and positioning information transmission in the present invention are all based on this wireless communication.

[0070] Step S20, generating a bipolar stimulation current according to the stimulation current parameters, and performing brain wave stimulation processing on the target object according to the bipolar stimulation current. The stimulation current parameters include stimulation current amplitude, stimulation current pulse interval, and preset pulse number.

[0071] Specifically, a target stimulation current is obtained, and level-segmented processing is performed on the target stimulation current to obtain multiple segmented levels, and the stimulation current amplitude and the stimulation current pulse spacing of the multiple segmented levels are set according to the stimulation current parameters; when the stimulation current amplitude and the stimulation current pulse spacing of the multiple segmented levels are set, the number of pulses corresponding to the target stimulation current is increased by one, and when the number of pulses reaches the preset number of pulses, a bipolar stimulation current is obtained; a target object is determined, and brain wave stimulation processing is performed on the target object according to the bipolar stimulation current.

[0072] The bipolar pulse stimulation function in the present invention is to control the subject (i.e., the target object in the present invention) by emitting stimulation current to specific brain areas, i.e., the "brain control" function in the brain-computer interface. Compared with unipolar stimulation, bipolar pulse stimulation provides more abundant and precise control options, and can more effectively regulate neural activity, thereby improving the diversity and effectiveness of stimulation control. Figure 5 As shown in the figure, the bipolar pulse is divided into four level stages, among which the B and D stages are generally zero level stages, and the A and C stages are opposite level stages, thus forming a bipolar pulse. Figure 6 As shown, Figure 6 The interface for setting the bipolar stimulation current amplitude of the host computer on the PC side is demonstrated. It can set whether the stimulation of each channel starts when the electrophysiological stimulation chip is initially stimulated, whether the stimulation polarity is positive or negative, and set the positive and negative stimulation current size of each channel.

[0073] The present invention first sets relevant parameters (i.e., stimulation current parameters in the present invention, including the amplitude, pulse spacing, and pulse number of stimulation current) through a host computer, and then generates a bipolar stimulation current (such as Figure 7 As shown, the process of generating bipolar stimulation current is as follows: after the embedded end receives the stimulation current parameters, it first sets the stimulation current amplitude of each of the 16 channels of the electrophysiological stimulation module through SPI instructions (SPI instructions refer to the instructions sent by the microprocessor to the electrophysiological acquisition stimulation module through the SPI communication protocol), and then enters the loop logic. First, SPI sets the on state of each channel of the stimulation module in phase A, and then SPI sets the current polarity state of each channel of the stimulation module in phase A. After the setting is completed, each channel starts to output the corresponding current, and then the microprocessor enters the delay waiting for the stimulation time set in phase A. Similarly, phases B, C, and D are executed in sequence. After the execution is completed, the number of stimulated pulses is increased by 1, and it is determined whether the number of bidirectional pulse stimulation is less than the set number of pulse stimulation. If so, the loop program continues to be executed. If not, the loop is exited, indicating that the stimulation program is completed). Figure 8 As shown, Figure 8 The interface for setting the bipolar pulse current channel opening, polarity, stage time length and number of pulses during stage control. Here, only the current channel opening and polarity of stages A and C are set, and the channels of stages B and D are not opened by default (zero level). Specifically, the host computer sends the stimulation current parameter data packet to the 4G communication module through a TCP (Transmission Control Protocol) connection, and the embedded microprocessor receives the stimulation current parameter data packet sent by the 4G module through the serial port and parses it. Among them, the stimulation current amplitude, the spacing of the stimulation pulses and the number of pulses are realized by the internal delay logic and loop judgment logic of the embedded microprocessor. The results of the bipolar pulse stimulation function can be displayed by an oscilloscope, and the generated bipolar stimulation pulses with adjustable amplitude, pulse width and number can be displayed on the oscilloscope.

[0074] like Figure 5As shown, in order to complete the bidirectional pulse function, the present invention divides the stimulation mode into four stages. Different stimulation polarities are set in each stage to achieve the stimulation pattern of a bidirectional pulse. For example: the stimulation polarity is set to positive in stage A, the stimulation is turned off in stage B (that is, the stimulation polarity is 0), the stimulation polarity is set to negative in stage C, and the stimulation is turned off in stage D (that is, the stimulation polarity is 0), thereby forming a bidirectional pulse stimulation current that is first positive and then negative.

[0075] Step S30, performing signal acquisition processing on the EEG signal after the EEG stimulation processing according to the signal acquisition parameters to obtain a target EEG signal, wherein the signal acquisition parameters include digital signal processing, sliding window and action potential detection threshold.

[0076] Specifically, signal acquisition processing is performed on the EEG signal after brain wave stimulation processing at a preset time interval of the sliding window to obtain an electrophysiological signal; the digital signal processing is performed on the electrophysiological signal to obtain a target EEG signal, wherein the digital signal processing includes filtering processing, amplification processing and analog-to-digital conversion processing.

[0077] For the EEG signal acquisition and real-time feedback function: this function is realized through the following five steps: 1. Parameter setting: the host computer sets the parameters of the electrophysiological collector (i.e., the electrophysiological acquisition module in the present invention), including parameters such as digital signal processing, sliding window, and action potential detection threshold; 2. 4G transmission parameters: the above parameters are sent to the 4G module through TCP, and the parameter data packet parsed by the 4G module is sent to the embedded microprocessor through the serial port; 3. EEG acquisition: after the embedded microprocessor receives the acquisition feedback command and parameters, it uses the timer to send the acquisition command to the 32-channel digital electrophysiological acquisition module through the SPI interface, and finally realizes the sampling of the EEG signal at 10kHz (the embedded microprocessor sends "CONVERT" through the SPI protocol). (i.e. conversion)" instruction to the electrophysiological acquisition module, that is, starting the voltage sampling process of a channel. After two SPI protocol instruction cycles, the electrophysiological acquisition module will return the analog-to-digital converted and amplified voltage value through the SPI protocol to the embedded microprocessor. The embedded microprocessor executes this process repeatedly. The time of sending a cycle of "CONVERT" instructions can achieve 10khz sampling) and the collected electrophysiological signals are digitized (the digitization process is a function implemented inside the electrophysiological acquisition module, mainly including filtering, amplification, analog-to-digital conversion, etc.) and stored in the RAM of the microprocessor; 4. Action potential detection: Use the threshold detection method to detect the action potential signal within the set sliding window time; such as Fig. 9 As shown, each time the embedded microprocessor controls the electrophysiological module to collect 32 channels of data, it is placed into sampling group i (such as Fig. 9Sample group 1, sample group 2, sample group 3 and sample group 4), then i is incremented and the formula Sample is judged. i >threshold∩Sample i+1 >threshold∩Sample i+2 <threshold∩Sample i+3 <Whether the threshold is established, where Sample i Indicates the first sampling, Sample i+1 Indicates the second sampling, Sample i+2 Indicates the third sampling, Sample i+3 Indicates the fourth sampling, threshold indicates the action potential detection threshold set by the host computer. If it exceeds this threshold, it is considered to be a possible action potential signal. This formula is used to determine whether it exceeds this threshold. If it is established, it is considered that a possible action potential signal is detected, and then the sampling detection action is repeated (because the action potential detection follows the EEG acquisition, as long as the EEG acquisition does not stop, there will be a steady stream of new EEG data being collected, and the detection program will be repeated. Fig. 9 The circular linked list shown is used for action potential detection, and each newly collected EEG signal will overwrite the previous position of the circular linked list); if not, the collected data will be discarded.

[0078] For the local storage function of EEG signals: Similar to the above-mentioned EEG signal acquisition function, the host computer first needs to set and send the parameters of the electrophysiological collector (i.e., the electrophysiological acquisition module in the present invention). After the parameters are received and analyzed by the 4G communication module on the brain-computer interface device, they are transmitted to the embedded microprocessor. After receiving the storage instruction, the microprocessor will collect and store the electrophysiological signals at a sampling rate of 15KHz. The storage process occurs in the sampling interval, mainly by configuring the SDIO (Secure Digital Input and Output) storage protocol and opening the storage DMA (Direct Memory Access) to achieve the simultaneous acquisition and storage of the original electrophysiological signals. The original electrophysiological signals stored in the SD card can be used for offline signal analysis and neural decoding.

[0079] Step S40, performing action potential signal detection processing and segmentation processing on the target EEG signal to obtain a target EEG data packet, and uploading the target EEG data packet to the host computer.

[0080] Specifically, multiple target EEG signals collected within a preset time of the sliding window are obtained, and it is determined whether the multiple target EEG signals are greater than the action potential detection threshold; if so, the EEG signals greater than the action potential detection threshold among the multiple target EEG signals are determined as target action potential signals; if not, the EEG signals less than or equal to the action potential detection threshold among the multiple target EEG signals are discarded.

[0081] The target EEG signal acquisition times are obtained. When the acquisition times reaches a first preset value, field potential signal acquisition is performed to obtain a target field potential signal. When the acquisition times reaches a second preset value, Beidou positioning signal acquisition is performed to obtain a target Beidou positioning signal, wherein the second preset value is greater than the first preset value. The target action potential signal, the target field potential signal and the target Beidou positioning signal are combined and processed to obtain a target data frame. When the number of the target data frames reaches a preset number of data frames, the target data frames are packaged and processed to obtain a target EEG data packet, and the target EEG data packet is uploaded to the host computer.

[0082] For the data packet construction process: the slicing operation of the configuration step before the 4G module is sent is inserted into the gap after each sampling, the field potential signal is sampled once in the gap after every 10 samplings (i.e., the first preset value in the present invention), and the 1Hz Beidou positioning signal is obtained once in the gap after every 30 samplings (i.e., the second preset value in the present invention) and forms a data frame. 11 data frames form a TCP packet and are sent once, such as Fig.10 shown.

[0083] For the data transmission process: according to the sampling interval, the embedded microprocessor sends the data to the 4G communication module through DMA (DMA is a function of the embedded microprocessor, which is designed to send data to the 4G module without consuming CPU time). The 4G communication module packages the data packet into a TCP packet and sends it to the host computer. During the test, the host computer receives the TCP data packet and parses it into field potential signals, action potentials, Beidou positioning signals, and frame numbers (such as Fig.10 As shown in the figure, the received data packet is 100 bytes, of which the index 0-63 bytes are action potential signals, 64-69 bytes are field potential signals, 72-97 bytes are Beidou positioning signal data, 98 is a timeout mark, and the last byte is the frame number data), and it is displayed in a visual way. Fig.11 As shown, Fig.11 This is the diagram for the upper computer to collect EEG feedback function in real time. Fig.11 a in the figure is a single-channel field potential acquisition display block diagram. Fig.11 The block diagram of b in the figure is a possible action potential signal display block diagram calculated by the embedded microprocessor. Fig.11 a and Fig.11 The b in the figure can display the analyzed field potential signal and action potential signal data respectively. For the Beidou positioning block diagram to display the positioning signal: Fig.12 As shown, Fig.12 The upper computer displays the Beidou positioning data sent back by the 4G module in real time and draws a trajectory diagram. The horizontal and vertical coordinates represent longitude and latitude respectively. Fig.13 As shown, Fig.13 To collect the implementation results of the storage function, the sampling results of channel 1 are displayed. It can be seen that the action potential shape can be sampled well.

[0084] In summary, the present invention sets up an implantable bipolar brain-computer interface architecture based on 4G network communication: 1. The architecture combines an embedded microprocessor, a professional digital electrophysiological acquisition and stimulation module, and a 4G communication module to achieve efficient data transmission and control; 2. Specifically, the embedded microprocessor is responsible for processing and parsing the signals obtained from the electrophysiological acquisition module, and controlling the electrophysiological stimulation module to output the specified bipolar pulses. At the same time, remote data transmission and control instruction reception are achieved through the 4G network.

[0085] The present invention provides a real-time EEG signal acquisition and transmission technology based on 4G network communication, including: 1. On-chip threshold detection technology: After each sampling, Fig. 9 1. The EEG data is processed in the circular sampling group linked list window of size 4 shown in the figure, and the action potential signal is detected using the threshold method, that is: after collecting 32 channels of data, it is placed in the sampling group i, and then i is incremented backward, and it is judged whether the formula is established. If it is established, it is considered that a possible action potential signal is detected, and then the sampling detection action is repeated; 2. Functional slicing technology in the sampling gap: the slicing operation of the configuration step before the 4G module is sent is inserted into the gap after each sampling, the field potential signal is sampled once in the gap after every 10 samplings, and the 1Hz Beidou positioning signal is obtained once in the gap after every 30 samplings and forms a data frame (11 data frames form a TCP packet and are sent once), so that data can be transmitted back without packet loss and ensuring the sampling rate; 3. 15kHz sampling rate EEG signal storage and recording technology, 512 sampling cycles are regarded as 1 sampling block, and the configuration of SDIO storage protocol and the opening of storage DMA operation are inserted into the slices from the 27th cycle of the reciprocal of 1 sampling block, so as to realize the acquisition and storage of the original signal at a sampling rate of 15kHz at the same time. The programmable 16-channel bipolar pulse stimulation technology based on 4G network divides the bipolar pulse into 4 stages, and the current polarity of each channel in each stage can be set, thereby realizing programmable bipolar pulses.

[0086] The present invention proposes an implantable bipolar brain-computer interface device based on a 4G network, which aims to solve many deficiencies in the prior art. The system consists of two parts: a remote PC and a multi-channel EEG acquisition stimulator on an animal, and specifically includes the following functions: 1. Remote control stimulation function: providing controllable number of pulses, pulse width, stimulation channels and stimulation time to achieve precise bipolar electrical stimulation control. 2. Real-time EEG signal feedback function: supporting 1 channel 1kHz sampling rate field potential signal, 32 channels 10kHz sampling and processed action potential signal, 3ms packet transmission to ensure real-time monitoring. 3. Subject positioning function: 1Hz Beidou positioning signal acquisition. 4. EEG signal storage and recording function: collecting EEG raw signals at a sampling rate of 15kHz, and recording them in the TF card of the collector (offline storage function, after storage, the TF storage card needs to be unplugged and read with a PC), which is convenient for subsequent analysis and research. By integrating remote control, data acquisition and electrical stimulation functions, the present invention effectively makes up for the shortcomings of existing equipment in real-time data feedback and signal storage, and provides strong support for animal robot research and nervous system exploration. The present invention not only improves the functionality and reliability of the system, but also expands its applicability in various application scenarios.

[0087] Technical effects of the present invention:

[0088] 1. The present invention sets up a remote real-time collection and feedback technology of remote implantable EEG based on 4G: previous technical solutions only provided EEG stimulation options, while the present invention can also feedback EEG signals and Beidou positioning signals in real time, so that the ground end can grasp the animal's trajectory information and EEG status in real time, which can not only be used for remote EEG decoding, but also for preview before EEG storage.

[0089] 2. The present invention provides an implantable EEG remote control acquisition and storage technology: the bipolar brain-computer interface terminal can realize the acquisition and storage functions of 32 channels and 15kHz sampling rate, which greatly improves the data processing capability and flexibility. The existing stimulation technology is expanded to a 16-channel programmable bipolar pulse stimulation mode, which can set the number of pulses, stage pulse width, stimulation channel and stimulation time. A more flexible stimulation mode is conducive to better electrophysiological regulation.

[0090] Furthermore, the technical contents of the expansion or replacement of the solution are as follows (introduced from the two aspects of application and implementation):

[0091] 1. Based on 5G network: Reason: 5G network has higher bandwidth and lower latency, which can significantly improve data transmission efficiency and real-time performance; Implementation: By replacing the existing 4G module with a 5G module, and adjusting the data transmission protocol to adapt to the 5G network.

[0092] 2. Low-power design: Reason: Extending the battery life of the device is very important for portability and practical applications; Implementation: Use low-power microprocessors (such as ARM Cortex-M series), optimize the code to reduce power consumption, and add power management modules.

[0093] 3. Multi-channel EEG signal acquisition: Reason: Multi-channel acquisition can provide richer EEG data and help more accurate signal analysis. Implementation: Add more electrophysiological acquisition channels and optimize data processing algorithms to handle more data.

[0094] 4. Biobattery Implementation: Reason: Biobatteries use biochemical processes to generate electricity, which can provide a more environmentally friendly and sustainable power solution, especially for long-term implanted devices. Implementation: Choose biobattery technology based on enzyme catalytic reactions or microbial fuel cells (MFCs) to ensure that it can provide enough power to support the normal operation of the device.

[0095] 5. Improved signal processing algorithm: Reason: Improve the detection and analysis accuracy of EEG signals. Implementation: Use more advanced machine learning algorithms (such as deep learning) to analyze EEG signals in real time and improve the recognition rate of action potential signals.

[0096] 6. Other uses:

[0097] Medical monitoring: Application: Real-time monitoring of the EEG activity of epilepsy patients, early warning of epileptic seizures. Implementation: Combining cloud computing and big data analysis, real-time transmission and analysis of patients' EEG signals, providing early warning information to doctors and patients.

[0098] Brain-computer interaction: Application: Used for smart home control, to control home appliances through EEG signals. Implementation: Combined with the smart home platform, design EEG signal control interface to control lighting, air conditioning, TV and other equipment.

[0099] Neuroscience research: Application: Used to study the activity patterns of the human brain under different tasks. Implementation: Provides an open API interface for researchers to collect and analyze EEG data, supporting a variety of experimental designs and data analysis methods.

[0100] Education and Learning: Application: Used to monitor students’ concentration and emotions and optimize the learning process. Implementation: Combined with the education platform, real-time monitoring of students’ EEG activities can be performed to provide personalized learning suggestions and improve learning efficiency.

[0101] Animal behavior research: Application: Used in animal behavior research to monitor the animal's neural activity through EEG signals. Implementation: Integrate multiple sensors and behavior analysis tools to collect and analyze animal EEG signals and behavior data in real time, and support complex behavior experiments.

[0102] Furthermore, if Fig.14 As shown, based on the above-mentioned signal acquisition and neural stimulation method based on wireless implantable brain-computer interface, the present invention also provides a signal acquisition and neural stimulation system based on wireless implantable brain-computer interface, wherein the signal acquisition and neural stimulation system based on wireless implantable brain-computer interface includes:

[0103] The parameter acquisition module 51 is used to establish a communication connection with a host computer and obtain stimulation current parameters and signal acquisition parameters set by the host computer;

[0104] A brain wave stimulation module 52, used for generating a bipolar stimulation current according to the stimulation current parameters, and performing brain wave stimulation processing on the target object according to the bipolar stimulation current;

[0105] A signal acquisition module 53, used for performing signal acquisition processing on the EEG signal after the EEG stimulation processing according to the signal acquisition parameters to obtain a target EEG signal;

[0106] The signal processing module 54 is used to perform action potential signal detection processing and segmentation processing on the target EEG signal to obtain a target EEG data packet, and upload the target EEG data packet to the host computer.

[0107] Furthermore, if Fig.15 As shown, based on the above-mentioned signal acquisition and neural stimulation method and system based on wireless implantable brain-computer interface, the present invention also provides a terminal accordingly, and the terminal includes a processor 10, a memory 20 and a display 30. Fig.15 Only some components of the terminal are shown, but it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0108] In some embodiments, the memory 20 may be an internal storage unit of the terminal, such as a hard disk or memory of the terminal. In other embodiments, the memory 20 may also be an external storage device of the terminal, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the terminal. Further, the memory 20 may also include both an internal storage unit of the terminal and an external storage device. The memory 20 is used to store application software and various types of data installed in the terminal, such as the program code of the installation terminal. The memory 20 may also be used to temporarily store data that has been output or is to be output. In one embodiment, a signal acquisition and neural stimulation program 40 based on a wireless implantable brain-computer interface is stored on the memory 20, and the signal acquisition and neural stimulation program 40 based on a wireless implantable brain-computer interface can be executed by the processor 10, thereby realizing the signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface in the present application.

[0109] In some embodiments, the processor 10 can be a central processing unit (CPU), a microprocessor or other data processing chip, used to run the program code or process data stored in the memory 20, such as executing the signal acquisition and neural stimulation method based on the wireless implantable brain-computer interface.

[0110] In some embodiments, the display 30 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. The display 30 is used to display information on the terminal and to display a visual user interface. The components 10-30 of the terminal communicate with each other via a system bus.

[0111] In one embodiment, when the processor 10 executes the signal acquisition and neural stimulation program 40 based on the wireless implantable brain-computer interface in the memory 20, the following steps are implemented:

[0112] Establishing a communication connection with a host computer and obtaining stimulation current parameters and signal acquisition parameters set by the host computer;

[0113] generating a bipolar stimulation current according to the stimulation current parameters, and performing brain wave stimulation processing on the target object according to the bipolar stimulation current;

[0114] Performing signal acquisition processing on the EEG signal after the EEG stimulation processing according to the signal acquisition parameters to obtain a target EEG signal;

[0115] The target EEG signal is subjected to action potential signal detection processing and segmentation processing to obtain a target EEG data packet, and the target EEG data packet is uploaded to the host computer.

[0116] The step of establishing a communication connection with a host computer and obtaining stimulation current parameters and signal acquisition parameters set by the host computer specifically includes:

[0117] When receiving a connection instruction issued by a user, generating a communication connection request according to the connection instruction, and sending the communication connection request to a preset network transparent transmission tool;

[0118] The communication connection request is sent to the host computer through the preset network transmission tool. When the authorization instruction of the host computer is received, a communication connection with the host computer is established, and the stimulation current parameters and signal acquisition parameters set by the host computer are obtained.

[0119] Wherein, the stimulation current parameters include stimulation current amplitude, stimulation current pulse interval and preset pulse number;

[0120] The step of generating a bipolar stimulation current according to the stimulation current parameter, and performing brain wave stimulation processing on the target object according to the bipolar stimulation current, specifically includes:

[0121] Acquire a target stimulation current, perform level segmentation processing on the target stimulation current to obtain multiple segment levels, and set the stimulation current amplitude and the stimulation current pulse interval of the multiple segment levels according to the stimulation current parameters;

[0122] When the stimulation current amplitudes and stimulation current pulse intervals of the multiple segment levels are set, the number of pulses corresponding to the target stimulation current is increased by one, and when the number of pulses reaches the preset number of pulses, a bipolar stimulation current is obtained;

[0123] A target object is determined, and brain wave stimulation processing is performed on the target object according to the bipolar stimulation current.

[0124] Wherein, the signal acquisition parameters include digital signal processing, sliding window and action potential detection threshold;

[0125] The step of performing signal acquisition processing on the EEG signal after the EEG stimulation processing according to the signal acquisition parameters to obtain the target EEG signal specifically includes:

[0126] Performing signal acquisition and processing on the EEG signal after the EEG stimulation process at each preset time interval of the sliding window to obtain an electrophysiological signal;

[0127] The electrophysiological signal is subjected to the digital signal processing to obtain a target electroencephalogram signal, wherein the digital signal processing includes filtering processing, amplification processing and analog-to-digital conversion processing.

[0128] The step of performing action potential signal detection and slicing processing on the target EEG signal to obtain a target EEG data packet, and uploading the target EEG data packet to the host computer specifically includes:

[0129] Using a threshold detection method to perform action potential signal detection processing on the collected target EEG signal within a preset time of the sliding window to obtain a target action potential signal;

[0130] Slice processing is performed according to the target action potential signal to obtain a target EEG data packet, and the target EEG data packet is uploaded to the host computer.

[0131] The step of performing action potential signal detection processing on the target EEG signal collected within a preset time of the sliding window using a threshold detection method to obtain a target action potential signal specifically includes:

[0132] Acquire multiple target EEG signals collected within a preset time of the sliding window, and determine whether the multiple target EEG signals are greater than the action potential detection threshold;

[0133] If yes, then determining the EEG signal greater than the action potential detection threshold among the multiple target EEG signals as the target action potential signal;

[0134] If not, the EEG signals whose values ​​are less than or equal to the action potential detection threshold among the multiple target EEG signals are discarded.

[0135] The step of performing slicing processing according to the target action potential signal to obtain a target EEG data packet specifically includes:

[0136] Acquiring the number of acquisitions of the target EEG signal, and when the number of acquisitions reaches a first preset value, performing field potential signal acquisition to obtain a target field potential signal;

[0137] When the number of acquisitions reaches a second preset value, Beidou positioning signal acquisition is performed to obtain a target Beidou positioning signal, wherein the second preset value is greater than the first preset value;

[0138] The target action potential signal, the target field potential signal and the target Beidou positioning signal are combined and processed to obtain a target data frame;

[0139] When the number of the target data frames reaches the preset number of data frames, the target data frames are packaged into data packets to obtain target EEG data packets.

[0140] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a signal acquisition and neural stimulation program based on a wireless implantable brain-computer interface, and when the signal acquisition and neural stimulation program based on a wireless implantable brain-computer interface is executed by a processor, the steps of the signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface as described above are implemented.

[0141] In summary, the present invention provides a signal acquisition and neural stimulation method and related equipment based on a wireless implantable brain-computer interface, the method comprising: establishing a communication connection with a host computer, and obtaining stimulation current parameters and signal acquisition parameters set by the host computer; generating a bipolar stimulation current according to the stimulation current parameters, and performing brain wave stimulation processing on the target object according to the bipolar stimulation current; performing signal acquisition processing on the EEG signal after the brain wave stimulation processing according to the signal acquisition parameters to obtain a target EEG signal; performing action potential signal detection processing and fragmentation processing on the target EEG signal to obtain a target EEG data packet, and uploading the target EEG data packet to the host computer. The present invention can realize the real-time feedback and storage of the target EEG signal through an implantable bipolar brain-computer interface device, and can also support controllable brain wave stimulation of the target object. The present invention integrates remote control, data acquisition and electrical stimulation functions, makes up for the shortcomings of existing research equipment, and has an important role in promoting the application research of animal robots and the exploration of the nervous system.

[0142] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or terminal including the element.

[0143] Of course, those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing related hardware (such as a processor, a controller, etc.) through a computer program, and the program can be stored in a computer-readable storage medium that can be read by a computer, and the program can include the processes of the above-mentioned method embodiments when executed. The computer-readable storage medium can be a memory, a disk, an optical disk, etc.

[0144] It should be understood that the application of the present invention is not limited to the above examples. For ordinary technicians in this field, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to the present invention.

Claims

1. A signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface, characterized in that: The signal acquisition and neural stimulation method based on the wireless implantable brain-computer interface includes: Establishing a communication connection with a host computer and obtaining stimulation current parameters and signal acquisition parameters set by the host computer; generating a bipolar stimulation current according to the stimulation current parameters, and performing brain wave stimulation processing on the target object according to the bipolar stimulation current; Performing signal acquisition processing on the EEG signal after the EEG stimulation processing according to the signal acquisition parameters to obtain a target EEG signal; The target EEG signal is subjected to action potential signal detection processing and segmentation processing to obtain a target EEG data packet, and the target EEG data packet is uploaded to the host computer.

2. The signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface according to claim 1, characterized in that: The step of establishing a communication connection with a host computer and obtaining stimulation current parameters and signal acquisition parameters set by the host computer specifically includes: When receiving a connection instruction issued by a user, generating a communication connection request according to the connection instruction, and sending the communication connection request to a preset network transparent transmission tool; The communication connection request is sent to the host computer through the preset network transmission tool. When the authorization instruction of the host computer is received, a communication connection with the host computer is established, and the stimulation current parameters and signal acquisition parameters set by the host computer are obtained.

3. The signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface according to claim 1, characterized in that: The stimulation current parameters include stimulation current amplitude, stimulation current pulse spacing and preset pulse number; The step of generating a bipolar stimulation current according to the stimulation current parameter, and performing brain wave stimulation processing on the target object according to the bipolar stimulation current, specifically includes: Acquire a target stimulation current, perform level segmentation processing on the target stimulation current to obtain multiple segment levels, and set the stimulation current amplitude and the stimulation current pulse interval of the multiple segment levels according to the stimulation current parameters; When the stimulation current amplitudes and stimulation current pulse intervals of the multiple segment levels are set, the number of pulses corresponding to the target stimulation current is increased by one, and when the number of pulses reaches the preset number of pulses, a bipolar stimulation current is obtained; A target object is determined, and brain wave stimulation processing is performed on the target object according to the bipolar stimulation current.

4. The signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface according to claim 1, characterized in that: The signal acquisition parameters include digital signal processing, sliding window and action potential detection threshold; The step of performing signal acquisition processing on the EEG signal after the EEG stimulation processing according to the signal acquisition parameters to obtain the target EEG signal specifically includes: Performing signal acquisition and processing on the EEG signal after the EEG stimulation process at each preset time interval of the sliding window to obtain an electrophysiological signal; The electrophysiological signal is subjected to the digital signal processing to obtain a target electroencephalogram signal, wherein the digital signal processing includes filtering processing, amplification processing and analog-to-digital conversion processing.

5. The signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface according to claim 4, characterized in that: The step of performing action potential signal detection processing and slicing processing on the target EEG signal to obtain a target EEG data packet, and uploading the target EEG data packet to the host computer specifically includes: Using a threshold detection method to perform action potential signal detection processing on the collected target EEG signal within a preset time of the sliding window to obtain a target action potential signal; Slice processing is performed according to the target action potential signal to obtain a target EEG data packet, and the target EEG data packet is uploaded to the host computer.

6. The signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface according to claim 5, characterized in that: The step of performing action potential signal detection processing on the collected target EEG signal within a preset time of the sliding window by using a threshold detection method to obtain a target action potential signal specifically includes: Acquire multiple target EEG signals collected within a preset time of the sliding window, and determine whether the multiple target EEG signals are greater than the action potential detection threshold; If yes, then determining the EEG signal greater than the action potential detection threshold among the multiple target EEG signals as the target action potential signal; If not, the EEG signals whose values ​​are less than or equal to the action potential detection threshold among the multiple target EEG signals are discarded.

7. The signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface according to claim 5, characterized in that: The performing of slicing processing according to the target action potential signal to obtain a target EEG data packet specifically includes: Acquiring the number of acquisitions of the target EEG signal, and when the number of acquisitions reaches a first preset value, performing field potential signal acquisition to obtain a target field potential signal; When the number of acquisitions reaches a second preset value, Beidou positioning signal acquisition is performed to obtain a target Beidou positioning signal, wherein the second preset value is greater than the first preset value; The target action potential signal, the target field potential signal and the target Beidou positioning signal are combined and processed to obtain a target data frame; When the number of the target data frames reaches the preset number of data frames, the target data frames are packaged into data packets to obtain target EEG data packets.

8. A signal acquisition and neural stimulation system based on a wireless implantable brain-computer interface, characterized in that: The signal acquisition and neural stimulation system based on the wireless implantable brain-computer interface includes: A parameter acquisition module is used to establish a communication connection with a host computer and obtain stimulation current parameters and signal acquisition parameters set by the host computer; A brain wave stimulation module, used for generating a bipolar stimulation current according to the stimulation current parameters, and performing brain wave stimulation processing on the target object according to the bipolar stimulation current; A signal acquisition module, used for performing signal acquisition processing on the EEG signal after the EEG stimulation processing according to the signal acquisition parameters to obtain a target EEG signal; The signal processing module is used to perform action potential signal detection processing and segmentation processing on the target EEG signal to obtain a target EEG data packet, and upload the target EEG data packet to the host computer.

9. A terminal, characterized in that: The terminal includes: a memory, a processor, and a signal acquisition and neural stimulation program based on a wireless implantable brain-computer interface stored in the memory and executable on the processor. When the signal acquisition and neural stimulation program based on a wireless implantable brain-computer interface is executed by the processor, the steps of the signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a signal acquisition and neural stimulation program based on a wireless implantable brain-computer interface. When the signal acquisition and neural stimulation program based on a wireless implantable brain-computer interface is executed by a processor, the steps of the signal acquisition and neural stimulation method based on a wireless implantable brain-computer interface are implemented.

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