An adaptive transcranial electrical stimulation method and system

Abstract

The present invention discloses an adaptive transcranial electrical stimulation method and system, and relates to the technical field of transcranial electrical stimulation equipment. The method and system acquire the EEG data of the subject and transmit it to a brain activity analysis module to calculate the real-time EEG index and judge whether the EEG is abnormal, and record the abnormal target, the number N of abnormal frequency segments and the abnormal frequency segment; in the target selection module, the stimulation target is adaptively determined based on the abnormal target and the number N of abnormal frequency segments; in the stimulation waveform generation module, an adaptive stimulation waveform is generated based on the abnormal target, the number N of abnormal frequency segments and the abnormal frequency segment; in the stimulation generation device, continuous electrical stimulation is achieved based on the stimulation target and the stimulation waveform until the abnormality disappears. The transcranial electrical stimulation method and system can automatically select a suitable stimulation target in real time according to the brain activity state, and at the same time, can modify the stimulation waveform, frequency, duration, amplitude and other parameters in real time according to the brain activity state to adapt to various different diseases.

Description

Technical Field

[0001] The present invention relates to the technical field of transcranial electrical stimulation equipment, and in particular to an adaptive transcranial electrical stimulation method and system. Background Art

[0002] Transcranial electrical stimulation mainly includes transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS). It refers to different types of current stimulation given to the brain area from the scalp, which has a very significant regulatory effect on perception, cognitive behavior, motor dysfunction, etc. Traditional transcranial electrical stimulation outputs a single and fixed electrical stimulation, such as direct current, sine wave, etc. Once the output parameters are determined, they cannot be changed.

[0003] As research on non-invasive brain stimulation continues to deepen, more and more studies have found that the effect of transcranial electrical stimulation is state-dependent, that is, the stimulation regulation effect (from very effective to almost ineffective) is closely related to the user's current brain activity state. However, the waveform and related parameters (frequency, amplitude, stimulation duration, etc.) output by traditional transcranial electrical stimulation are fixed. If the user's brain activity changes, the electrical stimulation will not change accordingly, and it is not adaptive. Therefore, for exactly the same stimulation paradigm, the regulation effect of different individuals may vary greatly. This limits the role of traditional transcranial electrical stimulation.

[0004] The new transcranial electrical stimulation technology collects individual EEG or other state signals, extracts the characteristic quantity of the signal, and changes the stimulation parameters, waveforms, targets, etc. according to certain conditions to apply specific stimulation. This closed-loop stimulation form is closely related to the user's brain state and has better adaptability. However, the electrical stimulation generated by the existing technology is still relatively fixed, that is, only some parameters, targets or waveforms can be changed. In addition, the existing technology is mostly aimed at a certain type of disease, and the developed equipment is not flexible. Therefore, an adaptive transcranial electrical stimulation that can adaptively generate waveforms, adaptively select targets, and adapt to a variety of diseases is a very promising technology.

[0005] The existing disclosed technology (device for improving sleep through real-time asynchronous transcranial electrical stimulation CN115212456B) collects the user's EEG signals and sets different stimulation parameters, such as amplitude, frequency, phase, etc., but can only output sine waves and cannot generate more waveforms, such as DC and high-level coupling waveforms.

[0006] The existing disclosed technology (individualized cognitive function regulation device based on cross-frequency coupling CN115487418A) uses the user's frontal lobe theta oscillation and gamma oscillation to change the output stimulation target, intensity, frequency, and coupling waveform (peak nesting, trough nesting). However, the stimulation targets are limited to F3, F4, P3, and P4, which is not suitable for the international standard 64 leads, and the coupling method it provides is single, and it cannot provide most common coupling methods, such as phase-amplitude coupling PAC, phase-phase coupling PPC, amplitude-amplitude coupling AAC, etc.

[0007] The existing disclosed technology (individualized cognitive function regulation device based on cross-frequency coupling CN115487418A) uses magnetic resonance to obtain the user's brain state, and then selects the target point and current for electrical stimulation. This technology needs to be used in conjunction with magnetic resonance, which is costly and complicated to operate. In addition, the output electrical stimulation does not contain frequency, coupling waveform, etc., and has a limited scope of application. Summary of the invention

[0008] Based on the technical problems existing in the background technology, the present invention proposes an adaptive transcranial electrical stimulation method and system to achieve adaptive electrical stimulation, and can expand EEG indicators and modify normal human EEG data, so that the system can adapt to various different diseases.

[0009] The present invention provides an adaptive transcranial electrical stimulation method, comprising the following steps:

[0010] Step 1, obtain abnormal target information: collect the EEG data of the subject and preprocess it to obtain pure real-time EEG data, set a sliding window in the time domain, convert the real-time EEG data of all targets in the sliding window and the EEG data of normal people to the frequency domain, divide them into segments according to frequency, calculate the real-time EEG index and the EEG index of normal people in each segment, and perform a t-test on the power in the real-time EEG index of each segment and the power in the corresponding EEG index of normal people. If the significance probability P<0.05, it is considered that the subject's EEG is abnormal, and the abnormal target, the number of abnormal frequency segments N and the abnormal frequency segment are recorded;

[0011] Step 2, determine the stimulation target: traverse the number N of abnormal frequency segments of all targets in the sliding window, take the targets with N ≥ 1 as abnormal targets, check the adjacent targets with the abnormal target as the center, and record the number of adjacent targets that are abnormal targets, traverse all abnormal targets, screen out the abnormal target with the largest number of adjacent abnormal targets, and take the one with the largest EEG amplitude corresponding to the screened abnormal targets as the stimulation target;

[0012] Step 3, electrical stimulation: construct an adaptive stimulation waveform based on the real-time EEG index of the target point in the sliding window, the pre-stored EEG index of normal people, the abnormal target point, the number N of abnormal frequency segments and the abnormal frequency segment, and use the stimulation target point as the anode of electrical stimulation. According to the system setting, use the central symmetrical target point or the adjacent target point as the cathode for electrical stimulation;

[0013] Step 4: loop step 1 to step 3, combine the real-time updated sliding window data, switch the stimulation target, modify the stimulation waveform and parameters, and achieve adaptive electrical stimulation until the abnormal target disappears.

[0014] Further, in step three, according to the system setting, the central symmetrical target or the adjacent target is used as the cathode, specifically:

[0015] Set the number of targets to be used as cathodes and use the stimulated targets as anodes;

[0016] When the number of cathodes is greater than or equal to 2, the target point adjacent to the stimulation target point is used as the cathode;

[0017] When the number of cathodes is equal to 1, in the brain plane, with the midpoint of the brain plane as the center, the target point corresponding to the center of the stimulation target point is used as the cathode.

[0018] Furthermore, in step 1, the real-time EEG index of each segment and the EEG index of a normal person are calculated, as follows:

[0019] Calculate real-time EEG indicators in the time domain and frequency domain, including power, average amplitude, power ratio, power spectrum density, phase, and real-time amplitude of common frequencies;

[0020] Calculate network connection indicators, wherein the network connection indicators include a phase lag index, a weighted phase lag index, a phase lock value, and a weighted phase lock value.

[0021] Further, in step three, an adaptive stimulation waveform is constructed based on the real-time EEG index of the target point in the sliding window, the pre-stored EEG index of normal people, the abnormal target point, the number of abnormal frequency segments N and the abnormal frequency segment. The parameters of the adaptive stimulation waveform include the stimulation waveform amplitude, the stimulation waveform frequency, and the stimulation waveform duration, specifically:

[0022] Based on the average amplitude of the real-time EEG indicators in the sliding window, the stimulation waveform amplitude is obtained;

[0023] When the number of abnormal frequency segments N is equal to 1, and When , the stimulus waveform is displayed as DC, and the stimulus waveform amplitude is used as the DC voltage, where represents the average amplitude of the abnormal frequency band, It represents the average amplitude of the same frequency band of normal people;

[0024] When the number of abnormal frequency segments N is equal to 1, and When , the stimulation waveform frequency selects the frequency corresponding to the maximum amplitude in the abnormal frequency segment, the stimulation waveform is displayed as a sine wave, the frequency selects the frequency corresponding to the maximum amplitude in the abnormal frequency segment, and the amplitude is the stimulation waveform amplitude;

[0025] When the number of abnormal frequency segments N is greater than or equal to 2, the two abnormal frequency segments with the largest amplitude of the stimulation waveform are selected as coupling objects, and are divided into low frequency and high frequency according to the frequency size. The stimulation waveform is displayed as a coupled waveform.

[0026] Furthermore, when the number of abnormal frequency segments N is greater than or equal to 2, the two frequency segments with the largest amplitudes are selected as coupling objects, which are divided into low frequency and high frequency according to the frequency size. The stimulation waveform is displayed as a coupled waveform, specifically including:

[0027] When the number of abnormal frequency segments N is greater than or equal to 2, the two abnormal frequency segments with the largest amplitude are selected as coupling objects, and divided into low frequency and high frequency according to the frequency size. All low-frequency phases and high-frequency amplitudes in the sliding window are extracted. If the low-frequency phase corresponding to the maximum high-frequency amplitude is always consistent, the electrical stimulation adopts phase-amplitude coupling APC;

[0028] When the number of abnormal frequency segments N is greater than or equal to 2, and the electrical stimulation is not phase-amplitude coupling APC, the two abnormal frequency segments with the largest amplitude are selected as coupling objects, and they are divided into low frequency and high frequency according to the frequency size. All low-frequency amplitudes and high-frequency amplitudes in the sliding window are extracted. If the maximum high-frequency amplitude corresponds to the maximum low-frequency amplitude, and the minimum high-frequency amplitude corresponds to the minimum low-frequency amplitude, then the electrical stimulation adopts amplitude-amplitude coupling AAC;

[0029] When the number of abnormal frequency segments N is greater than or equal to 2, and the electrical stimulation is not phase-amplitude coupling APC and amplitude-amplitude coupling ACC, the two abnormal frequency segments with the largest amplitude are selected as coupling objects, and they are divided into low frequency and high frequency according to the frequency size. All low-frequency phases and high-frequency phases in the sliding window are extracted, and multiple low-frequency cycles are taken. The corresponding high-frequency cycle in each cycle is a fixed value, and the electrical stimulation adopts phase-phase coupling PPC.

[0030] An adaptive transcranial electrical stimulation system includes a brain activity analysis module, a target selection module, a stimulation waveform generation module, and a stimulation generation device;

[0031] The brain activity analysis module is used to obtain abnormal target information: obtain the EEG data of the subject and preprocess it to obtain pure real-time EEG data, set a sliding window in the time domain, convert the real-time EEG data of all targets in the sliding window and the EEG data of normal people into the frequency domain, divide them into segments according to frequency, calculate the real-time EEG index and the EEG index of normal people in each segment, and perform a t-test on the power in the real-time EEG index of each segment and the power in the corresponding EEG index of normal people. If the significance probability P<0.05, it is considered that the subject's EEG is abnormal, and the abnormal target, the number of abnormal frequency segments N and the abnormal frequency segment are recorded;

[0032] The target selection module is used to determine the stimulation target: traverse the number N of abnormal frequency segments of all targets in the sliding window, take the targets with N ≥ 1 as abnormal targets, check the adjacent targets with the abnormal target as the center, and record the number of adjacent targets that are abnormal targets, traverse all abnormal targets, screen out the abnormal target with the largest number of adjacent abnormal targets, and take the one with the largest EEG amplitude corresponding to the screened abnormal targets as the stimulation target;

[0033] The stimulation waveform generation module is used for electrical stimulation: based on the real-time EEG index of the target point in the sliding window, the pre-stored EEG index of normal people, the abnormal target point, the number N of abnormal frequency segments and the abnormal frequency segment, an adaptive stimulation waveform is constructed, the stimulation target point is used as the anode of electrical stimulation, and according to the system setting, the central symmetrical target point or the adjacent target point is used as the cathode for electrical stimulation;

[0034] The stimulation generating device is used to circulate the brain activity analysis module to the stimulation waveform generating module, and in combination with the real-time updated sliding window data, switches the stimulation target, modifies the stimulation waveform and parameters, and realizes adaptive electrical stimulation until the abnormal target disappears.

[0035] Furthermore, in the stimulation waveform generation module, according to the system setting, the central symmetrical target point or the adjacent target point is used as the cathode, specifically:

[0036] Set the number of targets to be used as cathodes and use the stimulated targets as anodes;

[0037] When the number of cathodes is greater than or equal to 2, the target point adjacent to the stimulation target point is used as the cathode;

[0038] When the number of cathodes is equal to 1, in the brain plane, with the midpoint of the brain plane as the center, the target point corresponding to the center of the stimulation target point is used as the cathode.

[0039] The advantages of the adaptive transcranial electrical stimulation method and system provided by the present invention are: (1) Adaptive electrical stimulation: the waveform, frequency, duration, amplitude and other parameters of the stimulation can be modified in real time according to the brain activity state; (2) Adaptive stimulation target: the appropriate stimulation target can be automatically selected in real time according to the brain activity state; (3) The coupled stimulation waveform can be generated: the PAC, AAC, and PPC coupled waveform algorithms are integrated, and in addition to the traditional DC and sine waves, various coupled waveforms can be generated as needed; (4) Expandable indications: the EEG indicators can be expanded and the normal human EEG data can be modified as needed, so that the system can adapt to various different diseases. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a structural schematic diagram of the present invention;

[0041] Figure 2 It is a work flow chart of the present invention;

[0042] Figure 3 Generate a flow chart for the stimulus waveform;

[0043] Figure 4 Select a sample image for your target. DETAILED DESCRIPTION

[0044] Below, the technical solution of the present invention is described in detail through specific embodiments. Many specific details are set forth in the following description to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific implementation disclosed below.

[0045] like Figures 1 to 4 As shown, an adaptive transcranial electrical stimulation method proposed by the present invention comprises the following steps:

[0046] Step 1, obtain abnormal target information: obtain the EEG data of the subject and preprocess it to obtain pure real-time EEG data, set a sliding window in the time domain, convert the real-time EEG data of all targets in the sliding window and the EEG data of normal people to the frequency domain, divide them into frequency segments, calculate the real-time EEG index and the EEG index of normal people in each segment, and perform a t-test on the power in the real-time EEG index of each segment and the power in the corresponding EEG index of normal people. If the significance probability P<0.05, it is considered that the subject's EEG is abnormal, and the abnormal target, the number of abnormal frequency segments N and the abnormal frequency segment are recorded;

[0047] Among them, the EEG acquisition device includes a 64-lead EEG cap and an amplifier. The subject wears the EEG cap to collect the subject's EEG data, and the subject's EEG data is transmitted to the brain activity analysis module through the amplifier for data analysis.

[0048] The brain activity analysis module preprocesses the EEG data of the subject and calculates various EEG indicators. The EEG evaluation indicators of different diseases are not exactly the same. This embodiment calculates all indicators as much as possible. These indicators can be used as research data to evaluate the state of the brain, and stimulation parameters can be set from some indicators. If there are uncalculated indicators, users can expand them by themselves; the steps for processing the EEG data of the subject are as follows:

[0049] 1) De-noise and eliminate artifacts from the EEG data of the subjects to obtain pure EEG data. De-noise uses bandpass filtering and notch technology, and artifact elimination uses the existing recursive least squares method.

[0050] 2) Set a sliding window of 1 second, convert the real-time EEG data of all targets in the sliding window and the EEG data of normal people into the frequency domain, and segment them by frequency (dela wave 0.5-4Hz, theta wave 4-8Hz, alpha wave 8-13Hz, beta wave 13-30Hz, gamma wave 30-50Hz).

[0051] 3) Calculate real-time EEG indicators in the time domain and frequency domain. Calculate the power (integral of amplitude within a certain period of time), average amplitude (average value of amplitude within a certain period of time), proportion (the proportion of EEG power in this frequency band to the entire frequency band), power spectrum density, phase, real-time amplitude, etc. of common frequencies (such as dela waves, theta waves, alpha waves, beta waves, and gamma waves).

[0052] 4) Calculate network connectivity indicators, such as phase lag index (PLI), weighted phase lag index (wPLI), phase locking value (PLV), weighted phase locking value (wPLV), etc., and provide the network connectivity indicators to users to judge the brain state.

[0053] 5) Extract the power of the real-time EEG index of each frequency band and compare it with the power of the corresponding normal person's EEG index for t-test. If the significance probability P<0.05, it is considered that the EEG is abnormal, and the abnormal target, the number of abnormal frequency bands N and the abnormal frequency band are recorded. Every time 10 new data are read, the data in the sliding window will be updated, and the brain activity analysis will be re-performed to keep it up to date and provide a basis for EEG stimulation.

[0054] It should be noted that, in this embodiment, 5 segments of data are obtained by frequency segmentation. After a t-test is performed on the two groups of data in each segment, if there are abnormalities in the dela wave, theta wave, and alpha wave, the number of abnormal frequency segments N is 3, and the abnormal frequency segments correspond to the dela wave, theta wave, and alpha wave.

[0055] The brain activity analysis module will automatically calculate the above indicators and send some results to the stimulation waveform generation module and the target selection module.

[0056] Step 2: Determine the stimulation target: traverse the number of abnormal frequency segments N of all targets in the sliding window, and take the targets with N ≥ 1 as abnormal targets. Check the adjacent targets with the abnormal target as the center, and record the number of adjacent targets that are abnormal targets. Traverse all abnormal targets, filter out the abnormal target with the largest number of adjacent abnormal targets, and take the one with the largest EEG amplitude corresponding to the filtered abnormal target as the stimulation target;

[0057] The target is both the target brain area for brain activity analysis and the target brain area for electrical stimulation. The target selection module can either fix the target or adaptively select the target. The fixed target is set before the system is enabled and cannot be modified during the entire process. After setting, EEG acquisition and analysis will be based on the set target. The adaptive target is determined by the comparison results between the real-time EEG indicators and the EEG indicators of normal people. In the adaptive case, brain activity analysis will be based on all targets. The electrical stimulation of this embodiment is based on the adaptively selected target. Specific examples are as follows: Figure 4 The specific calculation is as follows:

[0058] 1) Determine the abnormal target. Traverse all the targets and obtain the number of abnormal frequency segments N of all the targets. If N ≥ 1, the target is an abnormal target;

[0059] 2) Mark the number of adjacent abnormal targets. Take a certain abnormal target as the center, check the adjacent targets, and record the number of adjacent targets that are abnormal targets.

[0060] 4) Determine the stimulation target. Traverse all abnormal targets, select the abnormal target with the largest number of adjacent abnormal targets, and select the abnormal target with the largest EEG amplitude as the stimulation target (anode);

[0061] 5) Select the cathode according to the number of cathodes set before the system is started. Assuming that the number of cathodes is ≥ 2, after the stimulation target is determined, the adjacent target is selected as the cathode with the stimulation target as the center. Assuming that the number of cathodes = 1, after the stimulation target is determined, the target corresponding to the central symmetry with the midpoint of the brain plane as the center is selected as the cathode.

[0062] In order to provide a wide range of electrical stimulation to act on multiple brain areas at the same time, the cathode is set to 1, and the corresponding target point after the central symmetry is selected as the cathode. In order to focus the electrical stimulation on a specific brain area and improve the accuracy of electrical stimulation, the cathode is set to be greater than 1, and adjacent targets are selected as cathodes.

[0063] Step 3: Electrical stimulation: Based on the real-time EEG indicators of the target in the sliding window, the pre-stored EEG indicators of normal people, the abnormal target, the number of abnormal frequency segments N and the abnormal frequency segments, an adaptive stimulation waveform is constructed, and the stimulation target is used as the anode of the electrical stimulation. According to the system settings, the central symmetrical target or the adjacent target is used as the cathode, and the adaptive stimulation waveform is used as the electrical stimulation waveform for electrical stimulation;

[0064] The stimulation waveform generation module receives the real-time EEG indicators from the brain activity analysis module and the normal human EEG indicators from the data storage expansion module. This module can generate fixed stimulation waveforms according to demand, and can also generate adaptive stimulation waveforms according to the analysis results of the brain activity analysis module. The fixed stimulation waveform is set before the system is enabled and cannot be modified during the entire process. The adaptive waveform is determined by the comparison results between the real-time EEG indicators and the normal human EEG indicators. This embodiment adopts an adaptive stimulation waveform. The parameters of the adaptive stimulation waveform include the stimulation waveform amplitude, the stimulation waveform frequency, and the stimulation waveform duration. The adaptive stimulation waveform is specifically calculated as follows:

[0065] Stimulus waveform amplitude : The amplitude is equal to the average amplitude of the real-time EEG indicators in the sliding window.

[0066] ;

[0067] in, Indicates the number of real-time EEG data collected within a 1s sliding window. Indicates the real-time EEG amplitude.

[0068] Stimulation waveform frequency and stimulation waveform: The stimulation waveform generated is determined based on the number of abnormal frequency segments N, the abnormal frequency segments, and the amplitude change range, such as Figure 3 As shown in the following table:

[0069]

[0070] In addition, the duration of the stimulation waveform: when real-time EEG detects an abnormality, stimulation is generated until the abnormality disappears.

[0071] The electrical stimulation and EEG acquisition devices use the same electrode cap and electrodes. They receive the results from the stimulation waveform generation module and the target selection module. They generate corresponding electrical stimulation in real time according to the results, and can switch the target in real time.

[0072] Step 4: loop step 1 to step 3, combine the real-time updated sliding window data, switch the stimulation target, modify the stimulation waveform and parameters, and achieve adaptive electrical stimulation until the abnormal target disappears.

[0073] According to the switching of different real-time EEG data in the sliding window, the stimulation target and stimulation waveform under different real-time EEG data can be obtained, and then continuous electrical stimulation can be achieved by changing the stimulation target until the abnormality disappears.

[0074] In this implementation, a control interface and a data storage / expansion module are also provided. The control interface has three functions: system test function, auxiliary modification / expansion index, and system operation interface, as follows:

[0075] 1) System test function: In order to facilitate use and test the overall function of the system, the control interface can select the system to enter the system test function. This function supports one-click import of offline EEG data, and the brain activity analysis module analyzes the EEG indicators, and then calculates the required stimulation waveform and stimulation target. The stimulation waveform information and stimulation target information will be displayed on the test function interface. After the user confirms, the electrical stimulation output will be turned on. During the whole process, the working status and output data of each module can be observed.

[0076] 2) Auxiliary modification / expansion of indicators: The control interface can select the system to enter the auxiliary modification / expansion of indicators function. The user follows the prompts to enter the data that meets the requirements, such as normal human EEG data, required EEG indicators, indicator-related algorithms, etc. The control interface will check the input data, and if it meets the requirements, it will be transferred to the data storage expansion module for storage, and the default indicators, algorithms, data, etc. will be modified.

[0077] 3) System operation interface: The control interface can select the system to enter the system operation function. The operation interface when the system is in normal use can view the status of each module, output data and set related parameters in real time.

[0078] The data storage / expansion module includes two functions: normal human EEG data storage and EEG data / indicator expansion.

[0079] 1) Normal human EEG data storage. This module stores a large amount of normal human EEG data, and calculates normal human EEG indicators based on these data, which is convenient for comparison with real-time EEG data, so as to determine the appropriate electrical stimulation targets and stimulation parameters.

[0080] 2) EEG data / indicator expansion. Different diseases require different EEG indicators for evaluation, and the EEG data of normal people for comparison may also vary due to diseases, regions, etc. In order to expand the scope of application of the system as much as possible, it is allowed to enter new EEG data, EEG indicators and their algorithms through the control interface. After entering, all evaluations, stimulations and calculations will be based on the new data.

[0081] This embodiment has the following advantages:

[0082] 1) Adaptive electrical stimulation: the waveform, frequency, duration, amplitude and other parameters of stimulation can be modified in real time according to the state of brain activity;

[0083] 2) Adaptive stimulation targets: The appropriate stimulation targets can be automatically selected in real time according to the state of brain activity;

[0084] 3) Can generate coupled stimulation waveforms; this embodiment integrates PAC, AAC, and PPC coupled waveform algorithms, and can generate various coupled waveforms as needed in addition to traditional DC and sine waves;

[0085] 4) Comes with normal human EEG data and EEG indicator algorithms for common diseases;

[0086] 5) Expandable to adapt to different diseases. EEG indicators and EEG data can be modified and expanded as needed to adapt to a variety of different diseases, that is, the stimulation waveform and parameters can be modified on the terminal to improve the problems that currently need to be modified on the host computer, thereby improving human-computer interaction.

[0087] As an embodiment: system testing function.

[0088] 1. During the system test, the EEG acquisition device is not used.

[0089] Connect the electrodes of the stimulation generating device to the input of the oscilloscope to measure the waveform of the output electrical stimulation. Open the debugging control interface, select the system test function, and import the offline EEG data prepared in advance. The brain activity analysis module will automatically analyze and display the EEG indicators. After the user checks that everything is correct, it starts to calculate and display the stimulation waveform and stimulation target, including waveform, amplitude, frequency, stimulation target location, etc. After the user checks that everything is correct, it starts to generate electrical stimulation. The generated electrical stimulation will be collected and displayed by the oscilloscope as feedback. The debugging personnel will know the system working status and key data of each part based on the feedback from the oscilloscope and the process feedback of each module to determine whether the system function is correct.

[0090] 2. Adaptive transcranial electrical stimulation

[0091] Open the debugging control interface, select the system operation function, and complete the settings of basic information, cathode number, fixed target, fixed waveform, adaptive and other information. Under fixed target and fixed waveform, the system will generate electrical stimulation in the set way, which cannot be changed during the whole stimulation process. Under adaptive, the waveform and target will be determined by the system. Wear the EEG cap of the EEG acquisition device on the user's head, inject the conductive paste, and complete the impedance measurement (the impedance is required to be less than 5kΩ). Measure the user's EEG signal in real time, and the system will transmit the real-time data to the brain activity analysis module. The brain activity analysis module will automatically analyze the EEG signal. Some values ​​are transmitted to the stimulation waveform generation module and the target selection module. After receiving the data, the stimulation waveform generation module calculates the waveform, amplitude, frequency and other parameters. After receiving the data, the target selection module compares and analyzes it with the normal human EEG data in the data storage expansion module, and automatically selects the corresponding target. The stimulation generation device will open the corresponding stimulation channel (the rest are closed) to generate electrical stimulation according to the results of the two modules.

[0092] 3. Assisted modification / extension indicators

[0093] Open the debugging control interface and select the auxiliary modification / expanded indicator function. Enter new EEG data, EEG indicators and their algorithms according to the prompts. After entering, all evaluations, stimulations and calculations will be based on the new data.

[0094] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An adaptive transcranial electrical stimulation method, characterized in that: The steps include: Step 1, obtain abnormal target information: collect the EEG data of the subject and preprocess it to obtain pure real-time EEG data, set a sliding window in the time domain, convert the real-time EEG data of all targets in the sliding window and the EEG data of normal people to the frequency domain, divide them into segments according to frequency, calculate the real-time EEG index and the EEG index of normal people in each segment, and perform a t-test on the power in each segment of the real-time EEG index and the power in the corresponding normal people's EEG index. If the significance probability P<0.05, it is considered that the subject's EEG is abnormal, and the abnormal target, the number of abnormal frequency segments N and the abnormal frequency segment are recorded; Step 2, determine the stimulation target: traverse the number N of abnormal frequency segments of all targets, take the targets with N ≥ 1 as abnormal targets, check the adjacent targets with the abnormal target as the center, and record the number of adjacent targets that are abnormal targets, traverse all abnormal targets, screen out the abnormal target with the largest number of adjacent abnormal targets, and take the one with the largest EEG amplitude corresponding to the screened abnormal targets as the stimulation target; Step 3, electrical stimulation: construct an adaptive stimulation waveform based on the real-time EEG index of the target point in the sliding window, the pre-stored EEG index of normal people, the abnormal target point, the number N of abnormal frequency segments and the abnormal frequency segment, use the stimulation target point as the anode of electrical stimulation, and according to the system setting, use the central symmetrical target point or the adjacent target point as the cathode, and use the adaptive stimulation waveform as the electrical stimulation waveform to perform electrical stimulation; Step 4: loop step 1 to step 3, combine the real-time updated sliding window data, switch the stimulation target, modify the stimulation waveform and parameters, and achieve adaptive electrical stimulation until the abnormal target disappears.

2. The adaptive transcranial electrical stimulation method according to claim 1, characterized in that: In step 3, according to the system settings, the central symmetrical target or the adjacent target is used as the cathode, specifically: Set the number of targets to be used as cathodes and use the stimulated targets as anodes; When the number of cathodes is greater than or equal to 2, the target point adjacent to the stimulation target point is used as the cathode; When the number of cathodes is equal to 1, in the brain plane, with the midpoint of the brain plane as the center, the target point corresponding to the center of the stimulation target point is used as the cathode.

3. The adaptive transcranial electrical stimulation method according to claim 1, characterized in that: In step 1, the real-time EEG index and the normal EEG index of each segment are calculated by frequency segment, as follows: Calculate real-time EEG indicators in the time domain and frequency domain, including power, average amplitude, power ratio, power spectrum density, phase, and real-time amplitude of common frequencies; Calculate network connection indicators, wherein the network connection indicators include a phase lag index, a weighted phase lag index, a phase lock value, and a weighted phase lock value.

4. The adaptive transcranial electrical stimulation method according to claim 3, characterized in that: In step 3, an adaptive stimulation waveform is constructed based on the real-time EEG index of the target point in the sliding window, the pre-stored EEG index of normal people, the abnormal target point, the number of abnormal frequency segments N and the abnormal frequency segment. The parameters of the adaptive stimulation waveform include the stimulation waveform amplitude, the stimulation waveform frequency, and the stimulation waveform duration, specifically: Based on the average amplitude of the real-time EEG in the sliding window of the stimulation target, the stimulation waveform amplitude is obtained; When the number of abnormal frequency segments N of the stimulation target is equal to 1, and When , the stimulus waveform is displayed as DC, and the stimulus waveform amplitude is used as the DC voltage, where represents the average amplitude of the abnormal frequency band, It represents the average amplitude of the same frequency band of normal people; When the number of abnormal frequency segments N of the stimulation target is equal to 1, and When , the stimulation waveform is displayed as a sine wave, the frequency is selected to correspond to the maximum amplitude in the abnormal frequency band, and the amplitude is the stimulation waveform amplitude; When the number of abnormal frequency segments N of the stimulation target is greater than or equal to 2, the two abnormal frequency segments with the largest amplitudes are selected as coupling objects, and are divided into low frequency and high frequency according to the frequency size. The stimulation waveform is displayed as a coupled waveform.

5. The adaptive transcranial electrical stimulation method according to claim 4, characterized in that: When the number of abnormal frequency segments N is greater than or equal to 2, the two frequency segments with the largest amplitude are selected as coupling objects, which are divided into low frequency and high frequency according to the frequency size. The stimulation waveform is displayed as a coupled waveform, including: When the number of abnormal frequency segments N is greater than or equal to 2, the two abnormal frequency segments with the largest amplitude are selected as coupling objects, and divided into low frequency and high frequency according to the frequency size. All low-frequency phases and high-frequency amplitudes in the sliding window are extracted. If the low-frequency phase corresponding to the maximum high-frequency amplitude is always consistent, the electrical stimulation adopts phase-amplitude coupling APC; When the number of abnormal frequency segments N is greater than or equal to 2, and the electrical stimulation is not phase-amplitude coupling APC, the two abnormal frequency segments with the largest amplitude are selected as coupling objects, and they are divided into low frequency and high frequency according to the frequency size. All low-frequency amplitudes and high-frequency amplitudes in the sliding window are extracted. If the maximum high-frequency amplitude corresponds to the maximum low-frequency amplitude, and the minimum high-frequency amplitude corresponds to the minimum low-frequency amplitude, then the electrical stimulation adopts amplitude-amplitude coupling AAC; When the number of abnormal frequency segments N is greater than or equal to 2, and the electrical stimulation is not phase-amplitude coupling APC and amplitude-amplitude coupling AAC, the two abnormal frequency segments with the largest amplitude are selected as coupling objects, and they are divided into low frequency and high frequency according to the frequency size. All low-frequency phases and high-frequency phases in the sliding window are extracted, and multiple low-frequency cycles are taken. The corresponding high-frequency cycle in each cycle is a fixed value, and the electrical stimulation adopts phase-phase coupling PPC.

6. An adaptive transcranial electrical stimulation system, characterized in that: It includes a brain activity analysis module, a target selection module, a stimulation waveform generation module and a stimulation generation device; The brain activity analysis module is used to obtain abnormal target information: obtain the EEG data of the subject and preprocess it to obtain pure real-time EEG data, set a sliding window in the time domain, convert the real-time EEG data of all targets in the sliding window and the EEG data of normal people into the frequency domain, divide them into segments according to frequency, calculate the real-time EEG index and the EEG index of normal people in each segment, and perform a t-test on the power in the real-time EEG index of each segment and the power in the corresponding EEG index of normal people. If the significance probability P<0.05, it is considered that the subject's EEG is abnormal, and the abnormal target, the number of abnormal frequency segments N and the abnormal frequency segment are recorded; The target selection module is used to determine the stimulation target: traverse the number N of abnormal frequency segments of all targets in the sliding window, take the targets with N ≥ 1 as abnormal targets, check the adjacent targets with the abnormal target as the center, and record the number of adjacent targets that are abnormal targets, traverse all abnormal targets, screen out the abnormal target with the largest number of adjacent abnormal targets, and take the one with the largest EEG amplitude corresponding to the screened abnormal targets as the stimulation target; The stimulation waveform generation module is used for electrical stimulation: based on the real-time EEG index of the target point in the sliding window, the pre-stored EEG index of normal people, the abnormal target point, the number N of abnormal frequency segments and the abnormal frequency segment, an adaptive stimulation waveform is constructed, the stimulation target point is used as the anode of electrical stimulation, and according to the system setting, the central symmetrical target point or the adjacent target point is used as the cathode, and the adaptive stimulation waveform is used as the electrical stimulation waveform to perform electrical stimulation; The stimulation generating device is used to circulate the brain activity analysis module to the stimulation waveform generating module, and in combination with the real-time updated sliding window data, switches the stimulation target, modifies the stimulation waveform and parameters, and realizes adaptive electrical stimulation until the abnormal target disappears.

7. The adaptive transcranial electrical stimulation system according to claim 6, characterized in that: In the stimulation waveform generation module, according to the system settings, the central symmetrical target or the adjacent target is used as the cathode, specifically: Set the number of targets to be used as cathodes and use the stimulated targets as anodes; When the number of cathodes is greater than or equal to 2, the target point adjacent to the stimulation target point is used as the cathode; When the number of cathodes is equal to 1, in the brain plane, with the midpoint of the brain plane as the center, the target point corresponding to the center of the stimulation target point is used as the cathode.

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