Fusion system combining brain-computer interface with transcranial electrical stimulation and feedback stimulation method

Abstract

The invention relates to the technical field of brain-computer interfaces, and particularly discloses a fusion system combining a brain-computer interface with transcranial electrical stimulation and a feedback stimulation method. The fusion system comprises a main machine part, an auxiliary machine part, a PCB substrate, a terminal integrated receiver and a feedback calculation module. The host part comprises an electroencephalogram signal acquisition device and a transcranial electrical stimulation device which are both installed on a PCB substrate. The auxiliary machine part comprises an MCU and a first wireless device which are both installed on the PCB substrate. The auxiliary machine part further comprises a battery which is connected to the MCU, the electroencephalogram signal collecting device and the transcranial electrical stimulation device. The terminal integrated receiver has a second wireless device. And the terminal integrated receiver is connected to the feedback calculation module. According to the fusion system, the electroencephalogram signal acquisition device and the transcranial electrical stimulation device are combined to acquire brain waves and feed back and adjust transcranial electrical stimulation parameters, so that nervous excitability can be better induced, and an electroencephalogram value is enhanced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of brain-computer interface, in particular to a fusion system of brain-computer interface combined with cranial electrostimulation and a feedback stimulation method. BACKGROUND

[0002] Brain-computer interface (BCI) technology is a technology that enables the brain to interact with computer systems, allowing the brain to directly control computer systems and other external devices. Brain-computer interface technology has been widely used in medical, gaming, auxiliary communication, psychology and other fields.

[0003] Cranial electrotherapy stimulation (CES) is a completely different treatment method from traditional drug treatment and electroconvulsive therapy. It stimulates the brain with low-intensity microcurrent to change the abnormal brain waves of patients and promote the secretion of neurotransmitters and hormones closely related to diseases such as anxiety, depression and insomnia, thereby achieving treatment of these diseases.

[0004] The treatment principle of CES is essentially to transmit special modulated waveforms (impulses) from the temple to the skull to directly stimulate the brain, hypothalamus, limbic system and reticular system that govern psychological and emotional activities.

[0005] Current products on the market mainly separate the collection of brain waves from cranial electrostimulation and use them separately, and do not form an effective feedback incentive that combines brain wave values with real-time adjustment of cranial electrostimulation signals. The actual coordination of the two is low. SUMMARY

[0006] In view of the problem that current products on the market mainly separate the collection of brain waves from cranial electrostimulation and use them separately, and do not form an effective feedback incentive that combines brain wave values with real-time adjustment of cranial electrostimulation signals, the actual coordination of the two is low, the present application proposes a fusion system of brain-computer interface combined with cranial electrostimulation and a feedback stimulation method to solve this problem.

[0007] In a first aspect, the present application proposes a fusion system of brain-computer interface combined with cranial electrostimulation, and adopts the following technical solution.

[0008] A fusion system of brain-computer interface combined with cranial electrostimulation, comprising a host part, a slave part, a PCB substrate, a terminal integrated receiver and a feedback calculation module.

[0009] The host part comprises a brain electrical signal acquisition device and a cranial electrostimulation device, both of which are installed on the PCB substrate.

[0010] The auxiliary machine part comprises an MCU and a first wireless device, both of which are installed on the PCB substrate; the EEG signal acquisition device, the transcranial electrical stimulation device and the first wireless device are all connected to the MCU.

[0011] The auxiliary machine part further comprises a battery, which is connected to the MCU, the EEG signal acquisition device and the transcranial electrical stimulation device; the transcranial electrical stimulation device has a conversion module for converting the electricity supplied by the battery into pulsed electric waves.

[0012] The terminal integrated receiver has a second wireless device for wireless communication with the first wireless device; the terminal integrated receiver is connected to the feedback calculation module.

[0013] By adopting the above technical solution, the fusion system combines the EEG signal acquisition device and the transcranial electrical stimulation device, can collect the brain waves and adjust the feedback of the transcranial electrical stimulation parameters, realizes the combination of the brain-computer interface and the transcranial electrical stimulation technology, can effectively induce the nerve excitability and enhance the brain wave value.

[0014] In a preferred scheme of the brain-computer interface fusion system combined with the transcranial electrical stimulation, the conversion module comprises a boost circuit part, a pulse modulation part and a protection device connected in sequence; the battery is connected to the boost circuit part.

[0015] By adopting the above technical solution, the direct current low-voltage electricity output by the battery can be boosted, converted into alternating current and converted into digital pulsed electric waves, can stimulate the subject beneficially, and is output after protection measures, plays a role in protecting the subject.

[0016] In a preferred scheme of the brain-computer interface fusion system combined with the transcranial electrical stimulation, the transcranial electrical stimulation device has a transcranial electrical stimulation left electrode and a transcranial electrical stimulation right electrode; the protection device is connected to the transcranial electrical stimulation left electrode and the transcranial electrical stimulation right electrode.

[0017] By adopting the above technical solution, the transcranial electrical stimulation left electrode and the transcranial electrical stimulation right electrode form a loop, can stimulate and regulate the target area.

[0018] In a preferred scheme of the brain-computer interface fusion system combined with the transcranial electrical stimulation, the EEG signal acquisition device has an EEG acquisition left electrode, an EEG acquisition right electrode and an ear electrode; the ear electrode comprises an ear clip and an ear wire, and the ear clip is connected to the end of the ear wire.

[0019] By adopting the technical scheme, the electroencephalogram acquisition left electrode and the electroencephalogram acquisition right electrode form a loop. The ear electrode is used as a reference electrode, and the difference between the test value of the electroencephalogram acquisition left electrode and the ear electrode and the difference between the test value of the electroencephalogram acquisition right electrode and the ear electrode are used as the respective measurement values of the electroencephalogram acquisition left electrode and the electroencephalogram acquisition right electrode, so that the measurement result is more accurate.

[0020] In a second aspect, the application provides a feedback stimulation method of a brain-computer interface combined with transcranial electrical stimulation, and adopts the following technical scheme.

[0021] The feedback stimulation method of the brain-computer interface combined with the transcranial electrical stimulation is executed by using the fusion system, the electroencephalogram signal acquisition device is worn on the left brain and the right brain of a testee, the transcranial electrical stimulation device is worn on the left brain and the right brain of the testee, and feedback stimulation is performed, including the following steps.

[0022] S1, the electroencephalogram signal acquisition device acquires electroencephalogram data of the testee in a resting state and transmits the electroencephalogram data to the feedback calculation module.

[0023] S2, the feedback calculation module calculates baseline parameters in the resting state, specifically, the acquired electroencephalogram data of the left brain and the right brain of two leads with a time length of t are converted into frequency domain modes by a fast Fourier transform algorithm or a wavelet transform algorithm to obtain frequency domain electroencephalogram data, each second of the frequency domain electroencephalogram data has a group, each group contains spectral intensity data of the left brain and the right brain of two leads, and the two leads are divided into the same multiple frequency bands.

[0024] S3, electrical stimulation is performed by using an initial set value of a transcranial electrical stimulation parameter.

[0025] S4, after a period of electrical stimulation is completed, the stimulation is stopped, then the electroencephalogram signal acquisition device acquires electroencephalogram signal values of the testee again, and after a period of electroencephalogram signal is acquired, the electroencephalogram data and the electrical stimulation parameter values of the transcranial electrical stimulation device are transmitted to the feedback calculation module.

[0026] S5, the electroencephalogram data obtained in step S4 are recalculated to obtain a group of feedback parameters in the manner of calculating baseline parameters in step S2.

[0027] S6, the feedback calculation module calculates feedback index parameters according to the baseline parameters and the feedback parameters, adjusts the electrical stimulation parameters of the transcranial electrical stimulation device according to the index parameters, and performs electrical stimulation according to the newly adjusted parameters.

[0028] By adopting the technical scheme, the method adjusts the stimulation signal according to the acquired electroencephalogram signal each time, so that the excitability of neurons can be effectively enhanced.

[0029] The preferred scheme of the brain-computer interface combined with the feedback stimulation method of transcranial electrical stimulation is that, in step S2, the data of each lead is divided into the same 5 frequency bands, including the data of 5 frequency bands of delta wave, theta wave, alpha wave, beta wave and gamma wave, and 10 frequency domain data of 2 leads of left and right brain are obtained every second, wherein the frequency band of the delta wave is 1-3Hz, the frequency band of the theta wave is 4-7Hz, the frequency band of the alpha wave is 8-12Hz, the frequency band of the beta wave is 13-30Hz, and the frequency band of the gamma wave is 31-50Hz.

[0030] By adopting the above technical scheme, each frequency band corresponds to different physiological significance, the electroencephalogram signal is converted into interpretable physiological language, and subsequent calculation and adjustment of the stimulation electric wave are facilitated.

[0031] The preferred scheme of the brain-computer interface combined with the feedback stimulation method of transcranial electrical stimulation is that, in step S2, the baseline parameters in the resting state are calculated, including first calculating a first parameter set P i , then calculating a first parameter A0 and a second parameter B0.

[0032] ,

[0033] In the above formula, P iL is the left brain spectrum intensity of the i-th frequency band, P iR is the right brain spectrum intensity of the i-th frequency band, and t is the electroencephalogram data length; P i of a plurality of frequency bands constitutes the first parameter set.

[0034] ,

[0035] In the above formula, n is the number of divided frequency bands.

[0036] ,

[0037] In the above formula, M LT is the spectrum intensity value of the first frequency band of the left brain at T moment, N LT is the spectrum intensity value of the second frequency band of the left brain at T moment, M RT is the spectrum intensity value of the first frequency band of the right brain at T moment, N RT is the spectrum intensity value of the second frequency band of the right brain at T moment, and t is the electroencephalogram data length.

[0038] By adopting the above technical scheme, the baseline parameters are quantified, and a quantitative index is provided for subsequent accurate evaluation and adjustment of the stimulation effect.

[0039] The preferred scheme of the brain-computer interface combined with the feedback stimulation method of transcranial electrical stimulation is that, in step S5, a group of feedback parameters are recalculated, including first calculating a first parameter set P i; and recalculating the first parameter A1 and the second parameter B1.

[0040] ,

[0041] In the above formula, P iL is the left brain spectral intensity of the i-th frequency band, P iR is the right brain spectral intensity of the i-th frequency band, and t is the length of the brain electrical data; P i of multiple frequency bands constitutes a first parameter set.

[0042] ,

[0043] In the above formula, n is the number of frequency bands.

[0044] ,

[0045] In the above formula, M LT is the spectral intensity value of the first frequency band of the left brain at time T, N LT is the spectral intensity value of the second frequency band of the left brain at time T, M RT is the spectral intensity value of the first frequency band of the right brain at time T, N RT is the spectral intensity value of the second frequency band of the right brain at time T, and t is the length of the brain electrical data.

[0046] By adopting the above technical solution, the feedback parameter is obtained in the same calculation manner as step S2, ensuring the consistency of the post-stimulation parameter and the baseline parameter calculation method and standard, making the comparison of the pre- and post-parameters comparable, and ensuring the rigor and effectiveness of the feedback adjustment logic.

[0047] A preferred scheme of the brain-computer interface combined with the feedback stimulation method of transcranial electrical stimulation is that in step S6, the index parameter includes a third parameter P1 and a fourth parameter Q1.

[0048] , ,

[0049] The parameters of the electrical stimulation signal are adjusted according to the values of P1 and Q1, and the electrical stimulation frequency and pulse width of the transcranial electrical stimulation device are adjusted respectively, and the adjustment mode is as follows.

[0050] (1) According to the value of P1, the stimulation frequency is adjusted on the basis of the initial basic frequency, and the new frequency = basic frequency *[1+(K1*P1) / 100], wherein K1 is a frequency adjustment coefficient, the value is between 0 and 1, and P1 is the third parameter value calculated at the current time.

[0051] (2) According to the value of Q1, adjust the pulse width of the stimulation on the basis of the initial basic pulse width, new pulse width = basic pulse width * [1 + (K2 * Q1) / 100], wherein K2 is a pulse width adjustment coefficient, the value is between 0 and 1, and Q1 is the value of the fourth parameter calculated at the current moment.

[0052] Carry out electrical stimulation according to the newly adjusted frequency and pulse width parameters.

[0053] By adopting the technical scheme, the post-stimulation electroencephalogram is collected, new parameters are calculated and compared with the baseline, and the frequency and pulse width of subsequent stimulation are quantitatively and directionally adjusted, so that a complete closed loop of stimulation, evaluation, adjustment and re-stimulation is realized, which enables the stimulation parameters to dynamically adapt to the real-time electroencephalogram feedback of the user and be personalized optimized towards the expected regulation target.

[0054] A preferred scheme of the brain-computer interface combined with the feedback stimulation method of transcranial electrical stimulation is that the actions of steps S4-S6 are repeatedly performed to realize the electrical stimulation process based on electroencephalogram feedback.

[0055] By adopting the technical scheme, through multiple executions of the collection, calculation, comparison and adjustment cycle, continuous and dynamic optimization of the stimulation parameters can be realized, so that the neural regulation process is more precise and more adaptive to the real-time state changes of the user, and the long-term intervention effect is improved.

[0056] In summary, the brain-computer interface combined with the fusion system and feedback stimulation method of transcranial electrical stimulation has the following beneficial effects: the brain-computer interface technology is combined with the transcranial electrical stimulation technology, the electrical stimulation signal is adjusted according to the collected electroencephalogram signal each time, the excitability of neurons can be effectively enhanced, and the electroencephalogram value of the measured person can be enhanced. BRIEF DESCRIPTION OF DRAWINGS

[0057] Figure 1 The brain-computer interface combined with the feedback stimulation block diagram of transcranial electrical stimulation.

[0058] Figure 2 The schematic diagram of the transcranial electrical stimulation device and the electroencephalogram signal collection device applied to the human body.

[0059] Figure 3 The schematic diagram of the alternating current pulse waveform generated by transcranial electrical stimulation modulation. DETAILED DESCRIPTION

[0060] The technical solutions in the embodiments will be described clearly and completely below with reference to the drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the following embodiments, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0061] REFERENCE Figure 1The application discloses a fusion system of a brain-computer interface combined with transcranial electrical stimulation.

[0062] The host part comprises an electroencephalogram signal acquisition device and a transcranial electrical stimulation device, which are both mounted on the PCB substrate.

[0063] The electroencephalogram signal acquisition device has an electroencephalogram acquisition left electrode, an electroencephalogram acquisition right electrode and an ear electrode.

[0064] Reference Figure 2 The transcranial electrical stimulation device has a transcranial electrical stimulation left electrode and a transcranial electrical stimulation right electrode.

[0065] The electroencephalogram acquisition left electrode, the electroencephalogram acquisition right electrode, the transcranial electrical stimulation left electrode and the transcranial electrical stimulation right electrode can all be in the shape of a flat circle. The electrodes are located at the ends of lead wires and are connected to the lead wires through single welding points, and the welding points are externally provided with insulation protection devices. The electrodes are pasted with sheet conductive gel before being in contact with the skin, and are used for skin contact and fixation, are comfortable to paste, and can effectively and uniformly stimulate electricity. The transcranial electrical stimulation left electrode and the transcranial electrical stimulation right electrode can be pasted at the two ends of the forehead of the skull. The electroencephalogram acquisition left electrode and the electroencephalogram acquisition right electrode can be pasted on the two sides of the transcranial electrical stimulation left electrode and the transcranial electrical stimulation right electrode. The ear electrode can be added at the earlobe position and serves as a reference electrode. In the process of electroencephalogram signal acquisition, in order to obtain accurate electroencephalogram signals, a stable reference electrode is needed to provide a reference potential. The biological electrical activity on the ear is relatively small, and thus can serve as an ideal reference point. By measuring the difference between the electroencephalogram acquisition left electrode, the electroencephalogram acquisition right electrode and the reference electrode, the quality and reliability of the electroencephalogram signals can be improved.

[0066] The slave part comprises a micro control unit (MCU) and a first wireless device, which can be Bluetooth. The MCU and the Bluetooth are both mounted on the PCB substrate. The electroencephalogram signal acquisition device, the transcranial electrical stimulation device and the Bluetooth are all connected to the MCU. The information collected by the electroencephalogram signal acquisition device is transmitted to the MCU, is processed, is wirelessly transmitted to the terminal integrated receiver through the Bluetooth, is wirelessly transmitted to the feedback calculation module through the terminal integrated receiver, and the electrical wave parameters needed for next stimulation are calculated and returned to the MCU and the transcranial electrical stimulation device for stimulation.

[0067] The slave part further comprises a battery, which is connected to the MCU, the electroencephalogram signal acquisition device and the transcranial electrical stimulation device.

[0068] Because the voltage supplied by the battery is low, it cannot reach the voltage required for effective electrical stimulation of the organism. Therefore, after the direct current enters the system, it is boosted to the voltage required for effective electrical stimulation of the organism. However, the boosted voltage is unstable, with a high voltage value, a small output current, and large peak-to-valley fluctuations, and cannot meet the needs of effective electrical stimulation of the organism. Therefore, the voltage needs to be processed by a voltage processing device to achieve relatively stable direct current output. However, direct current stimulation of the human body has no clinically beneficial biological stimulation effect, and therefore the voltage needs to be converted to alternating current to achieve electrical stimulation in different directions. At this time, the alternating current acting on the human body can be clearly perceived as hammering stimulation. The electrical signal is then modulated by a pulse modulation circuit to achieve controllable pulse signal modulation. The objects of modulation are pulse width and frequency, and the object of regulation is the strength of energy release. For safety reasons, the electrical signal cannot directly act on the human body, and a series of protection measures (such as voltage limit, current limit, direction correction, and residual electricity discharge) are required before it enters the human body.

[0069] Therefore, a transcranial electrical stimulation device is designed to have a conversion module that converts the battery-supplied electricity into a pulse electrical wave. Referring to Figure 2 , the conversion module includes a boost circuit portion, a pulse modulation portion, and a protection device connected in sequence. The battery is connected to the boost circuit portion. The protection device is connected to the transcranial electrical stimulation left electrode and the transcranial electrical stimulation right electrode.

[0070] The boost circuit portion is responsible for boosting the input low-voltage signal to an appropriate stimulation voltage to meet the stimulation needs. The boost circuit and the voltage processing portion include an input end, a boost converter, and an output end. The input end receives the low-voltage signal of the battery, which is boosted by the boost converter and outputs an appropriate stimulation voltage to the output end. Energy storage processing at the output end can prevent rapid voltage fluctuations and serve as a buffer. The boost converter uses a high-efficiency boost converter chip, which has high efficiency and stability.

[0071] Referring to Figure 3 , the pulse modulation portion is responsible for pulse conversion and modulation of the stimulation voltage to generate a stimulation signal with a specific frequency and amplitude.

[0072] The protection device limits the voltage, automatically cuts off the power supply when the voltage and current exceed a certain value, corrects the direction, automatically discards the group of electrical signals when the direction of the electrical pulse modulation is different from the expected direction, supplements with a default electrical signal (which has the characteristics of smoothness and safety), and discharges residual electricity. Residual electricity is the residue caused by dynamic electrical switches, which is actively discharged to the ground plane (energy is released by resistance) through a circuit, which can protect the human body from being burned by residual electrical current.

[0073] The limited protection processed electric signal is transmitted to the transcranial electric stimulation left electrode and the transcranial electric stimulation right electrode, the transcranial electric stimulation left electrode and the transcranial electric stimulation right electrode act on the two ends of the forehead of the skull for effective stimulation, the skull region is stimulated by using low-intensity current (1-2 ma), the excitability of the neurons in the left frontal gyrus part of the brain can be effectively enhanced, and thus the function of the brain electrical value of the measured person is enhanced and improved.

[0074] The terminal integrated receiver has a second wireless device, which can be Bluetooth, for wireless communication with the first wireless device. The brain electrical signal collected by the brain electrical signal collection device and the stimulation electric wave data output by the transcranial electric stimulation device are transmitted to the terminal integrated receiver through the wireless communication mode. The terminal integrated receiver is connected to the feedback calculation module through a connection line, such as a USB cable. The terminal integrated receiver transmits the brain electrical signal and the stimulation electric wave data to the feedback calculation module through the wired mode. The feedback calculation module runs on a PC, a tablet computer or the like. According to the analysis result based on the brain electrical data and the currently configured electric stimulation parameters, the feedback calculation module re-computes new stimulation parameters, and sends the new stimulation parameters to the slave machine part through the terminal integrated receiver. The slave machine part reconfigures the frequency, period and pulse width and the like of the stimulation current according to the new parameters, and starts the next round of stimulation process.

[0075] Due to the characteristics of weak amplitude, strong randomness and easy interference of the brain electrical signal, the brain electrical signal collection device should have high input impedance, high common mode rejection ratio and high safety performance and the like in order to accurately extract the brain electrical signal. However, the voltage applied by the transcranial electric stimulation is high, and therefore, from the technical point of view, the two cannot work at the same time. Limited by this, the embodiment designs a time-sharing working mechanism to complete the collection of the brain electrical signal and the transcranial electric stimulation.

[0076] The feedback stimulation method of the embodiment is executed by using the above brain-computer interface combined with the fusion system of the transcranial electric stimulation, and the specific execution steps are as follows.

[0077] The brain electrical signal collection left electrode and the brain electrical signal collection right electrode of the brain electrical signal collection device are worn on the left brain and the right brain forehead of the measured person, the ear electrode is clamped on the earlobe, the transcranial electric stimulation device is worn on the left brain and the right brain forehead of the measured person, the transcranial electric stimulation left electrode and the transcranial electric stimulation right electrode are located on the two sides of the brain electrical signal collection left electrode and the brain electrical signal collection right electrode, and then the following steps are performed.

[0078] S1, after the device is powered on, the brain electrical signal collection device collects the brain electrical data of the measured person in a resting state, and the data is transmitted to the feedback calculation module through a wireless mode.

[0079] S2, the feedback calculation module calculates the baseline parameters in the resting state, and the calculation specifically converts the initial electroencephalogram data in the time domain mode into the frequency domain mode by a fast Fourier transform algorithm (FFT) or a wavelet transform algorithm to obtain frequency domain electroencephalogram data, that is, one set of frequency domain electroencephalogram data per second, each set containing the spectral intensity data of two leads of the left brain and the right brain, and the two leads are divided into the same number of frequency bands, for example, the data of each lead is divided into the same 5 frequency bands, including the data of 5 frequency bands of δ wave, θ wave, α wave, β wave and γ wave, and 10 frequency domain data of two leads of the left brain and the right brain are obtained per second, wherein the frequency band of δ wave is 1-3 Hz, the frequency band of θ wave is 4-7 Hz, the frequency band of α wave is 8-12 Hz, the frequency band of β wave is 13-30 Hz, and the frequency band of γ wave is 31-50 Hz.

[0080] The first parameter set is calculated as follows: Formula: , In the above formula, P iL is the spectral intensity of the left brain in the i-th frequency band, P iR is the spectral intensity of the right brain in the i-th frequency band, and t is the electroencephalogram data length. The P i of the plurality of frequency bands constitutes the first parameter set.

[0081] The first parameter A0 is calculated as follows: Formula: , In the above formula, n is the number of frequency bands, and if the data of each lead is divided into 5 frequency bands, then n=5.

[0082] The second parameter B0 is calculated as follows: The second parameter value is calculated from the data of 2 frequency bands extracted from a plurality of frequency bands, which can be the data of 2 frequency bands of θ wave (4-7 Hz) and β wave (13-30 Hz).

[0083] Formula: ,

[0084] In the above formula, M LT is the spectral intensity value of the first frequency band of the left brain at time T, N LT is the spectral intensity value of the second frequency band of the left brain at time T, M RT is the spectral intensity value of the first frequency band of the right brain at time T, N RT is the spectral intensity value of the second frequency band of the right brain at time T, and t is the electroencephalogram data length.

[0085] S3, the initial setting value of the transcranial electrical stimulation parameter is used for electrical stimulation.

[0086] S4, after a period of electrical stimulation is completed, stop the stimulation, and then the electroencephalogram signal acquisition device acquires the electroencephalogram signal value of the measured person again, and after a period of electroencephalogram signal is acquired, the electroencephalogram data and the electrical stimulation parameter value of the transcranial electrical stimulation device are sent to the feedback calculation module.

[0087] S5, taking the electroencephalogram data obtained in step S4, re-calculating the first parameter and the second parameter in the manner of step S2 to obtain a new first parameter A1 and a new second parameter B1, and the re-calculation process is specifically as follows.

[0088] The collected electroencephalogram data of the left brain and the right brain of the two leads for a time t is converted into a frequency domain mode by a fast Fourier transform algorithm or a wavelet transform algorithm for frequency spectrum analysis of the initial electroencephalogram data in the time domain mode, to obtain frequency domain electroencephalogram data, which has a group per second, and each group contains frequency spectrum intensity data of the left brain and the right brain of two leads, the two leads are divided into the same five frequency bands, including data of five frequency bands of delta wave, theta wave, alpha wave, beta wave and gamma wave, and 10 frequency domain data of the left brain and the right brain are obtained per second, wherein the frequency band of the delta wave is 1-3 Hz, the frequency band of the theta wave is 4-7 Hz, the frequency band of the alpha wave is 8-12 Hz, the frequency band of the beta wave is 13-30 Hz, and the frequency band of the gamma wave is 31-50 Hz.

[0089] The first parameter set is calculated as follows: Formula: , In the above formula, P iL is the left brain frequency spectrum intensity of the i-th frequency band, P iR is the right brain frequency spectrum intensity of the i-th frequency band, and t is the electroencephalogram data time length; and the P i of multiple frequency bands constitute the first parameter set; The first parameter A1 is recalculated as follows: Formula: , In the above formula, n is the number of divided frequency bands; The second parameter B1 is recalculated as follows: The second parameter value is calculated by extracting 2 frequency band data from multiple frequency bands, which can be data of the theta wave (4-7 Hz) and the beta wave (13-30 Hz).

[0090] Formula: ,

[0091] In the above formula, M LT is the frequency spectrum intensity value of the first frequency band of the left brain at T time, N LT is the frequency spectrum intensity value of the second frequency band of the left brain at T time, and M RTis the spectral intensity value of the first frequency band of the right brain at time T, N RT is the spectral intensity value of the second frequency band of the right brain at time T, and t is the length of the brain electrical data.

[0092] The third parameter P1 is calculated: , The fourth parameter Q1 is calculated: .

[0093] S6, according to the values of P1 and Q1, adjust the parameters of the electrical stimulation signal, respectively adjust the frequency and pulse width of the electrical stimulation, and the adjustment method is as follows.

[0094] (1) According to the value of P1, adjust the stimulation frequency on the basis of the initial basic frequency, the new frequency = basic frequency *[1+(K1*P1) / 100], wherein K1 is the frequency adjustment coefficient, the value is between 0 and 1, and P1 is the third parameter value calculated at the current time.

[0095] (2) According to the value of Q1, adjust the pulse width of the stimulation on the basis of the initial basic pulse width, the new pulse width adjustment = basic pulse width *[1+(K2*Q1) / 100], wherein K2 is the pulse width adjustment coefficient, the value is between 0 and 1, and Q1 is the fourth parameter value calculated at the current time.

[0096] According to the new adjusted parameters, electrical stimulation is carried out.

[0097] Repeat the actions of steps S4-S6 to realize the electrical stimulation process based on the brain electrical feedback. The repeated steps S4-S6 can be performed in the following manner.

[0098] S7, after the electrical stimulation of step S6 is completed for a period of time, stop the stimulation process, and then the brain electrical signal collector collects the brain electrical signal values of the measured person again. After collecting the brain electrical signal for a period of time, the brain electrical data and the electrical stimulation parameter values of the transcranial electrical stimulation device are sent to the feedback calculation module.

[0099] S8, according to step S2, recalculate the brain electrical parameters to obtain new third parameter P2 and new fourth parameter Q2, and then adjust the parameters of the electrical stimulation signal according to the values of P2 and Q2, and then start the next round of electrical stimulation. Subsequently, the process is repeated according to this step, thereby realizing the electrical stimulation process based on the brain electrical feedback.

[0100] The above process can be operated, fed back, and summarized, and then matched with big data comparison to match similar electrical value intensity-duration curve-electrical stimulation waveform model, quickly generate electrical stimulation signal, and deliver the matched electrical stimulation signal to the slave part of the system, and then to the biological tissue for stimulation.

[0101] Among the above feedback stimulation methods, the electroencephalogram acquisition device collects the electroencephalogram signal values of the subject in time periods, and the transcranial electrical stimulation device initially uses a default value to perform micro-current stimulation, for example, the transcranial electrical stimulation device applies a low-intensity current (1-2 ma) to the brain to regulate neuronal activity and achieve the effect of neural regulation. At the same time, the current data and state values are transmitted to the PC end with a feedback calculation module through Bluetooth. The feedback calculation module analyzes the electroencephalogram signal in real time after receiving the real-time data, and designs an electrical stimulation waveform that can effectively induce neuronal excitation and improve the electroencephalogram value. After digitizing this feedback signal, it is transmitted back to the MCU through a wireless device, and the MCU controls the transcranial electrical stimulation device to perform corresponding stimulation, thereby forming an effective closed-loop biofeedback.

[0102] The present application combines the brain-computer interface and the transcranial electrical stimulation device by collecting electroencephalogram signals, which can provide a highly integrated effect. The electroencephalogram signals can capture the brain activity signals of the experimenter, such as brain waveforms, attention levels, and emotional states. By analyzing and interpreting these signals, the transcranial electrical stimulation can be used to make beneficial adjustments to the brain state. This personalized stimulation scheme can specifically regulate brain activity to improve cognitive function, emotional state, or other nervous system-related problems.

[0103] The combination of brain-computer interface technology and transcranial electrical stimulation technology has potential clinical application prospects. For example, in the field of neural rehabilitation, by monitoring the brain activity patterns of patients and combining transcranial electrical stimulation for intervention, the rehabilitation process can be accelerated and the rehabilitation effect can be improved. In the treatment of neuropsychiatric diseases, a personalized brain-computer interface combined with transcranial electrical stimulation treatment scheme can provide more effective treatment for patients, reduce symptoms, and improve quality of life.

[0104] It should be noted that the fusion system and feedback stimulation method can be applied to humans and other animals, such as monkeys, for scientific research activities.

[0105] Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent replacements to some technical features, and any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A fusion system of brain-computer interface combined with transcranial electrical stimulation, characterized in that, The system comprises a host part, a slave part, a PCB substrate, a terminal integrated receiver and a feedback calculation module. The host part comprises an electroencephalogram signal acquisition device and a transcranial electrical stimulation device, both of which are installed on the PCB substrate. The slave part comprises an MCU and a first wireless device, both of which are installed on the PCB substrate; the electroencephalogram signal acquisition device, the transcranial electrical stimulation device and the first wireless device are all connected to the MCU. The slave part further comprises a battery, which is connected to the MCU, the electroencephalogram signal acquisition device and the transcranial electrical stimulation device; the transcranial electrical stimulation device has a conversion module for converting the power supplied by the battery into pulsed electric waves. The terminal integrated receiver has a second wireless device for wireless communication with the first wireless device; the terminal integrated receiver is connected to the feedback calculation module.

2. The fusion system of a brain-machine interface combined with transcranial electrical stimulation according to claim 1, characterized in that, The conversion module comprises a step-up circuit part, a pulse modulation part and a protection device connected in sequence; the battery is connected to the step-up circuit part.

3. The fusion system of a brain-machine interface combined with transcranial electrical stimulation according to claim 2, characterized in that, The transcranial electrical stimulation device has a transcranial electrical stimulation left electrode and a transcranial electrical stimulation right electrode; the protection device is connected to the transcranial electrical stimulation left electrode and the transcranial electrical stimulation right electrode.

4. The fusion system of a brain-machine interface combined with transcranial electrical stimulation according to claim 3, characterized in that, The electroencephalogram signal acquisition device has an electroencephalogram acquisition left electrode, an electroencephalogram acquisition right electrode and an ear electrode; the ear electrode comprises an ear clip and an ear wire, and the ear clip is connected to the end of the ear wire.

5. A brain-machine interface feedback stimulation method in combination with transcranial electrical stimulation, characterized by, The system is used to perform the following steps: the electroencephalogram signal acquisition device is worn on the left and right brains of a subject, and the transcranial electrical stimulation device is worn on the left and right brains of the subject, and feedback stimulation is performed. S1, the electroencephalogram signal acquisition device acquires electroencephalogram data of the subject in a resting state and transmits the data to the feedback calculation module; S2, the feedback calculation module calculates baseline parameters in the resting state, specifically, the acquired electroencephalogram data of the left and right brains of the subject for a time period t are converted from time-domain mode to frequency-domain mode by a fast Fourier transform algorithm or a wavelet transform algorithm to obtain frequency-domain electroencephalogram data, each second of the frequency-domain electroencephalogram data has a group, and each group contains spectral intensity data of the left and right brains of the subject, and the two leads are divided into the same number of frequency bands; S3, the initial set value of the transcranial electrical stimulation parameter is used for electrical stimulation; S4, after a period of electrical stimulation, the stimulation is stopped, and then the electroencephalogram signal acquisition device acquires the electroencephalogram signal value of the subject again, and after a period of electroencephalogram signal acquisition, the electroencephalogram data and the electrical stimulation parameter value of the transcranial electrical stimulation device are transmitted to the feedback calculation module; S5, the electroencephalogram data obtained in step S4 are recalculated to obtain a group of feedback parameters according to the method of calculating baseline parameters in step S2; S6, the feedback calculation module calculates a feedback index parameter according to the baseline parameters and the feedback parameters, adjusts the electrical stimulation parameter of the transcranial electrical stimulation device according to the index parameter, and performs electrical stimulation according to the newly adjusted parameter.

6. The brain-computer interface method with feedback stimulation of transcranial electrical stimulation according to claim 5, characterized in that, In step S2, the data of each lead is divided into the same 5 frequency bands, including 5 frequency band data of delta wave, theta wave, alpha wave, beta wave and gamma wave, 10 frequency domain data of left and right brain leads are obtained every second, wherein the frequency band of delta wave is 1-3Hz, the frequency band of theta wave is 4-7Hz, the frequency band of alpha wave is 8-12Hz, the frequency band of beta wave is 13-30Hz, and the frequency band of gamma wave is 31-50Hz.

7. The brain-computer interface method with feedback stimulation of transcranial electrical stimulation according to claim 5 or 6, characterized in that, Step S2 calculates baseline parameters in the resting state, including first calculating a first parameter set P i and then calculating a first parameter A0 and a second parameter B0; ， In the above formula, P iL is the left brain spectral intensity of the i-th frequency band, P iR is the right brain spectral intensity of the i-th frequency band, and t is the brain electrical data time length; the P i of multiple frequency bands constitutes a first parameter set; ， In the above formula, n is the number of divided frequency bands; ， In the above formula, M LT is the spectral intensity value of the first frequency band of the left brain at time T, N LT is the spectral intensity value of the second frequency band of the left brain at time T, M RT is the spectral intensity value of the first frequency band of the right brain at time T, N RT is the spectral intensity value of the second frequency band of the right brain at time T, and t is the length of the brain electrical data.

8. The brain-computer interface method with feedback stimulation of transcranial electrical stimulation according to claim 7, characterized in that, In step S5, the recalculated feedback parameters include first parameters A1 and second parameters B1 calculated after the first parameters P i are calculated. ， In the above formula, P iL is the left brain spectral intensity of the i-th frequency band, P iR is the right brain spectral intensity of the i-th frequency band, and t is the brain electrical data time length; the P i of multiple frequency bands constitutes the first parameter set; ， In the above formula, n is the number of divided frequency bands; ， In the above formula, M LT is the spectral intensity value of the first frequency band of the left brain at time T, N LT is the spectral intensity value of the second frequency band of the left brain at time T, M RT is the spectral intensity value of the first frequency band of the right brain at time T, N RT is the spectral intensity value of the second frequency band of the right brain at time T, and t is the length of the brain electrical data.

9. The brain-computer interface method with feedback stimulation of transcranial electrical stimulation according to claim 8, characterized in that, In step S6, the index parameters include a third parameter P1 and a fourth parameter Q1. ， ， According to the values of P1 and Q1, the parameters of the electric stimulation signal are adjusted, and the electric stimulation frequency and pulse width of the transcranial electric stimulation device are adjusted respectively, and the adjustment mode is as follows: (1) According to the value of P1, the stimulation frequency is adjusted on the basis of the initial basic frequency, and the new frequency is basic frequency*[1+(K1*P1) / 100], wherein K1 is a frequency adjustment coefficient, the value is between 0 and 1, and P1 is the third parameter value calculated at the current moment; (2) According to the value of Q1, the pulse width of the stimulation is adjusted on the basis of the initial basic pulse width, and the new pulse width is basic pulse width*[1+(K2*Q1) / 100], wherein K2 is a pulse width adjustment coefficient, the value is between 0 and 1, and Q1 is the fourth parameter value calculated at the current moment; The electric stimulation is performed according to the new adjusted frequency and pulse width parameters.

10. The brain-computer interface method with feedback stimulation of transcranial electrical stimulation according to claim 9, characterized in that, The actions of steps S4-S6 are repeated to realize the electric stimulation process based on electroencephalogram feedback.

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