A transcranial electrical stimulation combined with electroencephalogram data processing method, device and storage medium

Abstract

The present application relates to the technical field of neural regulation combined with EEG, and in particular to a transcranial electrical stimulation combined with EEG data processing method, device and storage medium. The method comprises: obtaining patient medical imaging information, and determining patient personality information based on the patient medical imaging information, wherein the patient personality information is a patient brain treatment reference parameter required to be collected by the patient during transcranial electrical stimulation; obtaining the patient's EEG signal, and determining EEG oscillation data based on the patient's EEG signal; if the EEG oscillation data meets a preset value, then determining the patient's high excitement state based on the EEG oscillation data and the patient's personality information; if the patient's high excitement state meets the preset high excitement state, then determining the stimulation timing based on the patient's high excitement state; and generating a transcranial electrical stimulation instruction based on the stimulation timing. The present application can improve the therapeutic effect of transcranial electrical stimulation.

Description

Technical Field

[0001] The present application relates to the field of neural regulation combined with electroencephalogram (EEG) technology, and in particular to a method, device, and storage medium for transcranial electrical stimulation combined with EEG data processing. Background Art

[0002] Transcranial Electrical Stimulation (TES), a non-invasive neuromodulation technology, has been widely used in neurorehabilitation, psychiatric treatment, and brain function regulation. This technology, which applies a weak electrical current to the scalp to modulate the excitability of neurons in the cerebral cortex, is primarily used to improve cognitive impairment, depression, and motor dysfunction.

[0003] However, traditional TES technology still has certain limitations in practical application, so how to improve the therapeutic effect of TES technology has become a current research hotspot. Traditional TES often uses fixed time interval stimulation or relies on manual experience and judgment, which cannot capture the brain's active state window in real time, resulting in a large amount of ineffective stimulation during the treatment process, thus resulting in poor TES treatment effect. Summary of the Invention

[0004] In order to improve the therapeutic effect of transcranial electrical stimulation, the present application provides a transcranial electrical stimulation combined with EEG data processing method, device and storage medium.

[0005] In a first aspect, the present application provides a method for transcranial electrical stimulation combined with EEG data processing, which adopts the following technical solutions:

[0006] A transcranial electrical stimulation combined with electroencephalogram (EEG) data processing method, comprising:

[0007] Acquiring medical imaging information of the patient, and determining individual patient information based on the medical imaging information of the patient, wherein the individual patient information is a reference parameter for brain treatment of the patient required to be collected during transcranial electrical stimulation;

[0008] Acquiring an electroencephalogram (EEG) signal from a patient, and determining EEG oscillation data based on the EEG signal from the patient;

[0009] If the EEG oscillation data meets a preset value, determining that the patient is in a high-excitement state based on the EEG oscillation data and the patient's personality information;

[0010] If the patient's high excitement state meets the preset high excitement state, determining the stimulation timing based on the patient's high excitement state;

[0011] Based on the stimulation timing, a transcranial electrical stimulation instruction is generated.

[0012] By adopting the above technical solution, after obtaining the patient's medical imaging information, the patient's medical imaging information is identified, the patient's personality information is determined, and the patient's personalized brain characteristics are clarified, making the treatment more targeted; by analyzing and processing the obtained patient's EEG information, the corresponding EEG oscillation data of the patient is obtained; the EEG oscillation data is compared with the preset value. If the EEG oscillation data meets the preset value, it means that the EEG oscillation data has reached the EEG oscillation data threshold corresponding to the patient's cerebral cortex high excitement state, and then the patient's high excitement state is determined based on the EEG oscillation data and the patient's personality information; then the patient's high excitement state is compared with the preset high excitement state to verify the patient's high excitement state. If the patient's high excitement state meets the preset high excitement state, it means that the patient is in a cerebral cortex happy state at this time, and then the stimulation timing is selected; then, according to the stimulation timing, the corresponding transcranial electrical stimulation instruction is generated, thereby improving the transcranial electrical stimulation treatment effect.

[0013] In a possible implementation, determining EEG oscillation data based on the patient's EEG signal includes:

[0014] Dividing the patient's EEG signal into frequency bands to determine the signal frequency band;

[0015] Calculating the EEG power spectral density based on the signal frequency band;

[0016] Determining an EEG oscillation pattern and an EEG signal energy distribution according to the EEG power spectrum density;

[0017] determining oscillation data based on the EEG oscillation pattern and the EEG signal energy distribution;

[0018] If the oscillation data is consistent with the preset oscillation data, it is determined that the oscillation data is brain electrical oscillation data.

[0019] In one possible implementation, determining the patient's high excitement state based on the EEG oscillation data and the patient's personality information includes:

[0020] Preprocessing the EEG oscillation data to obtain first EEG data;

[0021] Calculating an EEG characteristic value according to the first EEG data;

[0022] If the EEG characteristic value is consistent with the preset treatment threshold, determining the patient's symptom information based on the patient's personality information;

[0023] Determining abnormal EEG characteristics of the disease based on the patient's disease information;

[0024] Determining triggering conditions based on the abnormal EEG characteristics of the disease;

[0025] determining a stimulation mode according to the trigger condition;

[0026] determining characteristics of an EEG excitation state based on the stimulation pattern;

[0027] The patient's high excitement state is determined based on the EEG excitement state characteristics and the first EEG data.

[0028] In a possible implementation, determining the patient's high excitement state based on the EEG excitement state characteristic and the first EEG data includes:

[0029] dividing the first EEG data into frequency bands, and determining the first EEG data as second EEG data if the first EEG data meets the characteristics of an EEG excitement state;

[0030] determining target area coherence based on the second EEG data and the stimulation pattern;

[0031] If the target area coherence satisfies the preset target area coherence, the second EEG data is marked as the patient's high excitement state.

[0032] In a possible implementation, the step of determining the stimulation timing further includes:

[0033] Determining a treatment plan based on the patient's personality information and the patient's condition information;

[0034] determining treatment parameters based on the treatment plan;

[0035] Marking the target brain area for treatment according to the treatment parameters;

[0036] determining a treatment target based on the target treatment brain region and the treatment parameters;

[0037] Based on the therapeutic target, an electrode arrangement plan is determined.

[0038] In a possible implementation, the step of generating a transcranial electrical stimulation instruction based on the stimulation timing further includes:

[0039] Acquiring third EEG data, where the third EEG data is EEG data of the patient after transcranial electrical stimulation;

[0040] determining event-related spectral perturbations and inter-trial coherence based on the third EEG data;

[0041] generating an efficacy report based on the event-related spectral perturbation and the inter-trial coherence;

[0042] Determining data to be verified based on the efficacy report;

[0043] If the data to be verified is consistent with the preset verification data, maintaining the stimulation timing;

[0044] If the data to be verified is inconsistent with the preset verification data, an optimization solution is generated.

[0045] In a second aspect, the present application provides a transcranial electrical stimulation combined with EEG data processing device, which adopts the following technical solution:

[0046] A transcranial electrical stimulation combined with electroencephalogram (EEG) data processing device comprises: a patient personality information determination module, an EEG oscillation data determination module, a patient high excitement state determination module, a stimulation timing determination module, and a transcranial electrical stimulation instruction generation module, wherein:

[0047] A patient personality information determination module is configured to obtain patient medical imaging information and determine patient personality information based on the patient medical imaging information, wherein the patient personality information is a patient brain treatment reference parameter required to be collected during transcranial electrical stimulation;

[0048] an EEG oscillation data determination module, configured to obtain an EEG signal of a patient and determine EEG oscillation data based on the EEG signal of the patient;

[0049] a patient high excitement state determination module, configured to determine the patient's high excitement state based on the EEG oscillation data and the patient's personality information if the EEG oscillation data meets a preset value;

[0050] a stimulation timing determination module, configured to determine a stimulation timing based on the patient's high excitement state if the patient's high excitement state meets a preset high excitement state;

[0051] The transcranial electrical stimulation instruction generation module is used to generate a transcranial electrical stimulation instruction based on the stimulation timing.

[0052] By adopting the above technical solution, after obtaining the patient's medical imaging information, the patient's individual information determination module identifies the patient's medical imaging information, determines the patient's individual information, clarifies the patient's brain personalized characteristics, and makes the treatment more targeted; the EEG oscillation data determination module analyzes and processes the obtained patient's EEG information to obtain the EEG oscillation data corresponding to the patient; the patient's high excitement state determination module compares the EEG oscillation data with a preset value. If the EEG oscillation data meets the preset value, it means that the EEG oscillation data has reached the EEG oscillation data threshold corresponding to the patient's cerebral cortex high excitement state. Then, based on the EEG oscillation data and the patient's individual information, the patient's high excitement state is determined; then, the stimulation timing determination module compares the patient's high excitement state with the preset high excitement state to verify the patient's high excitement state. If the patient's high excitement state meets the preset high excitement state, it means that the patient is in a cerebral cortex excited state at this time, and then the stimulation timing is selected; then, the transcranial electrical stimulation instruction generation module generates a corresponding transcranial electrical stimulation instruction according to the stimulation timing, thereby improving the transcranial electrical stimulation treatment effect.

[0053] In a possible implementation, the EEG oscillation data determination module includes: a signal frequency band determination unit, an EEG power spectrum density determination unit, a first information determination unit, an oscillation data determination unit, and an EEG oscillation data determination unit, wherein:

[0054] a signal frequency band determination unit, configured to divide the patient's EEG signal into frequency bands to determine the signal frequency band;

[0055] an EEG power spectrum density determination unit, configured to calculate the EEG power spectrum density based on the signal frequency band;

[0056] a first information determining unit, configured to determine an EEG oscillation pattern and an EEG signal energy distribution according to the EEG power spectrum density;

[0057] an oscillation data determining unit, configured to determine oscillation data based on the EEG oscillation pattern and the EEG signal energy distribution;

[0058] The EEG oscillation data determining unit is configured to determine that the oscillation data is EEG oscillation data if the oscillation data is consistent with preset oscillation data.

[0059] In a possible implementation, the patient high excitement state determination module includes: a first EEG data determination unit, an EEG characteristic value determination unit, a patient symptom information determination unit, a symptom EEG abnormality feature determination unit, a trigger condition determination unit, a stimulation mode determination unit, an EEG excitement state feature determination unit, and a patient high excitement state determination unit, wherein,

[0060] a first EEG data determining unit, configured to pre-process the EEG oscillation data to obtain first EEG data;

[0061] an EEG characteristic value determining unit, configured to calculate an EEG characteristic value based on the first EEG data;

[0062] a patient symptom information determination unit, configured to determine the patient symptom information based on the patient personality information if the EEG characteristic value is consistent with a preset treatment threshold;

[0063] a disease EEG abnormality feature determination unit, configured to determine the disease EEG abnormality feature based on the patient's disease information;

[0064] a trigger condition determination unit, configured to determine a trigger condition based on the abnormal EEG characteristics of the disease;

[0065] a stimulation mode determining unit, configured to determine a stimulation mode according to the triggering condition;

[0066] an EEG excitement state characteristic determination unit, configured to determine the EEG excitement state characteristic based on the stimulation pattern;

[0067] The patient high excitement state determining unit is used to determine the patient's high excitement state according to the EEG excitement state characteristics and the first EEG data.

[0068] In a possible implementation, the patient high excitement state determination unit is specifically configured to:

[0069] dividing the first EEG data into frequency bands, and determining the first EEG data as second EEG data if the first EEG data meets the characteristics of an EEG excitement state;

[0070] determining target area coherence based on the second EEG data and the stimulation pattern;

[0071] If the target area coherence satisfies the preset target area coherence, the second EEG data is marked as the patient's high excitement state.

[0072] In a possible implementation, the transcranial electrical stimulation combined with EEG data processing device further includes: a treatment plan determination module, a treatment parameter determination module, a target treatment brain area determination module, a treatment target determination module, and an electrode arrangement plan determination module, wherein:

[0073] A treatment plan determination module, configured to determine a treatment plan based on the patient's personality information and the patient's symptom information;

[0074] a treatment parameter determination module, configured to determine treatment parameters based on the treatment plan;

[0075] a target treatment brain region determination module, configured to mark the target treatment brain region according to the treatment parameters;

[0076] a treatment target determination module, configured to determine a treatment target based on the target treatment brain region and the treatment parameters;

[0077] The electrode arrangement scheme determination module is used to determine the electrode arrangement scheme based on the treatment target.

[0078] In a possible implementation, the transcranial electrical stimulation combined with EEG data processing device further includes: a third EEG data acquisition module, a calculation module, a therapeutic effect report generation module, a to-be-verified data determination module, a comparison module, and an optimization solution generation module, wherein:

[0079] A third EEG data acquisition module is used to acquire third EEG data, where the third EEG data is the EEG data of the patient after transcranial electrical stimulation;

[0080] a calculation module, configured to determine event-related spectral disturbance and inter-trial coherence based on the third EEG data;

[0081] an efficacy report generating module, configured to generate an efficacy report based on the event-related spectral perturbation and the inter-trial coherence;

[0082] A module for determining data to be verified, configured to determine data to be verified based on the efficacy report;

[0083] a comparison module, configured to maintain the stimulation timing if the data to be verified is consistent with preset verification data;

[0084] The optimization solution generating module is used to generate an optimization solution if the data to be verified is inconsistent with the preset verification data.

[0085] In a third aspect, the present application provides an electronic device, which adopts the following technical solution:

[0086] An electronic device, comprising:

[0087] at least one processor;

[0088] Memory;

[0089] At least one application, wherein the at least one application is stored in the memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the above-mentioned transcranial electrical stimulation combined with EEG data processing method.

[0090] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution:

[0091] A computer-readable storage medium includes: a computer program stored therein that can be loaded by a processor and execute the above-mentioned transcranial electrical stimulation combined with electroencephalogram data processing method.

[0092] In summary, this application has the following beneficial technical effects:

[0093] After obtaining the patient's medical imaging information, the patient's medical imaging information is identified, the patient's personality information is determined, and the patient's personalized brain characteristics are clarified to make the treatment more targeted; by analyzing and processing the acquired patient's EEG information, the corresponding EEG oscillation data of the patient is obtained; the EEG oscillation data is compared with the preset value. If the EEG oscillation data meets the preset value, it means that the EEG oscillation data has reached the EEG oscillation data threshold corresponding to the patient's cerebral cortex high excitement state, and then the patient's high excitement state is determined based on the EEG oscillation data and the patient's personality information; then the patient's high excitement state is compared with the preset high excitement state to verify the patient's high excitement state. If the patient's high excitement state meets the preset high excitement state, it means that the patient is in a cerebral cortex happy state at this time, and then the stimulation timing is selected; then, according to the stimulation timing, the corresponding transcranial electrical stimulation instruction is generated; thereby improving the transcranial electrical stimulation treatment effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0094] Figure 1 This is a flowchart of the transcranial electrical stimulation combined with EEG data processing method of the present application;

[0095] Figure 2 It is a block diagram of the transcranial electrical stimulation combined with EEG data processing device of the present application;

[0096] Figure 3 It is a schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0097] The following is combined with Figure 1-3 This application is described in further detail.

[0098] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0099] The embodiments of the present application provide a transcranial electrical stimulation combined with EEG data processing method, which is performed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, a server cluster or distributed device composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smartphone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited to these. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, which is not limited in the embodiments of the present application.

[0100] Reference Figure 1 The method includes: step S101, step S102, step S103, step S104 and step S105, wherein:

[0101] Step S101: Acquire patient medical imaging information, and determine patient personality information based on the patient medical imaging information.

[0102] In the application embodiment, the patient's individual information is the patient's brain treatment reference parameters that need to be collected during transcranial electrical stimulation.

[0103] Specifically, after the patient receives MRI and / or CT examination, the electronic device will receive the patient's medical imaging information transmitted by the detection instrument, and then the electronic device will pre-process and correct the patient's medical imaging information; after receiving the corrected patient medical imaging information, the electronic device will extract structural features and functional features of the patient's medical imaging information to obtain characteristic information of the patient's brain; based on the characteristic information, the electronic device will extract the patient's brain treatment reference parameters required for transcranial electrical stimulation and set them as the patient's personal information, and at the same time, the electronic device will construct a brain model.

[0104] Step S102: Acquire the patient's EEG signal, and determine EEG oscillation data based on the patient's EEG signal.

[0105] In the application embodiment, the patient's EEG signal is the EEG signal of the patient before starting transcranial electrical stimulation treatment while wearing the electrode cap.

[0106] Specifically, after the patient wears the electrode cap, when the technician guides the patient to actively imagine or the patient has spontaneous behavior causing changes in the patient's EEG signal, the electrode cap completely collects the patient's EEG signal and transmits the patient's EEG signal after wearing the electrode cap to the staff's display device and electronic device; after the electronic device receives the patient's EEG signal, the electronic device uses a digital filter to denoise the original EEG signal; the electronic device performs frequency band and time-frequency decomposition analysis on the denoised patient EEG signal; the electronic device calculates the characteristic parameters related to EEG oscillations based on the results of spectrum analysis and time-frequency analysis, and then the electronic device organizes the EEG oscillation data according to the characteristic parameters and transmits it to the technician's display device.

[0107] Step S103: If the EEG oscillation data meets the preset value, the patient's high excitement state is determined based on the EEG oscillation data and the patient's personality information.

[0108] Specifically, the electronic device compares the EEG oscillation data with the preset value. If the EEG oscillation data meets the preset value, it means that the EEG oscillation data has reached the EEG oscillation data threshold corresponding to the high excitement state of the patient's cerebral cortex. The electronic device then determines the patient's corresponding high excitement state based on the EEG oscillation data and the patient's personality information; if the EEG oscillation data does not meet the preset value, it means that although the EEG oscillation data has fluctuated, it has not reached the EEG oscillation data threshold corresponding to the high excitement state of the patient's cerebral cortex. The electronic device then issues an EEG oscillation data monitoring instruction until the EEG oscillation data meets the preset value.

[0109] Step S104, if the patient's high excitement state meets the preset high excitement state, then based on the patient's high excitement state, determine the stimulation timing.

[0110] Specifically, after obtaining the patient's high excitement state, the electronic device immediately compares the patient's high excitement state with the preset high excitement state, thereby verifying the patient's high excitement state; if the patient's high excitement state meets the preset high excitement state, it means that the patient's cerebral cortex is in a high excitement state, and then the electronic device sets the time point corresponding to the patient's high excitement state as the stimulation time; if the patient's high excitement state does not meet the preset high excitement state, it means that although the patient's EEG oscillation has reached the EEG oscillation data threshold corresponding to the patient's cerebral cortex high excitement state, it is not suitable to apply stimulation at this time, presenting a false excitement state. For example, the abnormal discharge of an epileptic patient may meet the EEG oscillation data threshold but is actually pathological excitement; the preset high excitement state is that the patient's cerebral cortex is in physiological excitement, excluding pathological abnormalities.

[0111] Step S105: Generate a transcranial electrical stimulation instruction based on the stimulation timing.

[0112] Specifically, after determining the stimulation timing, the electronic device extracts the corresponding stimulation intensity, stimulation frequency, stimulation duration, interval and stimulation target positioning during the treatment process according to the patient's corresponding treatment plan and transmits them to the stimulator; then, when the stimulation timing occurs, the electronic device generates a transcranial electrical stimulation instruction and transmits it to the stimulator. After receiving the transcranial electrical stimulation instruction, the stimulator immediately starts to apply stimulation and stimulates according to the stimulation duration and interval.

[0113] An embodiment of the present application provides a transcranial electrical stimulation combined with EEG data processing method, which, after obtaining the patient's medical imaging information, identifies the patient's medical imaging information, determines the patient's personality information, clarifies the patient's brain personality characteristics, and makes the treatment more targeted; by analyzing and processing the acquired patient's EEG information, obtains the EEG oscillation data corresponding to the patient; compares the EEG oscillation data with a preset value; if the EEG oscillation data meets the preset value, it means that the EEG oscillation data has reached the EEG oscillation data threshold corresponding to the patient's cerebral cortex high excitement state, and then determines the patient's high excitement state based on the EEG oscillation data and the patient's personality information; then compares the patient's high excitement state with the preset high excitement state to verify the patient's high excitement state; if the patient's high excitement state meets the preset high excitement state, it means that the patient is in a cerebral cortex happy state at this time, and then selects the stimulation timing; then generates a corresponding transcranial electrical stimulation instruction based on the stimulation timing; thereby improving the transcranial electrical stimulation treatment effect.

[0114] Determine EEG oscillation data based on the patient's EEG signal, including: dividing the patient's EEG signal into frequency bands to determine the signal frequency band; calculating the EEG power spectrum density based on the signal frequency band; determining the EEG oscillation pattern and the EEG signal energy distribution based on the EEG power spectrum density; determining the oscillation data based on the EEG oscillation pattern and the EEG signal energy distribution; if the oscillation data is consistent with the preset oscillation data, determine the oscillation data as EEG oscillation data.

[0115] Specifically, after receiving the patient's EEG signal, the electronic device immediately performs denoising on the patient's EEG signal, and divides the denoising patient's EEG signal into frequency bands, mainly into delta wave, theta wave, alpha wave, and beta wave; the electronic device selects the Welch periodogram method or parameterized model to calculate the EEG power spectrum density, and draws the EEG power spectrum density map and transmits it to the display device; the electronic device extracts the visual features in the EEG power spectrum density map and identifies the EEG oscillation pattern; at the same time, the electronic device extracts the dominant signal frequency band according to the patient's corresponding symptoms, and corresponds the signal frequency band to the patient's condition. The EEG oscillation pattern is marked; the electronic device calculates the percentage of each signal frequency band in the total power to obtain the EEG signal energy distribution; then the electronic device integrates the oscillation data according to the EEG oscillation pattern and the EEG signal energy distribution. If the oscillation data is consistent with the preset oscillation data, it means that the oscillation data is valid EEG oscillation, and the electronic device then sets the oscillation data as the EEG oscillation data; if the oscillation data is inconsistent with the preset oscillation data, it means that the oscillation data is invalid EEG oscillation, and the electronic device then discards the oscillation data, and repeats the above operation until the oscillation data is consistent with the preset oscillation data.

[0116] Determining a patient's hyperexcited state based on EEG oscillation data and the patient's personality information includes: preprocessing the EEG oscillation data to obtain first EEG data; calculating an EEG characteristic value based on the first EEG data; determining the patient's symptom information based on the patient's personality information if the EEG characteristic value is consistent with a preset treatment threshold; determining abnormal EEG characteristics of the symptom based on the patient's symptom information; determining trigger conditions based on the abnormal EEG characteristics of the symptom; determining a stimulation mode based on the trigger conditions; determining EEG excitement state characteristics based on the stimulation mode; and determining the patient's hyperexcited state based on the EEG excitement state characteristics and the first EEG data.

[0117] Specifically, the electronic device preprocesses the EEG oscillation data, dynamically adjusts the cutoff frequency, and eliminates interference data, such as blink data and electromyographic component data. The electronic device sets the preprocessed EEG oscillation data as the first EEG data; the electronic device calculates the EEG characteristic value of the first EEG data, and compares the EEG characteristic value with the preset treatment threshold. If the EEG characteristic value is consistent with the preset treatment threshold, it means that the patient's EEG signal fluctuates at this time, thereby verifying the EEG oscillation data; if the EEG characteristic value is inconsistent with the preset treatment threshold, it means that the EEG signal fluctuates at this time but the fluctuation is small and cannot meet the treatment standard, then the EEG signal continues to be monitored until the EEG characteristic value is consistent with the preset treatment threshold; wherein, the preset treatment threshold is set according to physiological significance. Furthermore, the electronic device identifies the patient's personal information and extracts keywords for the patient's symptoms. At the same time, the electronic device compares the keywords with a preset symptom database to determine the patient's symptom information corresponding to the patient; then the electronic device extracts the abnormal EEG characteristics of the symptom based on the patient's symptom information, and calculates the trigger conditions based on the abnormal EEG characteristics of the symptom to obtain the trigger conditions corresponding to the abnormal EEG characteristics of the symptom; the electronic device compares the trigger conditions with a preset stimulation pattern database to determine the corresponding stimulation pattern, wherein the stimulation pattern is specific information that defines the stimulation type and stimulation parameters, such as the intensity, frequency, and duration of transcranial electrical stimulation; then the electronic device extracts data from the changes in EEG data under the corresponding stimulation pattern, and uses the corresponding feature calculation method to calculate the EEG excitement state characteristics of the patient when the cerebral cortex is in a high excitement state; the electronic device filters the first EEG data based on the EEG excitement state characteristics, and sets the EEG data that passes the screening as the patient's high excitement state.

[0118] Based on the characteristics of the EEG excitement state and the first EEG data, determining the patient's high excitement state includes: dividing the first EEG data into frequency bands, and if the first EEG data meets the characteristics of the EEG excitement state, determining the first EEG data as the second EEG data; based on the second EEG data and the stimulation pattern, determining the target area coherence; if the target area coherence meets the preset target area coherence, marking the second EEG data as the patient's high excitement state.

[0119] Specifically, the electronic device divides the first EEG data into frequency bands and decomposes it into different frequency bands of delta wave (0.5-4Hz), theta wave (4-8Hz), alpha wave (8-13Hz), and beta wave (13-30Hz); then the electronic device filters the first EEG data according to the characteristics of the EEG excitement state. If the first EEG data meets the characteristics of the EEG excitement state, the filtered first EEG data is set as the second EEG data; the electronic device calculates the coherence between each target treatment brain area based on the current second EEG data and the stimulation mode, and sets it as the target area coherence; if the target area coherence meets the preset target area coherence, it means that if the current stimulation mode is effective, the EEG state is as expected, and then the electronic device will set the second EEG data at this time as the patient's high excitement state.

[0120] Determining the timing of stimulation also includes: determining a treatment plan based on the patient's personality information and patient disease information; determining treatment parameters based on the treatment plan; marking the target treatment brain area based on the treatment parameters; determining the treatment target based on the target treatment brain area and treatment parameters; and determining the electrode arrangement plan based on the treatment target.

[0121] Specifically, after receiving the patient's personalized information transmitted by the technician, the electronic device extracts keywords from the patient's personalized information and builds an individualized neural feature template based on the extracted keywords. At the same time, it combines the patient's symptom information to set the disease type, disease stage and symptom severity to generate a corresponding treatment plan; the electronic device determines the corresponding treatment parameters for the patient according to the treatment plan; the electronic device selects the patient's personalized brain area based on the treatment parameters, and then the electronic device locates the patient's personalized brain area based on the patient's personalized information. At the same time, the electronic device verifies the patient's personalized brain area based on the treatment parameters, and sets the verified patient's personalized brain area as the target treatment brain area; the electronic device superimposes the MRI / CT and the electrode cap 3D model, uses electrode positioning software, such as BrainCap, to mark the location corresponding to the target treatment brain area, and uses electrophysiological positioning to perform a secondary verification of the location corresponding to the target treatment brain area; the electronic device marks the treatment target in the target treatment brain area based on the treatment parameters, and at the same time, the electronic device fuses MRI and CTA to avoid intracranial blood vessels or brain functional areas. The electronic device uses a navigation system, such as Brainlab , mark the location corresponding to the treatment target; the electronic equipment formulates the electrode arrangement plan for the stimulator according to the treatment target, adopts multi-channel synchronous stimulation to treat different target brain areas, and regulates neural excitability through electrode configuration, such as 1 anode with 4 cathodes to enhance excitability, or 1 cathode with 4 anodes to enhance inhibition.

[0122] Based on the stimulation timing, a transcranial electrical stimulation instruction is generated, which then includes: obtaining third EEG data; determining event-related spectral disturbances and inter-trial coherence based on the third EEG data; generating an efficacy report based on the event-related spectral disturbances and inter-trial coherence; determining data to be verified based on the efficacy report; if the data to be verified is consistent with the preset verification data, maintaining the stimulation timing; if the data to be verified is inconsistent with the preset verification data, generating an optimization plan.

[0123] In the application embodiment, the third EEG data is the EEG data of the patient after transcranial electrical stimulation.

[0124] Specifically, after the patient receives transcranial electrical stimulation treatment, the electrode cap transmits the patient's EEG data at this time to the electronic device. After receiving the EEG data, the electronic device sets it as the third EEG data and classifies and stores it according to different frequency bands. Then, the electronic device calculates the event-related spectral perturbation (ERSP) and inter-trial coherence (ITC) corresponding to the third EEG data, integrates the ERSP and ITC results, and selects key indicators based on the treatment goal. For example, if the treatment goal is to enhance beta wave synchronization in the motor cortex, the ITC value of the beta wave frequency band and the change in the proportion of beta wave power are selected as core indicators. If the goal is to inhibit gamma wave activity in the epileptic focus, the focus is on the reduction amplitude of the gamma wave ERSP and the change in coherence between the epileptic focus and the contralateral brain area. The key indicators are combined with the pre-stimulation baseline data and the improvement of clinical symptoms. Through charts (for example, time-frequency heat maps to display ERSP, line charts to display ITC trends) and text descriptions, a visual efficacy report is formed to intuitively present the treatment effect. The electronic device extracts quantitative indicators directly related to the treatment goal from the efficacy report as data to be verified. These indicators must have clear therapeutic significance and measurability, and be able to accurately reflect the treatment effect; the electronic device will then compare the data to be verified with the preset verification data. If the data to be verified is consistent with the preset verification data, it means that the current stimulation timing is accurate and the stimulation plan is effective, and the current stimulation timing is maintained; if the data to be verified is inconsistent with the preset verification data, it means that there is a deviation in the stimulation timing, and it is determined that the current stimulation timing has not achieved the expected effect. The electronic device analyzes the third EEG data, clarifies the reason for the inconsistency between the data to be verified and the preset verification data, and generates a corresponding optimization plan; when the optimization plan is generated, repeat the stimulation treatment and continue to monitor the third EEG data until the data to be verified is consistent with the preset verification data.

[0125] Reference Figure 2 The transcranial electrical stimulation combined with EEG data processing device 20 may specifically include: a patient personality information determination module 201, an EEG oscillation data determination module 202, a patient high excitement state determination module 203, a stimulation timing determination module 204, and a transcranial electrical stimulation instruction generation module 205, wherein,

[0126] The patient personality information determination module 201 is used to obtain the patient's medical imaging information and determine the patient's personality information based on the patient's medical imaging information;

[0127] The EEG oscillation data determination module 202 is used to obtain the patient's EEG signal and determine the EEG oscillation data based on the patient's EEG signal;

[0128] A stimulation timing determination module 204 is configured to determine a stimulation timing based on the EEG oscillation data and the patient's personality information if the EEG oscillation data meets a preset value;

[0129] The transcranial electrical stimulation instruction generation module 205 is configured to generate a transcranial electrical stimulation instruction based on the stimulation timing.

[0130] In a possible implementation of the embodiment of the present application, the EEG oscillation data determination module 202 includes: a signal frequency band determination unit, an EEG power spectrum density determination unit, a first information determination unit, an oscillation data determination unit, and an EEG oscillation data determination unit, wherein:

[0131] A signal frequency band determination unit, used to divide the patient's EEG signal into frequency bands and determine the signal frequency band;

[0132] an EEG power spectrum density determination unit, configured to calculate the EEG power spectrum density based on the signal frequency band;

[0133] A first information determination unit is used to determine the EEG oscillation pattern and the EEG signal energy distribution according to the EEG power spectrum density;

[0134] an oscillation data determining unit, configured to determine oscillation data based on the EEG oscillation pattern and the EEG signal energy distribution;

[0135] The EEG oscillation data determining unit is configured to determine that the oscillation data is EEG oscillation data if the oscillation data is consistent with preset oscillation data.

[0136] In a possible implementation of the embodiment of the present application, the patient high excitement state determination module 203 includes: a first EEG data determination unit, an EEG characteristic value determination unit, a patient symptom information determination unit, a symptom EEG abnormality feature determination unit, a trigger condition determination unit, a stimulation mode determination unit, an EEG excitement state feature determination unit, and a patient high excitement state determination unit, wherein,

[0137] a first EEG data determining unit, configured to pre-process the EEG oscillation data to obtain first EEG data;

[0138] an EEG characteristic value determining unit, configured to calculate an EEG characteristic value based on the first EEG data;

[0139] a patient symptom information determination unit, configured to determine the patient symptom information based on the patient's personality information if the EEG characteristic value is consistent with a preset treatment threshold;

[0140] a symptom EEG abnormality feature determination unit, configured to determine the symptom EEG abnormality feature based on the patient's symptom information;

[0141] A trigger condition determination unit, used to determine the trigger condition according to the abnormal EEG characteristics of the disease;

[0142] A stimulation mode determination unit, configured to determine a stimulation mode according to a trigger condition;

[0143] an EEG excitement state characteristic determination unit, configured to determine the EEG excitement state characteristic based on the stimulation pattern;

[0144] The patient high excitement state determining unit is used to determine the patient's high excitement state according to the EEG excitement state characteristics and the first EEG data.

[0145] In a possible implementation of the embodiment of the present application, the patient high excitement state determination unit is specifically configured to:

[0146] Performing frequency band division on the first EEG data, and determining the first EEG data as the second EEG data if the first EEG data meets the EEG excitement state characteristic;

[0147] Determine the coherence of the target area based on the second EEG data and the stimulation pattern;

[0148] If the target area coherence meets the preset target area coherence, the second EEG data is marked as a high excitement state of the patient.

[0149] In a possible implementation of the embodiment of the present application, the transcranial electrical stimulation combined with EEG data processing device 20 further includes: a treatment plan determination module, a treatment parameter determination module, a target treatment brain area determination module, a treatment target determination module, and an electrode arrangement plan determination module, wherein:

[0150] A treatment plan determination module is used to determine a treatment plan based on the patient's personality information and the patient's condition information;

[0151] A treatment parameter determination module, configured to determine treatment parameters based on a treatment plan;

[0152] The target brain region determination module is used to mark the target brain region according to the treatment parameters;

[0153] A treatment target determination module, used to determine the treatment target based on the target treatment brain area and treatment parameters;

[0154] The electrode arrangement scheme determination module is used to determine the electrode arrangement scheme based on the treatment target.

[0155] In a possible implementation of the embodiment of the present application, the transcranial electrical stimulation combined with EEG data processing device 20 further includes: a third EEG data acquisition module, a calculation module, a therapeutic effect report generation module, a to-be-verified data determination module, a comparison module, and an optimization solution generation module, wherein:

[0156] A third EEG data acquisition module is used to acquire third EEG data, where the third EEG data is the EEG data of the patient after transcranial electrical stimulation;

[0157] a calculation module, for determining event-related spectral perturbations and inter-trial coherence based on the third EEG data;

[0158] The efficacy report generation module is used to generate efficacy reports based on event-related spectral perturbations and inter-trial coherence;

[0159] A module for determining data to be verified, used to determine data to be verified based on the efficacy report;

[0160] A comparison module, configured to maintain the stimulation timing if the data to be verified is consistent with the preset verification data;

[0161] The optimization solution generation module is used to generate an optimization solution if the data to be verified is inconsistent with the preset verification data.

[0162] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0163] The embodiment of the present application also introduces an electronic device from the perspective of a physical device, such as Figure 3 As shown, Figure 3 The electronic device 30 shown includes a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, for example, via a bus 302. Optionally, the electronic device 30 may further include a transceiver 304. It should be noted that in actual applications, the number of transceivers 304 is not limited to one, and the structure of the electronic device 30 does not constitute a limitation on the embodiments of the present application.

[0164] Processor 301 can be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic device, transistor logic device, hardware component, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 301 can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0165] Bus 302 may include a path for transmitting information between the above components. Bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. Bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, Figure 3 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0166] The memory 303 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0167] The memory 303 is used to store application code for executing the solution of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the content shown in the above method embodiment.

[0168] Electronic devices include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. They may also include servers, etc. Figure 3 The electronic device shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0169] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the flowcharts of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0170] The above are only some of the implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A transcranial electrical stimulation combined with EEG data processing method, characterized in that: include: Acquiring medical imaging information of the patient, and determining individual patient information based on the medical imaging information of the patient, wherein the individual patient information is a reference parameter for brain treatment of the patient required to be collected during transcranial electrical stimulation; Acquiring an electroencephalogram (EEG) signal from a patient, and determining EEG oscillation data based on the EEG signal from the patient; If the EEG oscillation data meets a preset value, determining that the patient is in a high-excitement state based on the EEG oscillation data and the patient's personality information; The step of determining the patient's high excitement state based on the EEG oscillation data and the patient's personality information includes: Preprocessing the EEG oscillation data to obtain first EEG data; Calculating an EEG characteristic value according to the first EEG data; If the EEG characteristic value is consistent with the preset treatment threshold, determining the patient's symptom information based on the patient's personality information; Determining abnormal EEG characteristics of the disease based on the patient's disease information; Determining triggering conditions based on the abnormal EEG characteristics of the disease; determining a stimulation mode according to the trigger condition; determining characteristics of an EEG excitation state based on the stimulation pattern; Determining a patient's high excitement state based on the EEG excitement state characteristics and the first EEG data; The step of determining the patient's high excitement state based on the EEG excitement state characteristic and the first EEG data includes: dividing the first EEG data into frequency bands, and determining the first EEG data as second EEG data if the first EEG data meets the characteristics of an EEG excitement state; determining target area coherence based on the second EEG data and the stimulation pattern; If the target area coherence satisfies the preset target area coherence, marking the second EEG data as a high excitement state of the patient; If the patient's high excitement state meets the preset high excitement state, determining the stimulation timing based on the patient's high excitement state; Based on the stimulation timing, a transcranial electrical stimulation instruction is generated.

2. A transcranial electrical stimulation combined with EEG data processing method according to claim 1, characterized in that: Determining EEG oscillation data based on the patient's EEG signal includes: Dividing the patient's EEG signal into frequency bands to determine the signal frequency band; Calculating the EEG power spectral density based on the signal frequency band; Determining an EEG oscillation pattern and an EEG signal energy distribution according to the EEG power spectrum density; determining oscillation data based on the EEG oscillation pattern and the EEG signal energy distribution; If the oscillation data is consistent with the preset oscillation data, it is determined that the oscillation data is brain electrical oscillation data.

3. The method for transcranial electrical stimulation combined with EEG data processing according to claim 1, characterized in that: The determining of the stimulation timing further includes: Determining a treatment plan based on the patient's personality information and the patient's condition information; determining treatment parameters based on the treatment plan; Marking the target brain area for treatment according to the treatment parameters; determining a treatment target based on the target treatment brain region and the treatment parameters; Based on the therapeutic target, an electrode arrangement plan is determined.

4. The method for transcranial electrical stimulation combined with EEG data processing according to claim 1, characterized in that: The step of generating a transcranial electrical stimulation instruction based on the stimulation timing further includes: Acquiring third EEG data, where the third EEG data is EEG data of the patient after transcranial electrical stimulation; determining event-related spectral perturbations and inter-trial coherence based on the third EEG data; generating an efficacy report based on the event-related spectral perturbation and the inter-trial coherence; Determining data to be verified based on the efficacy report; If the data to be verified is consistent with the preset verification data, maintaining the stimulation timing; If the data to be verified is inconsistent with the preset verification data, an optimization solution is generated.

5. A transcranial electrical stimulation combined with electroencephalogram (EEG) data processing device, used in a transcranial electrical stimulation combined with EEG data processing method according to any one of claims 1 to 4, characterized in that: include: A patient personality information determination module is configured to obtain patient medical imaging information and determine patient personality information based on the patient medical imaging information, wherein the patient personality information is a patient brain treatment reference parameter required to be collected during transcranial electrical stimulation; an EEG oscillation data determination module, configured to obtain an EEG signal of a patient and determine EEG oscillation data based on the EEG signal of the patient; a patient high excitement state determination module, configured to determine the patient's high excitement state based on the EEG oscillation data and the patient's personality information if the EEG oscillation data meets a preset value; The patient high excitement state determination module includes: a first EEG data determination unit, an EEG characteristic value determination unit, a patient symptom information determination unit, a symptom EEG abnormality feature determination unit, a trigger condition determination unit, a stimulation mode determination unit, an EEG excitement state feature determination unit, and a patient high excitement state determination unit, wherein, a first EEG data determining unit, configured to pre-process the EEG oscillation data to obtain first EEG data; an EEG characteristic value determining unit, configured to calculate an EEG characteristic value based on the first EEG data; a patient symptom information determination unit, configured to determine the patient symptom information based on the patient's personality information if the EEG characteristic value is consistent with a preset treatment threshold; a symptom EEG abnormality feature determination unit, configured to determine the symptom EEG abnormality feature based on the patient's symptom information; A trigger condition determination unit, used to determine the trigger condition according to the abnormal EEG characteristics of the disease; A stimulation mode determination unit, configured to determine a stimulation mode according to a trigger condition; an EEG excitement state characteristic determination unit, configured to determine the EEG excitement state characteristic based on the stimulation pattern; a patient high excitement state determining unit, configured to determine the patient's high excitement state based on the EEG excitement state characteristics and the first EEG data; The patient's high excitement state determination unit is specifically used to: Performing frequency band division on the first EEG data, and determining the first EEG data as the second EEG data if the first EEG data meets the EEG excitement state characteristic; Determine the coherence of the target area based on the second EEG data and the stimulation pattern; If the target area coherence meets the preset target area coherence, the second EEG data is marked as a high excitement state of the patient; a stimulation timing determination module, configured to determine a stimulation timing based on the patient's high excitement state if the patient's high excitement state meets a preset high excitement state; The transcranial electrical stimulation instruction generation module is used to generate a transcranial electrical stimulation instruction based on the stimulation timing.

6. An electronic device, characterized in that: The electronic device includes: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute a transcranial electrical stimulation combined with electroencephalogram data processing method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed in a computer, the computer is caused to execute the transcranial electrical stimulation combined with EEG data processing method according to any one of claims 1 to 4.

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