Transcranial electrical stimulation combined electroencephalogram data processing method and device and storage medium

Abstract

The invention relates to the technical field of nerve regulation and control combined electroencephalogram, in particular to a transcranial electrical stimulation combined electroencephalogram data processing method and device and a storage medium. The method comprises the steps that patient medical image information is acquired, patient personality information is determined based on the patient medical image information, and the patient personality information is patient brain treatment reference parameters needing to be collected by a patient in transcranial electrical stimulation; acquiring an electroencephalogram signal of a patient, and determining electroencephalogram oscillation data based on the electroencephalogram signal of the patient; if the electroencephalogram oscillation data meets a preset value, determining a highly excited state of the patient based on the electroencephalogram oscillation data and the patient personality information; if the high-excitation state of the patient accords with a preset high-excitation state, determining a stimulation opportunity based on the high-excitation state of the patient; and generating a transcranial electrical stimulation instruction based on the stimulation opportunity. The transcranial electrical stimulation treatment effect can be improved.

Description

Technical Field

[0001] This application relates to the field of neuromodulation combined with electroencephalogram technology, and particularly to a transcranial electrical stimulation combined with electroencephalogram data processing method, device and storage medium. Background Art

[0002] Transcranial Electrical Stimulation (TES), as a non-invasive neuromodulation technology, has been widely used in the fields of neurorehabilitation, mental disease treatment, and brain function regulation. The main principle of this technology is to apply a weak current to the scalp to regulate the excitability of cortical neurons in the brain, and it is mainly used to improve diseases such as cognitive impairment, depression, and motor function disorders.

[0003] However, traditional TES technology still has certain limitations in actual applications. Therefore, how to improve the treatment effect of TES technology has become a current research hotspot. Traditional TES mostly uses fixed-time interval stimulation or relies on manual experience judgment, and cannot capture the brain active state window in real time, resulting in a large number of ineffective stimulations during the treatment process, thus leading to poor TES treatment effects. Summary of the Invention

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

[0005] In the first aspect, this application provides a transcranial electrical stimulation combined with electroencephalogram data processing method, adopting the following technical solution: A transcranial electrical stimulation combined with electroencephalogram data processing method includes: Obtain the medical image information of the patient, and based on the medical image information of the patient, determine the patient's personality information, where the patient's personality information is the patient's brain treatment reference parameters required for transcranial electrical stimulation; Obtain the electroencephalogram signal of the patient, and based on the electroencephalogram signal of the patient, determine the electroencephalogram oscillation data; If the electroencephalogram oscillation data meets the preset value, then based on the electroencephalogram oscillation data and the patient's personality information, determine the patient's high-excitation state; If the patient's high-excitation state conforms to the preset high-excitation state, then based on the patient's high-excitation state, determine the stimulation timing; Generate a transcranial electrical stimulation instruction based on the stimulation timing.

[0006] By adopting the above technical solution, after obtaining the patient's medical image information, the patient's medical image information is identified to determine the patient's personal information, clarify the personalized characteristics of the patient's brain, and make the treatment more targeted; by analyzing and processing the obtained patient's EEG information, the EEG oscillation data corresponding to the patient is obtained; the EEG oscillation data is compared with a preset value. If the EEG oscillation data meets the preset value, it indicates that the EEG oscillation data has reached the EEG oscillation data threshold corresponding to the high-excitation state of the patient's cerebral cortex. Then, based on the EEG oscillation data and the patient's personal information, the patient's high-excitation state is determined; afterwards, the patient's high-excitation state is compared with the preset high-excitation state to verify the patient's high-excitation state. If the patient's high-excitation state conforms to the preset high-excitation state, it indicates that the patient is in a high state of the cerebral cortex at this time, and then the stimulation timing is selected; afterwards, according to the stimulation timing, a corresponding transcranial electrical stimulation instruction is generated; thereby improving the treatment effect of transcranial electrical stimulation.

[0007] In a possible implementation manner, determining the EEG oscillation data based on the patient's EEG signal includes: Dividing the frequency band of the patient's EEG signal to determine the signal frequency band; Calculating the EEG power spectral density based on the signal frequency band; Determining the EEG oscillation mode and the energy distribution of the EEG signal according to the EEG power spectral density; Determining the oscillation data based on the EEG oscillation mode and the energy distribution of the EEG signal; If the oscillation data is consistent with the preset oscillation data, determine that the oscillation data is the EEG oscillation data.

[0008] In a possible implementation manner, determining the patient's high-excitation state based on the EEG oscillation data and the patient's personal information includes: Preprocessing the EEG oscillation data to obtain the first EEG data; Calculating the EEG eigenvalue according to the first EEG data; If the EEG eigenvalue is consistent with the preset treatment threshold, determine the patient's disease information based on the patient's personal information; Determining the abnormal EEG characteristics of the disease based on the patient's disease information; Determining the trigger condition according to the abnormal EEG characteristics of the disease; Determining the stimulation mode according to the trigger condition; Determining the EEG excitation state characteristics based on the stimulation mode; Determining the patient's high-excitation state according to the EEG excitation state characteristics and the first EEG data.

[0009] In a possible implementation, determining the high-excitation state of the patient based on the EEG excitation state feature and the first EEG data includes: Dividing the frequency bands of the first EEG data. If the first EEG data satisfies the EEG excitation state feature, determine the first EEG data as the second EEG data; Based on the second EEG data and the stimulation pattern, determine the target coherence; If the target coherence meets the preset target coherence, mark the second EEG data as the high-excitation state of the patient.

[0010] In a possible implementation, after determining the stimulation timing, it further includes: Based on the patient's personality information and the patient's disease information, determine the treatment plan; Based on the treatment plan, determine the treatment parameters; According to the treatment parameters, mark the target treatment brain area; Based on the target treatment brain area and the treatment parameters, determine the treatment target; Based on the treatment target, determine the electrode arrangement plan.

[0011] In a possible implementation, after generating the transcranial electrical stimulation instruction based on the stimulation timing, it further includes: Obtain the third EEG data, where the third EEG data is the EEG data of the patient after transcranial electrical stimulation; According to the third EEG data, determine the event-related spectral perturbation and the inter-trial coherence; Based on the event-related spectral perturbation and the inter-trial coherence, generate an efficacy report; According to the efficacy report, determine the data to be verified; If the data to be verified is consistent with the preset verification data, maintain the stimulation timing; If the data to be verified is inconsistent with the preset verification data, generate an optimization plan.

[0012] In a second aspect, the present application provides a transcranial electrical stimulation combined with EEG data processing device, adopting the following technical solution: A transcranial electrical stimulation combined with EEG data processing device includes: a patient personality information determination module, an EEG oscillation data determination module, a patient high-excitation state determination module, a stimulation timing determination module, and a transcranial electrical stimulation instruction generation module, where The patient personality information determination module is used to obtain the patient's medical image information and determine the patient's personality information based on the patient's medical image information. The patient's personality information is the patient's brain treatment reference parameters required in transcranial electrical stimulation; An electroencephalogram (EEG) oscillation data determination module, configured to obtain a patient's EEG signal and determine EEG oscillation data based on the patient's EEG signal; A patient high-excitement state determination module, configured to determine a 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; 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; A transcranial electrical stimulation instruction generation module, configured to generate a transcranial electrical stimulation instruction based on the stimulation timing.

[0013] By adopting the above technical solution, after the patient personality information determination module obtains the patient's medical image information, it identifies the patient's medical image information to determine the patient's personality information and clarify the personalized characteristics of the patient's brain, making the treatment more targeted; the EEG oscillation data determination module analyzes and processes the obtained patient EEG information to obtain the corresponding EEG oscillation data of the patient; the patient 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 high-excitement state of the patient's cerebral cortex at this time. Then, based on the EEG oscillation data and the patient's personality information, the patient's high-excitement state is determined; afterwards, 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 high-excitement state of the cerebral cortex at this time, and then the stimulation timing is selected; afterwards, the transcranial electrical stimulation instruction generation module generates a corresponding transcranial electrical stimulation instruction according to the stimulation timing; thereby improving the treatment effect of transcranial electrical stimulation.

[0014] In a possible implementation manner, the EEG oscillation data determination module includes: a signal frequency band determination unit, an EEG power spectral density determination unit, a first information determination unit, an oscillation data determination unit, and an EEG oscillation data determination unit, where The signal frequency band determination unit is configured to divide the frequency band of the patient's EEG signal to determine the signal frequency band; The EEG power spectral density determination unit is configured to calculate the EEG power spectral density based on the signal frequency band; The first information determination unit is configured to determine the EEG oscillation mode and the EEG signal energy distribution according to the EEG power spectral density; The oscillation data determination unit is configured to determine oscillation data based on the EEG oscillation mode and the EEG signal energy distribution; The EEG oscillation data determination unit is configured to determine the oscillation data as EEG oscillation data if the oscillation data is consistent with the preset oscillation data.

[0015] In a possible implementation manner, the patient high-excitement state determination module includes: a first electroencephalogram data determination unit, an electroencephalogram eigenvalue determination unit, a patient disease information determination unit, a disease electroencephalogram abnormal feature determination unit, a trigger condition determination unit, a stimulation mode determination unit, an electroencephalogram excitement state feature determination unit, and a patient high-excitement state determination unit, where, The first electroencephalogram data determination unit is configured to preprocess the electroencephalogram oscillation data to obtain first electroencephalogram data; The electroencephalogram eigenvalue determination unit is configured to calculate electroencephalogram eigenvalues according to the first electroencephalogram data; The patient disease information determination unit is configured to, if the electroencephalogram eigenvalues are consistent with a preset treatment threshold, determine patient disease information based on the patient personality information; The disease electroencephalogram abnormal feature determination unit is configured to determine disease electroencephalogram abnormal features based on the patient disease information; The trigger condition determination unit is configured to determine a trigger condition according to the disease electroencephalogram abnormal features; The stimulation mode determination unit is configured to determine a stimulation mode according to the trigger condition; The electroencephalogram excitement state feature determination unit is configured to determine electroencephalogram excitement state features based on the stimulation mode; The patient high-excitement state determination unit is configured to determine the patient high-excitement state according to the electroencephalogram excitement state features and the first electroencephalogram data.

[0016] In a possible implementation manner, the patient high-excitement state determination unit is specifically configured to: Perform frequency band division on the first electroencephalogram data, and if the first electroencephalogram data satisfies the electroencephalogram excitement state features, determine the first electroencephalogram data as second electroencephalogram data; Determine target area coherence based on the second electroencephalogram data and the stimulation mode; If the target area coherence satisfies the preset target area coherence, mark the second electroencephalogram data as the patient high-excitement state.

[0017] In a possible implementation manner, the transcranial electrical stimulation combined with electroencephalogram 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, where, The treatment plan determination module is configured to determine a treatment plan based on the patient personality information and the patient disease information; The treatment parameter determination module is configured to determine treatment parameters based on the treatment plan; A target treatment brain region determination module, configured to label a target treatment brain region according to the treatment parameters; A treatment target determination module, configured to determine a treatment target based on the target treatment brain region and the treatment parameters; An electrode arrangement scheme determination module, configured to determine an electrode arrangement scheme based on the treatment target.

[0018] In a possible implementation manner, the transcranial electrical stimulation combined with electroencephalogram data processing device further includes: a third electroencephalogram data acquisition module, a calculation module, an efficacy report generation module, a data to be verified determination module, a comparison module, and an optimization scheme generation module, where The third electroencephalogram data acquisition module is configured to acquire third electroencephalogram data, where the third electroencephalogram data is the electroencephalogram data of a patient after transcranial electrical stimulation; The calculation module is configured to determine event-related spectral perturbation and inter-trial coherence according to the third electroencephalogram data; The efficacy report generation module is configured to generate an efficacy report based on the event-related spectral perturbation and the inter-trial coherence; The data to be verified determination module is configured to determine data to be verified according to the efficacy report; The comparison module is configured to maintain the stimulation timing if the data to be verified is consistent with preset verification data; The optimization scheme generation module is configured to generate an optimization scheme if the data to be verified is inconsistent with preset verification data.

[0019] In a third aspect, the present application provides an electronic device, adopting the following technical solution: An electronic device, the electronic device includes: At least one processor; A memory; At least one application program, where at least one application program is stored in the memory and is configured to be executed by at least one processor, and the at least one application program is configured to: execute the above-mentioned transcranial electrical stimulation combined with electroencephalogram data processing method.

[0020] In a fourth aspect, the present application provides a computer-readable storage medium, adopting the following technical solution: A computer-readable storage medium, including: a computer program stored therein that can be loaded and executed by a processor to execute the above-mentioned transcranial electrical stimulation combined with electroencephalogram data processing method.

[0021] In summary, the present application includes the following beneficial technical effects: After obtaining the medical image information of the patient, identify the medical image information of the patient, determine the patient's personal information, and clarify the personalized characteristics of the patient's brain, making the treatment more targeted; through the analysis and processing of the obtained electroencephalogram information of the patient, obtain the corresponding electroencephalogram oscillation data of the patient; compare the electroencephalogram oscillation data with a preset value. If the electroencephalogram oscillation data meets the preset value, it indicates that the electroencephalogram oscillation data has reached the electroencephalogram oscillation data threshold corresponding to the highly excited state of the patient's cerebral cortex. Then, based on the electroencephalogram oscillation data and the patient's personal information, determine the patient's highly excited state; then compare the patient's highly excited state with the preset highly excited state to verify the patient's highly excited state. If the patient's highly excited state conforms to the preset highly excited state, it indicates that the patient is in a highly excited state of the cerebral cortex at this time, and then select the stimulation timing; then generate a corresponding transcranial electrical stimulation instruction according to the stimulation timing; thereby improving the treatment effect of transcranial electrical stimulation Brief Description of the Drawings

[0022] Figure 1 is a schematic flowchart of the method for processing transcranial electrical stimulation combined with electroencephalogram data in this application; Figure 2 is a schematic block diagram of the device for processing transcranial electrical stimulation combined with electroencephalogram data in this application; Figure 3 is a schematic diagram of the electronic device in the embodiment of this application. Detailed Embodiment

[0023] The following is a further detailed description of this application in conjunction with the attached Figures 1-3 to this application.

[0024] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, 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 some, but not all, of the embodiments of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of this application without creative efforts shall fall within the protection scope of this application.

[0025] The embodiment of this application provides a method for processing transcranial electrical stimulation combined with electroencephalogram data, which is executed by an electronic device. The electronic device can be a server or a terminal device. Among them, 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 smart phone, a tablet computer, a notebook computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected through wired or wireless communication methods, and this application does not make any restrictions in this regard.

[0026] Refer toFigure 1 The method includes: step S101, step S102, step S103, step S104, and step S105, where: Step S101: Obtain the patient's medical image information, and based on the patient's medical image information, determine the patient's personalized information.

[0027] In the application embodiment, the patient's personalized information is the patient's brain treatment reference parameters required in transcranial electrical stimulation.

[0028] Specifically, when the patient undergoes MRI and / or CT examinations, the electronic device will receive the patient's medical image information transmitted by the detection instrument. Subsequently, the electronic device preprocesses and corrects the patient's medical image information. After receiving the corrected patient's medical image information, the electronic device extracts the structural features and functional features of the patient's medical image information to obtain the feature information of the patient's brain. The electronic device extracts the patient's brain treatment reference parameters required in transcranial electrical stimulation according to the feature information and sets them as the patient's personalized information. At the same time, the electronic device constructs a brain model.

[0029] Step S102: Obtain the patient's electroencephalogram (EEG) signal, and based on the patient's EEG signal, determine the EEG oscillation data.

[0030] In the application embodiment, the patient's EEG signal is the EEG signal of the patient before starting transcranial electrical stimulation treatment when wearing an electrode cap.

[0031] Specifically, after the patient wears the electrode cap, when the technician guides the patient to perform active imagination or the patient's spontaneous behavior causes 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 display device and the electronic device of the staff. After receiving 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's EEG signal. Based on the results of spectral analysis and time-frequency analysis, the electronic device calculates the characteristic parameters related to EEG oscillation. Subsequently, the electronic device sorts out the EEG oscillation data according to the characteristic parameters and transmits it to the display device of the technician.

[0032] Step S103: If the EEG oscillation data meets the preset value, then based on the EEG oscillation data and the patient's personalized information, determine the patient's high-excitement state.

[0033] Specifically, the electronic device compares the electroencephalogram oscillation data with a preset value. If the electroencephalogram oscillation data meets the preset value, it indicates that the electroencephalogram oscillation data at this time has reached the electroencephalogram oscillation data threshold corresponding to the highly excited state of the patient's cerebral cortex. Subsequently, the electronic device determines the patient's corresponding highly excited state based on the electroencephalogram oscillation data and in combination with the patient's personality information. If the electroencephalogram oscillation data does not meet the preset value, it indicates that although the electroencephalogram oscillation data has fluctuated at this time, it has not reached the electroencephalogram oscillation data threshold corresponding to the highly excited state of the patient's cerebral cortex. Subsequently, the electronic device issues an electroencephalogram oscillation data monitoring instruction until the electroencephalogram oscillation data meets the preset value.

[0034] Step S104: If the patient's highly excited state conforms to the preset highly excited state, determine the stimulation timing based on the patient's highly excited state. Specifically, after obtaining the patient's highly excited state, the electronic device immediately compares the patient's highly excited state with the preset highly excited state to verify the patient's highly excited state. If the patient's highly excited state conforms to the preset highly excited state, it indicates that the patient's cerebral cortex is in a highly excited state. Subsequently, the electronic device sets the time point corresponding to the patient's highly excited state as the stimulation timing. If the patient's highly excited state does not conform to the preset highly excited state, it indicates that although the patient's electroencephalogram oscillation has reached the electroencephalogram oscillation data threshold corresponding to the highly excited state of the patient's cerebral cortex at this time, it is not suitable to apply stimulation at this time, presenting a false excitation state. For example, the abnormal discharge of an epileptic patient may meet the electroencephalogram oscillation data threshold but is actually a pathological excitation. The preset highly excited state is that the patient's cerebral cortex is in a physiological excitation, excluding pathological abnormalities.

[0035] Step S105: Generate a transcranial electrical stimulation instruction based on the stimulation timing.

[0036] Specifically, after determining the stimulation timing, the electronic device extracts and transmits the corresponding stimulation intensity, stimulation frequency, stimulation duration, interval, and the positioning of the stimulation target during the treatment process to the stimulator according to the treatment plan corresponding to the patient. Subsequently, the electronic device generates a transcranial electrical stimulation instruction and transmits it to the stimulator at the same time when the stimulation timing appears. The stimulator immediately starts to apply stimulation after receiving the transcranial electrical stimulation instruction and stimulates according to the stimulation duration and interval.

[0037] An embodiment of the present application provides a transcranial electrical stimulation combined with electroencephalogram data processing method. After obtaining the medical image information of a patient, the medical image information of the patient is identified to determine the patient's personality information and clarify the personalized characteristics of the patient's brain, making the treatment more targeted; by analyzing and processing the obtained electroencephalogram information of the patient, the electroencephalogram oscillation data corresponding to the patient is obtained; the electroencephalogram oscillation data is compared with a preset value. If the electroencephalogram oscillation data meets the preset value, it indicates that the electroencephalogram oscillation data has reached the electroencephalogram oscillation data threshold corresponding to the high-excitation state of the patient's cerebral cortex. Then, based on the electroencephalogram oscillation data and the patient's personality information, the patient's high-excitation state is determined; afterwards, the patient's high-excitation state is compared with the preset high-excitation state to verify the patient's high-excitation state. If the patient's high-excitation state conforms to the preset high-excitation state, it indicates that the patient is in a high-excitation state of the cerebral cortex at this time, and then the stimulation timing is selected; afterwards, according to the stimulation timing, a corresponding transcranial electrical stimulation instruction is generated; thereby improving the treatment effect of transcranial electrical stimulation.

[0038] Based on the patient's electroencephalogram signal, determining the electroencephalogram oscillation data includes: dividing the frequency band of the patient's electroencephalogram signal to determine the signal frequency band; calculating the electroencephalogram power spectral density based on the signal frequency band; determining the electroencephalogram oscillation mode and the electroencephalogram signal energy distribution according to the electroencephalogram power spectral density; determining the oscillation data based on the electroencephalogram oscillation mode and the electroencephalogram signal energy distribution; if the oscillation data is consistent with the preset oscillation data, determining the oscillation data as the electroencephalogram oscillation data.

[0039] Specifically, after receiving the patient's electroencephalogram signal, the electronic device immediately performs denoising processing on the patient's electroencephalogram signal. The electronic device divides the frequency band of the denoised patient's electroencephalogram signal, mainly into delta wave, theta wave, alpha wave, and beta wave; the electronic device selects the Welch periodogram method or a parametric model to calculate the electroencephalogram power spectral density and draws an electroencephalogram power spectral density map and transmits it to a display device; the electronic device extracts the visual features in the electroencephalogram power spectral density map to identify the electroencephalogram oscillation mode; at the same time, the electronic device extracts the dominant signal frequency band according to the disease corresponding to the patient and marks the electroencephalogram oscillation mode corresponding to the signal frequency band; the electronic device calculates the percentage of each signal frequency band in the total power to obtain the electroencephalogram signal energy distribution; afterwards, the electronic device integrates the oscillation data according to the electroencephalogram oscillation mode and the electroencephalogram signal energy distribution. If the oscillation data is consistent with the preset oscillation data, it indicates that the oscillation data is valid electroencephalogram oscillation. Then, the electronic device sets the oscillation data as the electroencephalogram oscillation data; if the oscillation data is inconsistent with the preset oscillation data, it indicates that the oscillation data is invalid electroencephalogram oscillation. Then, the electronic device discards the oscillation data and repeats the above operation until the oscillation data is consistent with the preset oscillation data.

[0040] Determine the high-excitement state of the patient based on electroencephalogram (EEG) oscillation data and the patient's personality information, including: preprocessing the EEG oscillation data to obtain first EEG data; calculating EEG eigenvalue based on the first EEG data; if the EEG eigenvalue is consistent with the preset treatment threshold, determine the patient's disease information based on the patient's personality information; determine the abnormal EEG characteristics of the disease based on the patient's disease information; determine the triggering condition according to the abnormal EEG characteristics of the disease; determine the stimulation mode according to the triggering condition; determine the EEG excitement state characteristics based on the stimulation mode; determine the high-excitement state of the patient according to the EEG excitement state characteristics and the first EEG data.

[0041] Specifically, the electronic device preprocesses the EEG oscillation data, dynamically adjusts the cut-off frequency, and eliminates interference data at the same time, such as blinking data and electromyogram component data. The electronic device sets the preprocessed EEG oscillation data as the first EEG data; the electronic device calculates the EEG eigenvalue of the first EEG data and compares the EEG eigenvalue with the preset treatment threshold. If the EEG eigenvalue is consistent with the preset treatment threshold, it indicates that the patient's EEG signal fluctuates at this time, so as to verify the EEG oscillation data; if the EEG eigenvalue is inconsistent with the preset treatment threshold, it indicates that the EEG signal fluctuates but the fluctuation is small and cannot reach the treatment standard, so the EEG signal is continuously monitored until the EEG eigenvalue is consistent with the preset treatment threshold; among them, the preset treatment threshold is set according to the physiological significance. Further, the electronic device identifies the patient's personality information, extracts keywords for the patient's disease, and at the same time the electronic device compares the keywords with the preset disease database to determine the patient's disease information corresponding to the patient; then the electronic device extracts the abnormal EEG characteristics of the disease based on the patient's disease information, and the electronic device calculates the triggering condition according to the abnormal EEG characteristics of the disease to obtain the triggering condition corresponding to the abnormal characteristics of the EEG of the disease; the electronic device compares the triggering condition with the preset stimulation mode database to determine the corresponding stimulation mode, where the stimulation mode is the specific information defining the stimulation type and stimulation parameters, such as the intensity, frequency, and duration of transcranial electrical stimulation; then the electronic device extracts the changes in the EEG data under the corresponding stimulation mode, and uses the corresponding feature calculation method to calculate the EEG excitement state characteristics of the patient in the high-excitement state of the cerebral cortex; the electronic device filters the first EEG data based on the EEG excitement state characteristics, and sets the filtered EEG data as the high-excitement state of the patient.

[0042] Determine the high-excitement state of the patient according to the EEG excitement state characteristics and the first EEG data, including: dividing the frequency band of the first EEG data, if the first EEG data meets the EEG excitement state characteristics, determine the first EEG data as the second EEG data; determine the target area coherence based on the second EEG data and the stimulation mode; if the target area coherence meets the preset target area coherence, mark the second EEG data as the high-excitement state of the patient.

[0043] Specifically, the electronic device divides the first electroencephalogram data into different frequency bands, namely delta wave (0.5 - 4 Hz), theta wave (4 - 8 Hz), alpha wave (8 - 13 Hz), and beta wave (13 - 30 Hz); then the electronic device screens the first electroencephalogram data according to the electroencephalogram excitation state characteristics. If the first electroencephalogram data meets the electroencephalogram excitation state characteristics, the first electroencephalogram data that passes the screening is set as the second electroencephalogram data; the electronic device calculates the coherence between each target treatment brain region based on the current second electroencephalogram data and the stimulation mode, and sets it as the target region coherence; if the target region coherence meets the preset target region coherence, it indicates that if the current stimulation mode is effective, the electroencephalogram state meets the expectation. Immediately, the electronic device sets the second electroencephalogram data at this time as the high-excitation state of the patient.

[0044] Determining the stimulation timing also includes: based on the patient's personality information and the patient's disease information, determining the treatment plan; based on the treatment plan, determining the treatment parameters; according to the treatment parameters, marking the target treatment brain regions; based on the target treatment brain regions and the treatment parameters, determining the treatment targets; based on the treatment targets, determining the electrode arrangement plan.

[0045] Specifically, after receiving the patient's personality information transmitted by the technician, the electronic device extracts keywords from the patient's personality information, constructs an individualized neural feature template based on the extracted keywords, and combines the patient's disease information to set the disease type, disease course stage, and disease severity, generating 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 regions according to the treatment parameters, then the electronic device locates the patient's personalized brain regions according to the patient's personality information, and at the same time the electronic device verifies the patient's personalized brain regions according to the treatment parameters, and sets the verified patient's personalized brain regions as the target treatment brain regions; the electronic device superimposes the MRI / CT and the electrode cap 3D model, uses electrode positioning software, such as BrainCap, to mark the corresponding positions of the target treatment brain regions, and uses electrophysiological positioning to perform secondary verification on the corresponding positions of the target treatment brain regions; the electronic device marks the treatment targets in the target treatment brain regions according to the treatment parameters, and at the same time the electronic device fuses the MRI and CTA to avoid intracranial blood vessels or avoid the brain functional areas, and the electronic device uses a navigation system, such as Brainlab, to mark the corresponding positions of the treatment targets; the electronic device formulates an electrode arrangement plan for the electrode arrangement of the stimulator according to the treatment targets, and uses multi-channel synchronous stimulation of different target treatment brain regions to regulate neural excitability through electrode configuration, such as 1 anode cooperating with 4 cathodes to enhance excitability, or 1 cathode cooperating with 4 anodes to enhance inhibition.

[0046] Generate transcranial electrical stimulation (tES) commands based on the stimulation timing, which further includes: obtaining third electroencephalogram (EEG) data; determining event-related spectral perturbation (ERSP) and inter-trial coherence (ITC) based on the third EEG data; generating a treatment efficacy report based on ERSP and ITC; determining data to be verified according to the treatment efficacy report; if the data to be verified is consistent with the preset verification data, maintain the stimulation timing; if the data to be verified is inconsistent with the preset verification data, generate an optimization plan.

[0047] In the application embodiment, the third EEG data is the EEG data of the patient after tES.

[0048] Specifically, when the patient undergoes tES 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 stores it classified by 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 in combination with the treatment goal. For example, if the treatment goal is to enhance the β-wave synchronization of the motor cortex, select the ITC value in the β-wave frequency band and the change in the β-wave power ratio as the core indicators; if the aim is to suppress the γ-wave activity of the epileptic focus, pay attention to the reduction amplitude of the γ-wave ERSP and the change in the coherence between the epileptogenic focus and the contralateral brain region. Combine the key indicators with the pre-stimulation baseline data and the improvement of clinical symptoms, and form a visual treatment efficacy report through charts (such as time-frequency heat maps showing ERSP and line charts showing ITC trends) and text descriptions to intuitively present the treatment effect; the electronic device extracts the quantitative indicators directly related to the treatment goal from the treatment efficacy report as the data to be verified. These indicators need to have clear treatment significance and measurability and can accurately reflect the treatment effect; then the electronic device compares 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 does not reach the expected effect. The electronic device analyzes the third EEG data to clarify the reason for the inconsistency between the data to be verified and the preset verification data, and generates a corresponding optimization plan; after the optimization plan is generated, repeat the stimulation treatment and continuously monitor the third EEG data until the data to be verified is consistent with the preset verification data.

[0049] Refer to Figure 2 , the tES 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 hyperexcitability determination module 203, a stimulation timing determination module 204, and a tES command generation module 205, where The patient personality information determination module 201 is configured to obtain patient medical image information and determine patient personality information based on the patient medical image information; The electroencephalogram oscillation data determination module 202 is configured to obtain the patient's electroencephalogram signal and determine electroencephalogram oscillation data based on the patient's electroencephalogram signal; The stimulation timing determination module 203 is configured to, if the electroencephalogram oscillation data meets a preset value, determine the stimulation timing based on the electroencephalogram oscillation data and the patient personality information; The transcranial electrical stimulation instruction generation module 204 is configured to generate a transcranial electrical stimulation instruction based on the stimulation timing.

[0050] In a possible implementation manner of the embodiment of the present application, the electroencephalogram oscillation data determination module 202 includes: a signal frequency band determination unit, an electroencephalogram power spectral density determination unit, a first information determination unit, an oscillation data determination unit, and an electroencephalogram oscillation data determination unit, where The signal frequency band determination unit is configured to divide the frequency band of the patient's electroencephalogram signal and determine the signal frequency band; The electroencephalogram power spectral density determination unit is configured to calculate the electroencephalogram power spectral density based on the signal frequency band; The first information determination unit is configured to determine the electroencephalogram oscillation mode and the electroencephalogram signal energy distribution according to the electroencephalogram power spectral density; The oscillation data determination unit is configured to determine oscillation data based on the electroencephalogram oscillation mode and the electroencephalogram signal energy distribution; The electroencephalogram oscillation data determination unit is configured to, if the oscillation data is consistent with the preset oscillation data, determine the oscillation data as the electroencephalogram oscillation data.

[0051] In a possible implementation manner of the embodiment of the present application, the patient high-excitement state determination module 203 includes: a first electroencephalogram data determination unit, an electroencephalogram eigenvalue determination unit, a patient disease information determination unit, a disease electroencephalogram abnormal feature determination unit, a trigger condition determination unit, a stimulation mode determination unit, an electroencephalogram excitement state feature determination unit, and a patient high-excitement state determination unit, where The first electroencephalogram data determination unit is configured to preprocess the electroencephalogram oscillation data to obtain the first electroencephalogram data; The electroencephalogram eigenvalue determination unit is configured to calculate the electroencephalogram eigenvalue according to the first electroencephalogram data; The patient disease information determination unit is configured to, if the electroencephalogram eigenvalue is consistent with the preset treatment threshold, determine the patient disease information based on the patient personality information; The disease electroencephalogram abnormal feature determination unit is configured to determine the disease electroencephalogram abnormal feature based on the patient disease information; The trigger condition determination unit is configured to determine the trigger condition according to the disease electroencephalogram abnormal feature; A stimulation mode determination unit, configured to determine a stimulation mode according to a triggering condition; An EEG excitatory state feature determination unit, configured to determine an EEG excitatory state feature based on the stimulation mode; A patient high-excitation state determination unit, configured to determine a patient high-excitation state according to the EEG excitatory state feature and first EEG data.

[0052] In a possible implementation manner of the embodiment of the present application, the patient high-excitation state determination unit is specifically configured to: Perform frequency band division on the first EEG data. If the first EEG data meets the EEG excitatory state feature, determine the first EEG data as second EEG data; Determine target area coherence based on the second EEG data and the stimulation mode; If the target area coherence meets a preset target area coherence, mark the second EEG data as the patient high-excitation state.

[0053] In a possible implementation manner 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, where The treatment plan determination module is configured to determine a treatment plan based on patient personality information and patient disease information; The treatment parameter determination module is configured to determine treatment parameters based on the treatment plan; The target treatment brain area determination module is configured to mark a target treatment brain area according to the treatment parameters; The treatment target determination module is configured to determine a treatment target based on the target treatment brain area and the treatment parameters; The electrode arrangement plan determination module is configured to determine an electrode arrangement plan based on the treatment target.

[0054] In a possible implementation manner 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, an efficacy report generation module, a data to be verified determination module, a comparison module, and an optimization plan generation module, where The third EEG data acquisition module is configured to acquire third EEG data, and the third EEG data is the EEG data of the patient after transcranial electrical stimulation; The calculation module is configured to determine event-related spectral perturbation and inter-trial coherence according to the third EEG data; The efficacy report generation module is configured to generate an efficacy report based on the event-related spectral perturbation and inter-trial coherence; The data to be verified determination module is configured to determine data to be verified according to the efficacy report; A comparison module, configured to maintain the stimulation timing if the data to be verified is consistent with the preset verification data. An optimization scheme generation module, configured to generate an optimization scheme if the data to be verified is inconsistent with the preset verification data.

[0055] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0056] This application embodiment also introduces an electronic device from the perspective of an entity device, such as Figure 3 shown. Figure 3 The electronic device 30 shown in the figure includes: a processor 301 and a memory 303. Among them, the processor 301 and the memory 303 are connected, such as connected through a bus 302. Optionally, the electronic device 30 may further include a transceiver 304. It should be noted that in practical applications, the transceiver 304 is not limited to one, and the structure of the electronic device 30 does not constitute a limitation to the embodiments of this application.

[0057] The processor 301 may be a CPU (Central Processing Unit, central processor), a general-purpose processor, a DSP (Digital Signal Processor, data signal processor), an ASIC (Application Specific Integrated Circuit, application-specific integrated circuit), an FPGA (Field Programmable Gate Array, field programmable gate array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute various exemplary logical blocks, modules, and circuits described in combination with the disclosure of this application. The processor 301 may also be a combination that realizes computing functions, such as a combination including one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0058] The bus 302 may include a path for transmitting information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect, peripheral component interconnect standard) bus or an EISA (Extended Industry Standard Architecture, extended industry standard architecture) bus, etc. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, Figure 3 only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.

[0059] The memory 303 can be a ROM (Read Only Memory), or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory), or other types of dynamic storage devices that can store information and instructions. It can also be an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media, or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0060] The memory 303 is used to store the application program code for implementing the solution of this application, and is controlled by the processor 301 for execution. The processor 301 is used to execute the application program code stored in the memory 303 to implement the content shown in the foregoing method embodiments.

[0061] Among them, the electronic device includes but is 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), in-vehicle terminals (such as in-vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. It can also be a server, etc. Figure 3 The shown electronic device is merely an example and should not impose any limitations on the functions and usage scope of the embodiments of this application.

[0062] It should be understood that although each step in the flowchart of the accompanying drawings is shown sequentially according to the indication of the arrows, these steps do not necessarily have to be executed sequentially in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit and can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages. These sub-steps or stages do not necessarily have to be executed at the same moment, but can be executed at different moments, and their execution order does not necessarily have to be sequential, but can be executed alternately or in turn with at least a part of other steps or sub-steps or stages of other steps.

[0063] The above are only some implementation manners of the present application. It should be noted that for those of ordinary skill in the art, several improvements and refinements can be made without departing from the principle of the present application, and these improvements and refinements should also be regarded as the protection scope of the present application.

Claims

1. A transcranial electrical stimulation combined with electroencephalogram data processing method, characterized in that Including: Obtain the medical image information of the patient, and based on the medical image information of the patient, determine the patient's personality information, where the patient's personality information is the reference parameter for brain treatment of the patient to be collected during transcranial electrical stimulation; Obtain the electroencephalogram (EEG) signal of the patient, and based on the EEG signal of the patient, determine the EEG oscillation data; If the EEG oscillation data meets a preset value, then based on the EEG oscillation data and the patient's personality information, determine the patient's high-excitation state; If the patient's high-excitation state conforms to a preset high-excitation state, then based on the patient's high-excitation state, determine the stimulation timing; Generate a transcranial electrical stimulation instruction based on the stimulation timing.

2. The transcranial electrical stimulation combined with electroencephalogram data processing method according to claim 1, characterized in that, The determining the EEG oscillation data based on the EEG signal of the patient includes: Perform frequency band division on the EEG signal of the patient to determine the signal frequency band; Calculate the EEG power spectral density based on the signal frequency band; Determine the EEG oscillation pattern and the energy distribution of the EEG signal according to the EEG power spectral density; Determine the oscillation data based on the EEG oscillation pattern and the energy distribution of the EEG signal; If the oscillation data is consistent with the preset oscillation data, then determine the oscillation data as the EEG oscillation data.

3. A transcranial electrical stimulation combined with electroencephalogram data processing method according to claim 1, characterized in that, The determining the patient's high-excitation state based on the EEG oscillation data and the patient's personality information includes: Preprocess the EEG oscillation data to obtain the first EEG data; Calculate the EEG eigenvalue according to the first EEG data; If the EEG eigenvalue is consistent with the preset treatment threshold, then based on the patient's personality information, determine the patient's disease information; Determine the abnormal EEG characteristics of the disease based on the patient's disease information; Determine the triggering condition according to the abnormal EEG characteristics of the disease; Determine the stimulation mode according to the triggering condition; Determine the EEG excitation state characteristics based on the stimulation mode; Determine the patient's high-excitation state according to the EEG excitation state characteristics and the first EEG data.

4. A transcranial electrical stimulation combined with electroencephalogram data processing method according to claim 3, characterized in that The determining the patient's high-excitation state according to the EEG excitation state characteristics and the first EEG data includes: Perform frequency band division on the first EEG data. If the first EEG data meets the EEG excitation state characteristics, then determine the first EEG data as the second EEG data; Determine the target area coherence based on the second EEG data and the stimulation mode; If the target area coherence meets the preset target area coherence, then mark the second EEG data as the patient's high-excitation state.

5. A transcranial electrical stimulation combined with electroencephalogram data processing method according to claim 3, characterized in that, After determining the stimulation timing, it further includes: Determine the treatment plan based on the patient's personality information and the patient's disease information; Determine the treatment parameters based on the treatment plan; Mark the target treatment brain area according to the treatment parameters; Determine the treatment target based on the target treatment brain area and the treatment parameters; Determine the electrode arrangement plan based on the treatment target.

6. A transcranial electrical stimulation combined with electroencephalogram data processing method according to claim 1, characterized in that After generating the transcranial electrical stimulation instruction based on the stimulation timing, it further includes: Obtain the third EEG data, where the third EEG data is the EEG data of the patient after transcranial electrical stimulation; Determine the event-related spectral perturbation and the inter-trial coherence according to the third EEG data; Generate a treatment effect report based on the event-related spectral perturbation and the inter-trial coherence. Determine the data to be verified according to the efficacy report; If the data to be verified is consistent with the preset verification data, maintain the stimulation timing; If the data to be verified is inconsistent with the preset verification data, generate an optimization plan.

7. A transcranial electrical stimulation combined with electroencephalogram data processing device, characterized in that, Including: A patient personality information determination module, configured to obtain patient medical image information, and determine patient personality information based on the patient medical image information, where the patient personality information is the reference parameters for patient brain treatment required in transcranial electrical stimulation; An electroencephalogram oscillation data determination module, configured to obtain the patient's electroencephalogram signal and determine the electroencephalogram oscillation data based on the patient's electroencephalogram signal; A patient high-excitement state determination module, configured to determine the patient's high-excitement state based on the electroencephalogram oscillation data and the patient personality information if the electroencephalogram oscillation data meets a preset value; A stimulation timing determination module, configured to determine the stimulation timing based on the patient's high-excitement state if the patient's high-excitement state conforms to a preset high-excitement state; A transcranial electrical stimulation instruction generation module, configured to generate a transcranial electrical stimulation instruction based on the stimulation timing.

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

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed on a computer, cause the computer to execute a method for processing transcranial electrical stimulation combined with electroencephalogram data according to any one of claims 1 to 6.

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