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

Abstract

The invention discloses a transcranial magnetic stimulation combined electroencephalogram data processing method and device and a storage medium. The method comprises the following steps: acquiring transcranial magnetic stimulation combined electroencephalogram data; the transcranial magnetic stimulation combined electroencephalogram data is electroencephalogram data of a target object under transcranial magnetic stimulation with preset parameters; determining electroencephalogram potential data and electroencephalogram oscillation data based on the transcranial magnetic stimulation and electroencephalogram data; generating a transcranial magnetic stimulation combined electroencephalogram report based on the electroencephalogram potential data and the electroencephalogram oscillation data; the transcranial magnetic stimulation combined electroencephalogram report is used for carrying out grading evaluation on the transcranial magnetic stimulation combined electroencephalogram data, collecting the transcranial magnetic stimulation combined electroencephalogram data while carrying out transcranial magnetic stimulation, processing the real-time transcranial magnetic stimulation combined electroencephalogram data, obtaining needed electroencephalogram potential data and electroencephalogram oscillation data in the transcranial magnetic stimulation combined electroencephalogram data, and outputting the transcranial magnetic stimulation combined electroencephalogram report. A report is generated, subsequent electroencephalogram data grading evaluation is facilitated, and transcranial magnetic stimulation and electroencephalogram data are effectively utilized.

Description

Technical Field

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

[0002] Transcranial Magnetic Stimulation (TMS) is a non-invasive neuroregulation technology. Since its development in the 1980s, it has gradually become an important tool for neuroscience research and clinical treatment. Its core principle is that a rapidly changing pulsed magnetic field penetrates the skull and induces an induced current in the cerebral cortex, thereby reversibly activating or inhibiting local neuronal activities. Due to the advantages of high spatial resolution, non-invasive characteristics, and small side effects of TMS, it has now been widely used in the diagnosis and treatment of nervous system and mental diseases such as depression, schizophrenia, and Parkinson's disease, and has become a key technical means for exploring human brain functions and higher cognitive functions.

[0003] However, existing TMS technologies still have significant limitations, restricting their clinical applications and research potential. When the transcranial magnetic stimulator emits pulsed stimuli, it will generate huge electromagnetic interference, covering the real electroencephalogram signals and evoked electroencephalogram signals within 30 - 50 milliseconds at this time and afterwards, making them unidentifiable. As a result, the electroencephalogram signals collected by the electroencephalogram device combined with transcranial magnetic stimulation are unidentifiable, so the electroencephalogram signals cannot be normally graded and evaluated using the electroencephalogram signals combined with transcranial magnetic stimulation. Summary of the Invention

[0004] To solve the technical problem that the electromagnetic interference generated by existing transcranial magnetic stimulators affects electroencephalogram signals, resulting in the inability to use electroencephalogram signals combined with transcranial magnetic stimulation for grading and evaluation of electroencephalogram signals, the present invention provides a transcranial magnetic stimulation combined electroencephalogram data processing method, device, and storage medium. By collecting transcranial magnetic stimulation combined electroencephalogram data while performing transcranial magnetic stimulation, and processing the real-time transcranial magnetic stimulation combined electroencephalogram data, the required electroencephalogram potential data and electroencephalogram oscillation data are obtained, and a report is generated, facilitating subsequent grading and evaluation of electroencephalogram data and effectively utilizing transcranial magnetic stimulation combined electroencephalogram data.

[0005] In a first aspect, an embodiment of the present application provides a transcranial magnetic stimulation combined electroencephalogram data processing method, which includes: Obtain transcranial magnetic stimulation combined electroencephalogram data; the transcranial magnetic stimulation combined electroencephalogram data is electroencephalogram data of a target object under transcranial magnetic stimulation with preset parameters; Determine electroencephalogram potential data and electroencephalogram oscillation data based on the transcranial magnetic stimulation combined electroencephalogram data; Generate a transcranial magnetic stimulation combined electroencephalogram report based on the electroencephalogram potential data and the electroencephalogram oscillation data; the transcranial magnetic stimulation combined electroencephalogram report is used to perform a hierarchical evaluation on the transcranial magnetic stimulation combined electroencephalogram data.

[0006] In an alternative embodiment, the determining the electroencephalogram potential data and the electroencephalogram oscillation data based on the transcranial magnetic stimulation combined electroencephalogram data includes: Preprocess the transcranial magnetic stimulation combined electroencephalogram data to obtain preprocessed transcranial magnetic stimulation combined electroencephalogram data; Perform independent component analysis in reverse on the preprocessed transcranial magnetic stimulation combined electroencephalogram data to obtain transcranial magnetic stimulation combined electroencephalogram data after artifact removal; Perform inverse wavelet transform on the transcranial magnetic stimulation combined electroencephalogram data after artifact removal to determine the electroencephalogram potential data; Determine the electroencephalogram oscillation data based on the transcranial magnetic stimulation combined electroencephalogram data after artifact removal.

[0007] In an alternative embodiment, the performing independent component analysis in reverse on the preprocessed transcranial magnetic stimulation combined electroencephalogram data to obtain transcranial magnetic stimulation combined electroencephalogram data after artifact removal includes: Segment the preprocessed transcranial magnetic stimulation combined electroencephalogram data to obtain a plurality of first electroencephalogram data segments; Perform time-axis inversion processing on each of the first electroencephalogram data segments to obtain a plurality of inverted first electroencephalogram data segments; Perform independent component analysis on each of the inverted first electroencephalogram data segments to obtain inverted independent component data; Separate the artifact component data in the inverted independent component data to obtain inverted independent component data after artifact removal; Perform time-axis restoration on the inverted independent component data after artifact removal to obtain the transcranial magnetic stimulation combined electroencephalogram data after artifact removal.

[0008] In an alternative embodiment, the performing inverse wavelet transform on the transcranial magnetic stimulation combined electroencephalogram data after artifact removal to determine the electroencephalogram potential data includes: Segment the transcranial magnetic stimulation combined electroencephalogram data after artifact removal to obtain a plurality of second electroencephalogram data segments; Perform time-axis inversion processing on each of the second electroencephalogram data segments to obtain a plurality of inverted second electroencephalogram data segments; Perform wavelet transform on each of the inverted second electroencephalogram data segments to obtain inverted wavelet coefficients; Perform time-axis restoration on the inverted wavelet coefficients to obtain wavelet coefficients; Determine the electroencephalogram potential data based on the wavelet coefficients.

[0009] In an alternative embodiment, the determining the electroencephalogram oscillation data based on the artifact-removed transcranial magnetic stimulation combined electroencephalogram data includes: Segment the artifact-removed transcranial magnetic stimulation combined electroencephalogram data to obtain a plurality of third electroencephalogram data segments; Obtain event-related spectral perturbation data and inter-trial coherence data based on the plurality of third electroencephalogram data segments; Determine the electroencephalogram oscillation data based on the event-related spectral perturbation data and the inter-trial coherence data.

[0010] In an alternative embodiment, the transcranial magnetic stimulation combined electroencephalogram report includes at least one of a total average transcranial magnetic stimulation evoked potential map, a spatio-temporal distribution map, a global average field power map, a local average field power map, an event-related spectral perturbation map, and an inter-trial coherence map.

[0011] In a second aspect, an embodiment of the present application provides a transcranial magnetic stimulation combined electroencephalogram data processing device, including: An acquisition module, configured to acquire transcranial magnetic stimulation combined electroencephalogram data; the transcranial magnetic stimulation combined electroencephalogram data is electroencephalogram data of a target object under transcranial magnetic stimulation with preset parameters; A determination module, configured to determine electroencephalogram potential data and electroencephalogram oscillation data based on the transcranial magnetic stimulation combined electroencephalogram data; A report generation module, configured to generate a transcranial magnetic stimulation combined electroencephalogram report based on the electroencephalogram potential data and the electroencephalogram oscillation data; the transcranial magnetic stimulation combined electroencephalogram report is used to perform a hierarchical evaluation on the transcranial magnetic stimulation combined electroencephalogram data.

[0012] In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor and a memory. At least one instruction, at least one program, a code set, or an instruction set is stored in the memory, and at least one instruction, at least one program, the code set, or the instruction set is loaded and executed by the processor to implement the transcranial magnetic stimulation combined electroencephalogram data processing method in the first aspect.

[0013] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which at least one instruction or at least one program is stored, and at least one instruction or at least one program is loaded and executed by the processor to implement the transcranial magnetic stimulation combined electroencephalogram data processing method in the first aspect.

[0014] Fifth aspect, an embodiment of the present application provides a computer program product or a computer program. The computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the transcranial magnetic stimulation combined with electroencephalogram data processing method of the first aspect.

[0015] The transcranial magnetic stimulation combined with electroencephalogram data processing method, device and storage medium provided by the embodiments of the present application have the following technical effects: Obtain transcranial magnetic stimulation combined with electroencephalogram data; the transcranial magnetic stimulation combined with electroencephalogram data is electroencephalogram data of a target object under transcranial magnetic stimulation with preset parameters; determine electroencephalogram potential data and electroencephalogram oscillation data based on the transcranial magnetic stimulation combined with electroencephalogram data; generate a transcranial magnetic stimulation combined with electroencephalogram report based on the electroencephalogram potential data and the electroencephalogram oscillation data; the transcranial magnetic stimulation combined with electroencephalogram report is used for grading evaluation of the transcranial magnetic stimulation combined with electroencephalogram data. By collecting the transcranial magnetic stimulation combined with electroencephalogram data while performing transcranial magnetic stimulation and processing the real-time transcranial magnetic stimulation combined with electroencephalogram data, the required electroencephalogram potential data and electroencephalogram oscillation data are obtained, and a report is generated, which is convenient for subsequent grading evaluation of electroencephalogram data and effectively utilizes the transcranial magnetic stimulation combined with electroencephalogram data. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0017] Figure 1 is a schematic diagram of an application environment provided by an embodiment of the present application; Figure 2 is a flowchart of a transcranial magnetic stimulation combined with electroencephalogram data processing method provided by an embodiment of the present application Figure 1 ; Figure 3 is a flowchart of a transcranial magnetic stimulation combined with electroencephalogram data processing method provided by an embodiment of the present application Figure 2 ; Figure 4 is an average potential map and spatio-temporal distribution map of a TEP provided by the present application; Figure 5 is a schematic diagram of the global average field power and local average field power of a TEP provided by the present application; Figure 6It is a schematic flowchart of an artifact removal method for transcranial magnetic stimulation combined with electroencephalogram data provided by an embodiment of the present application; Figure 7 It is a schematic structural diagram of a transcranial magnetic stimulation combined with electroencephalogram data processing device provided by an embodiment of the present application; Figure 8 It is a hardware structure block diagram of a server for a transcranial magnetic stimulation combined with electroencephalogram data processing method provided by an embodiment of the present application. Detailed implementation manners

[0018] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0019] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0020] Please refer to Figure 1 , Figure 1 It is a schematic diagram of an application environment provided by an embodiment of the present application. The transcranial magnetic stimulation combined with electroencephalogram data processing system includes a transcranial magnetic stimulation device 101, an electroencephalogram acquisition device 102, an electroencephalogram amplification device 103, and a transcranial magnetic stimulation combined with electroencephalogram data processing device 104.

[0021] In an optional embodiment, the electroencephalogram acquisition device includes an electroencephalogram cap, electroencephalogram electrodes, and an electroencephalogram cable.

[0022] Specifically, the electroencephalogram acquisition device 102 is used to acquire the electroencephalogram signals of the target object. Among them, multiple electroencephalogram electrodes are arranged inside the electroencephalogram cap, and the electroencephalogram cable connects each electrode to the electroencephalogram amplifier and transmits the electrical signals collected by the electrodes to the electroencephalogram amplifier for amplification. The electroencephalogram cap is used to fix the positions of multiple electrodes to ensure accurate positioning of brain regions.

[0023] In the embodiments of the present application, the EEG cap is made of silver or silver chloride and carbon fiber. Silver or silver chloride has high conductivity and stable chemical properties, and carbon fiber is light in weight and has a certain flexibility, which can better fit the head of the target object.

[0024] In the embodiments of the present application, conductive glue is provided on the contact surface of the EEG electrode, and an isolation shielding layer is provided on the other side. The conductive glue can fill the gap between the electrode and the scalp, reduce the resistance, and on the other hand, can also achieve moisturizing and prevent the electrode from falling off.

[0025] The isolation shielding layer can be configured as a metal foil wrap (such as aluminum foil) or a conductive polymer coating, which is used to shield external electromagnetic interference, especially the signal interference caused by transcranial magnetic stimulation equipment.

[0026] The EEG cable uses a double-layer shielded cable. For example, the outer shield uses a silver-plated copper braided mesh, which has a high-strength shielding effect, and the inner shield uses aramid fiber to enhance the tensile strength, support repeated bending, and also play a role in shielding external electromagnetic interference.

[0027] In an optional embodiment, the transcranial magnetic stimulation device 101 includes a transcranial magnetic coil; the EEG electrode and the transcranial magnetic stimulation coil are arranged by the parallel line method. Specifically, the electrode and the transcranial magnetic coil are arranged in the same direction (such as front-back or left-right symmetry) to minimize the electromagnetic coupling between the two. In addition, the distance between the electrode and the transcranial magnetic coil can also be controlled to be greater than a set distance (such as 0.5 cm) to reduce the induced voltage.

[0028] In an optional embodiment, the EEG amplification device is mainly used to amplify the electrical signals collected by the EEG device for subsequent use. The EEG amplification device includes an EEG amplification main board, and an amplifier module, a filtering module, and an artifact processing module are provided on the EEG amplification main board.

[0029] Specifically, a differential amplifier with a high sampling rate and a high dynamic range above 5 kHz is used. The differential amplifier can eliminate common-mode interference, capture fast-changing transcranial magnetic stimulation artifacts and perform subsequent processing. The filtering module can be a low-pass filter or a band-stop filter, which is used to remove transcranial magnetic stimulation artifacts in real time.

[0030] In an optional embodiment, an anti-magnetic field interference circuit can also be added to the EEG amplification main board to reduce the influence of the magnetic field on signal acquisition, improve the common-mode rejection ratio of the amplifier module, and reduce the influence of common-mode noise on the EEG signal.

[0031] Optionally, extending the cable length between the electrodes of the EEG acquisition device 102 and the EEG amplification device 103 can also reduce the possibility of magnetic field induction.

[0032] In an alternative embodiment, a non-magnetic material can also be used to wrap the connectors between the various devices to reduce magnetic field induction.

[0033] In an alternative embodiment, the transcranial magnetic stimulation combined with electroencephalogram data processing system further includes a magnetic field shielding room, and the transcranial magnetic stimulation device 101, the electroencephalogram acquisition device 102, and the electroencephalogram amplification device 103 are all arranged in the magnetic field shielding room.

[0034] The magnetic field shielding room can suppress external interference. The shielding room can reduce environmental noise and improve the signal-to-noise ratio of the electroencephalogram signal. At the same time, the magnetic field shielding room can block radio frequency interference and prevent wireless signals such as WiFi and Bluetooth from interfering with the electroencephalogram signal. Further, the magnetic field shielding room can block the diffusion of the magnetic field of the transcranial magnetic coil and avoid the contamination of the electroencephalogram signal by stimulation artifacts.

[0035] In an alternative embodiment, the transcranial magnetic stimulation combined with electroencephalogram data processing device 104 receives and processes the amplified electroencephalogram signal, including an acquisition module for acquiring transcranial magnetic stimulation combined with electroencephalogram data; the transcranial magnetic stimulation combined with electroencephalogram data is the electroencephalogram data of a target object under transcranial magnetic stimulation with preset parameters; a determination module for determining electroencephalogram potential data and electroencephalogram oscillation data based on the transcranial magnetic stimulation combined with electroencephalogram data; a report generation module for generating a transcranial magnetic stimulation combined with electroencephalogram report based on the electroencephalogram potential data and the electroencephalogram oscillation data; the transcranial magnetic stimulation combined with electroencephalogram report is used for grading and evaluating the transcranial magnetic stimulation combined with electroencephalogram data. During transcranial magnetic stimulation, the transcranial magnetic stimulation combined with electroencephalogram data is collected, and the real-time transcranial magnetic stimulation combined with electroencephalogram data is processed to obtain the required electroencephalogram potential data and electroencephalogram oscillation data, and a report is generated, which is convenient for subsequent grading and evaluation of electroencephalogram data and effectively utilizes the transcranial magnetic stimulation combined with electroencephalogram data.

[0036] The following introduces a specific embodiment of a method for processing transcranial magnetic stimulation combined with electroencephalogram data in the present application. Figure 2 It is a flowchart showing a method for processing transcranial magnetic stimulation combined with electroencephalogram data provided by an embodiment of the present application. Figure 1 This specification provides the method operation steps as in the embodiment or flowchart, but based on routine or non-creative labor, there can be more or fewer operation steps. The step order listed in the embodiment is only one way among the execution orders of numerous steps and does not represent the only execution order. When the actual system or server product executes, it can be executed in the order shown in the embodiment or the flowchart or executed in parallel (for example, in an environment of parallel processors or multi-threaded processing). Specifically, as Figure 2 shown, this method is applied to a transcranial magnetic stimulation combined with electroencephalogram data processing device and may include: S201: Obtain transcranial magnetic stimulation combined with electroencephalogram data; the transcranial magnetic stimulation combined with electroencephalogram data is the electroencephalogram data of the target object under transcranial magnetic stimulation with preset parameters.

[0037] S202: Determine electroencephalogram potential data and electroencephalogram oscillation data based on the transcranial magnetic stimulation combined with electroencephalogram data.

[0038] S203: Generate a transcranial magnetic stimulation combined with electroencephalogram report based on the electroencephalogram potential data and the electroencephalogram oscillation data; the transcranial magnetic stimulation combined with electroencephalogram report is used to perform a grading evaluation on the transcranial magnetic stimulation combined with electroencephalogram data.

[0039] Figure 3 It is a flowchart of a method for processing transcranial magnetic stimulation combined with electroencephalogram data provided by an embodiment of the present application Figure 2 The method may include: S301: Obtain transcranial magnetic stimulation combined with electroencephalogram data.

[0040] In a possible embodiment, the transcranial magnetic stimulation combined with electroencephalogram data is the electroencephalogram data of the target object under transcranial magnetic stimulation with preset parameters.

[0041] In the embodiment of the present application, the target object is a user who needs transcranial magnetic stimulation, and may be a patient with disorders of consciousness, cognitive impairment, mental disorders, etc.

[0042] Before performing transcranial magnetic stimulation, first connect an electroencephalogram acquisition device to collect the basic electroencephalogram data of the user, and use the electroencephalogram data without the influence of transcranial magnetic stimulation to adjust the transcranial magnetic stimulation parameters.

[0043] In a possible embodiment, the preset parameters are usually standard parameters based on population data or clinical guidelines, and the preset parameters may include stimulation intensity parameters, stimulation frequency parameters, stimulation position parameters, etc. The preset parameters for different users are different.

[0044] Taking the grading evaluation of the user's mental disorder as an example, the preset parameters can be a stimulation frequency of 1 Hz, a stimulation intensity parameter of 40% of the resting motor threshold, and a stimulation position parameter of the left dorsolateral prefrontal cortex.

[0045] S302: Preprocess the transcranial magnetic stimulation combined with electroencephalogram data to obtain the preprocessed transcranial magnetic stimulation combined with electroencephalogram data.

[0046] In a possible embodiment, the preprocessing may include using a band-pass filter of 0.5 - 80 Hz to remove low-frequency drift and high-frequency non-physiological noise; and optionally interpolating the signal or marking it as NaN near the stimulation point (such as within 0 - 10 ms) to weaken the influence of transient extreme values.

[0047] S303: Perform independent component analysis in reverse on the preprocessed transcranial magnetic stimulation combined with electroencephalogram data to obtain the transcranial magnetic stimulation combined with electroencephalogram data after artifact removal.

[0048] S304: Perform inverse wavelet transform on the transcranial magnetic stimulation combined with electroencephalogram data after artifact removal to determine the electroencephalogram potential data.

[0049] In the embodiment of the present application, the electroencephalogram potential data refers to the transcranial magnetic stimulation evoked potential (TMS-Evoked Potential, TEP) signal, and more specifically refers to the P30 and N45 components in TEP. Among them, P30 represents a latency of 30 ms and an amplitude orientation of positive, that is, P30 appears at 30 ms, which is a direct indicator reflecting cortical excitability. Similarly, N45 is an indicator reflecting cortical inhibition.

[0050] In a possible embodiment, performing inverse wavelet transform on the transcranial magnetic stimulation combined with electroencephalogram data after artifact removal to determine the electroencephalogram potential data includes: S3041: Segment the transcranial magnetic stimulation combined with electroencephalogram data after artifact removal to obtain multiple second electroencephalogram data segments.

[0051] S3042: Perform time-axis inversion processing on each of the second electroencephalogram data segments to obtain multiple inverted second electroencephalogram data segments.

[0052] S3043: Perform wavelet transform on each of the inverted second electroencephalogram data segments to obtain inverted wavelet coefficients.

[0053] S3044: Restore the time axis of the inverted wavelet coefficients to obtain wavelet coefficients.

[0054] S3045: Determine the electroencephalogram potential data based on the wavelet coefficients.

[0055] Specifically, in the above inverse wavelet transform processing, the signal corresponding to each stimulation can be intercepted as an independent second electroencephalogram data segment, and the time axis of each second electroencephalogram data segment is inverted to form a new time series. This inversion enables the wavelet decomposition algorithm to preferentially access the relatively "clean" later electroencephalogram activities when processing the signal, avoiding misleading the processing model by the early signals dominated by artifacts. Then, wavelet decomposition is applied to each inverted electroencephalogram signal to obtain inverted wavelet coefficients. It is preferably to use the Daubechies wavelet function (db4) because it has strong detection ability for mutation signals. Finally, the inverted wavelet coefficients are inverted again to return to the original time series order, that is, the wavelet transform from back to front is completed.

[0056] After the inverse wavelet transform processing, a transcranial magnetic stimulation evoked potential (TMS-Evoked Potential, TEP) component map is constructed based on the forward wavelet coefficients. Based on the image, the signal in the interval of 30 - 50 ms after stimulation can be selected for visualization and quantitative analysis.

[0057] The experimental results in the embodiments of this application show that the classic P30 and N45 component waveforms can be clearly observed in this section. Compared with the original signal, the signal in this time window is no longer submerged by the instantaneous high-frequency noise induced by TMS, and the signal-to-noise ratio is significantly improved.

[0058] In other possible embodiments, the following method can also be used for wavelet analysis: The fast continuous wavelet transform (fCWT) is used to analyze the transcranial magnetic stimulation combined with electroencephalogram data. By convolving the signal with sub-wavelets of different scales and positions, the time-frequency characteristics of the signal are extracted. The specific scheme is as follows: First, preprocess the electroencephalogram signal, obtain the frequency domain representation using the fast Fourier transform, and generate the mother wavelet in the frequency domain; By downsampling the mother wavelet, sub-wavelets of different scales are obtained. After parallel computing, the inverse Fourier transform is used to obtain the wavelet coefficients in the time domain method; Visualize the wavelet coefficient results, with the horizontal axis being time and the vertical axis being amplitude, to obtain the final transcranial magnetic stimulation evoked potential (TMS-Evoked Potential, TEP) component map.

[0059] S305: Based on the transcranial magnetic stimulation combined with electroencephalogram data after removing artifacts, determine the electroencephalogram oscillation data.

[0060] In the embodiments of this application, the electroencephalogram oscillation data refers to the transcranial magnetic stimulation induced oscillation (TMS-InducedOscillation, TIO) signal.

[0061] In a possible embodiment, based on the transcranial magnetic stimulation combined with electroencephalogram data after removing artifacts, determining the electroencephalogram oscillation data includes: S3051: Segment the transcranial magnetic stimulation combined with electroencephalogram data after removing artifacts to obtain multiple third electroencephalogram data segments.

[0062] S3052: Obtain event-related spectral perturbation data and inter-trial coherence data based on the multiple third electroencephalogram data segments.

[0063] S3053: Determine the electroencephalogram oscillation data based on the event-related spectral perturbation data and the inter-trial coherence data.

[0064] Among them, obtaining event-related spectral perturbation data includes: performing short-time Fourier transform (STFT) on the EEG data of each trial to obtain spectral estimation; performing single-trial baseline correction before trial averaging, that is, performing baseline correction on each trial to reduce the influence of noisy trials; calculating the average value of spectral power of all trials; converting the result to decibel (dB) units to represent the power change relative to the baseline.

[0065] Obtaining inter-trial coherence data includes: extracting phase information from the spectral estimation of each trial; calculating the average value of phase vectors of all trials.

[0066] ERSP and ITC analyze EEG oscillation data from two dimensions of power and phase respectively. ERSP reveals "whether it is activated" (power change), and ITC reveals "how to cooperate" (phase synchronization). The combined use of the two can more accurately reflect the specific situation of EEG oscillation data, and further achieve the purpose of accurately evaluating the functional connection between cortical regions.

[0067] S306: Generate a transcranial magnetic stimulation combined with EEG report based on the EEG potential data and the EEG oscillation data.

[0068] In the embodiment of the present application, the transcranial magnetic stimulation combined with EEG report includes at least one of a total average transcranial magnetic stimulation evoked potential map, a spatio-temporal distribution map, a global average field power map, a local average field power map, an event-related spectral perturbation map, and an inter-trial coherence map.

[0069] In the embodiment of the present application, the transcranial magnetic stimulation combined with EEG report may include a transcranial magnetic stimulation evoked potential (TMS-Evoked Potential, TEP) report and a transcranial magnetic stimulation induced oscillation (TMS-Induced Oscillation, TIO) report.

[0070] Figure 4 It is an average potential map and a spatio-temporal distribution map of a TEP provided by the present application. The average potential map (butterfly map) visualizes data such as the latency, amplitude, and waveform of the TEP by superimposing multi-channel EEG signals. The spatio-temporal distribution map is used to display the time dynamics (such as the timing of wave peaks) and spatial distribution (such as the cortical activation range) of the TEP signal, revealing the brain network activation pattern and signal propagation path.

[0071] In Figure 4 P22 represents that the latency is 22 ms and the amplitude orientation is positive, that is, the P22 component appears at 22 ms; P63 represents that the latency is 63 ms and the amplitude orientation is positive, that is, the P63 component appears at 63 ms; P163 represents that the latency is 163 ms and the amplitude orientation is positive, that is, the P163 component appears at 163 ms.

[0072] Correspondingly, N44 represents a latency of 44 ms with a negative amplitude orientation, i.e., the N44 component appears at 44 ms; N94 represents a latency of 94 ms with a negative amplitude orientation, i.e., the N94 component appears at 94 ms; N281 represents a latency of 281 ms with a negative amplitude orientation, i.e., the N281 component appears at 281 ms.

[0073] Furthermore, Figure 5 It is a schematic diagram of the global mean field power and local mean field power of a TEP provided by this application. Among them, the global mean field power (GMFP) quantifies the intensity of the electroencephalogram activity of the whole brain and reflects the global activation level of the brain after stimulation. The local mean field power (LMFP) quantifies the activity intensity of a specific brain region and reflects the activation level of the local neural network.

[0074] The TIO report includes a schematic diagram of event-related spectral perturbation and a schematic diagram of inter-trial coherence. Event-related spectral perturbation (ERSP) quantifies the change of energy over time in a specific frequency band (such as the 4 - 40 Hz band, including the θ, α, β1, β2, γ bands) after stimulation, and identifies energy enhancement (ERS) or attenuation (ERD), which is suitable for analyzing energy characteristics and time dynamics.

[0075] Inter-trial coherence (ITC) is used to quantify the phase consistency of brain activities, reveal phase locking, and is suitable for analyzing phase characteristics and time dynamics. These two methods complement each other in electroencephalogram signal analysis, helping researchers comprehensively understand the frequency domain characteristics of brain activities from the perspectives of energy and phase.

[0076] In the embodiments of this application, by visually displaying the TEP report (waveform, spatio-temporal, GMFP / LMFP) and the TIO report (ERSP, ITC), the regulatory effect of TMS on the brain is analyzed from multiple dimensions of time, space, energy, and phase. This multi-modal analysis method helps to determine the next cycle of transcranial magnetic stimulation from multiple angles, providing a dynamic, three-dimensional, and quantifiable evaluation framework for precise closed-loop feedback control.

[0077] Since the strong magnetic field generated by transcranial magnetic stimulation will interfere with the electroencephalogram data recording, it is necessary to effectively remove the artifacts from the transcranial magnetic stimulation combined with electroencephalogram data. Figure 6 It is a schematic flowchart of a method for removing artifacts from transcranial magnetic stimulation combined with electroencephalogram data provided by the embodiments of this application. This method may include: S401: Segment the preprocessed transcranial magnetic stimulation combined with electroencephalogram data to obtain a plurality of first electroencephalogram data segments.

[0078] S402: Perform time-axis inversion processing on each of the first EEG data segments to obtain multiple inverted first EEG data segments.

[0079] S403: Perform independent component analysis on each of the inverted first EEG data segments to obtain inverted independent component data.

[0080] S404: Separate the artifact component data from the inverted independent component data to obtain inverted independent component data after artifact removal.

[0081] S405: Perform time-axis restoration on the inverted independent component data after artifact removal to obtain the transcranial magnetic stimulation combined with EEG data after artifact removal.

[0082] Specifically, in the above-mentioned independent component analysis (ICA) reverse processing, the signal corresponding to each stimulation can be intercepted as an independent first EEG data segment, and each first EEG data segment is processed by time dimension inversion, that is, the data is arranged forward from 500 ms after the stimulation to 500 ms before the stimulation. This operation flips the data in the time dimension, but keeps the channel and sampling information unchanged.

[0083] This can ensure that when the ICA algorithm "first contacts" the cleaner signal part, a more stable and representative independent source distribution model is established, avoiding being dominated by artifacts.

[0084] Based on the inverted data, use the ICA algorithm to perform blind source separation on the EEG signal, identify and remove the artifact components therein, and finally reverse the EEG data in the time dimension again to restore the original time order.

[0085] In another possible embodiment, artifact removal can also be performed using forward independent component analysis. Specifically, the Fast Independent Component Analysis algorithm (FastICA) is used to utilize the characteristic that the mixed signal tends to be Gaussian distributed, and the independent components in the signal are separated by maximizing non-Gaussianity (such as sparsity) to achieve the purpose of removing artifact interference and separating specific components from the EEG signal. The specific solution is as follows: Perform data preprocessing, perform centering and whitening processing on the obtained EEG signal to accelerate the algorithm convergence, remove signal correlation, and ensure the accuracy of the separation direction.

[0086] Randomly initialize a unit vector for each independent component and perform fixed-point iteration optimization separately. The steps include: continuously determining the optimal iteration direction using the direction of the negative entropy gradient to make the algorithm approach the optimal separation matrix faster; preventing all unit vectors from converging to the same direction to cause data redundancy, so it is required that each unit vector is orthogonal to other unit vectors; ensuring the unit length of the unit vector during the iteration process to avoid numerical instability; finally, if it is determined that the vector converges, stop the iteration.

[0087] All the unit vectors after iterative optimization obtain the separation matrix, and the independent components are estimated through the separation matrix to achieve the purpose of the algorithm.

[0088] In other possible embodiments, other artifact removal methods can also be used, as long as they can achieve the purpose of removing artifacts. For example: Perform linear decomposition processing on the preprocessed transcranial magnetic stimulation combined with electroencephalogram data, separate the first artifact signal from the preprocessed transcranial magnetic stimulation combined with electroencephalogram data, and obtain the transcranial magnetic stimulation combined with electroencephalogram data after linear decomposition.

[0089] In a possible embodiment, the linear decomposition processing includes any one of principal component analysis processing and blind source separation processing.

[0090] Perform frequency-domain filtering processing on the transcranial magnetic stimulation combined with electroencephalogram data after linear decomposition to obtain the transcranial magnetic stimulation combined with electroencephalogram data after frequency-domain filtering.

[0091] Input the transcranial magnetic stimulation combined with electroencephalogram data after frequency-domain filtering into the trained artifact separation model to obtain the transcranial magnetic stimulation combined with electroencephalogram data after artifact separation.

[0092] Through the multiple artifact removal of the above linear decomposition, frequency-domain filtering, and artifact separation model, the artifact influence in the electroencephalogram data under transcranial magnetic stimulation can be effectively removed.

[0093] The embodiment of the present application also provides a transcranial magnetic stimulation combined with electroencephalogram data processing device. Figure 7 It is a schematic structural diagram of a transcranial magnetic stimulation combined with electroencephalogram data processing device provided by the embodiment of the present application, as Figure 7 shown. The device 500 includes: An acquisition module 510, configured to acquire transcranial magnetic stimulation combined with electroencephalogram data; the transcranial magnetic stimulation combined with electroencephalogram data is the electroencephalogram data of the target object under transcranial magnetic stimulation with preset parameters; A determination module 520, configured to determine electroencephalogram potential data and electroencephalogram oscillation data based on the transcranial magnetic stimulation combined with electroencephalogram data; A report generation module 530 is configured to generate a transcranial magnetic stimulation combined electroencephalogram report based on the electroencephalogram potential data and the electroencephalogram oscillation data; the transcranial magnetic stimulation combined electroencephalogram report is used for grading and evaluating the transcranial magnetic stimulation combined electroencephalogram data.

[0094] In an alternative embodiment, the determination module is further configured to: Preprocess the transcranial magnetic stimulation combined electroencephalogram data to obtain preprocessed transcranial magnetic stimulation combined electroencephalogram data; Perform independent component analysis in the reverse direction on the preprocessed transcranial magnetic stimulation combined electroencephalogram data to obtain transcranial magnetic stimulation combined electroencephalogram data after artifact removal; Perform inverse wavelet transform on the transcranial magnetic stimulation combined electroencephalogram data after artifact removal to determine the electroencephalogram potential data; Determine the electroencephalogram oscillation data based on the transcranial magnetic stimulation combined electroencephalogram data after artifact removal.

[0095] In an alternative embodiment, the determination module further includes: Segment the preprocessed transcranial magnetic stimulation combined electroencephalogram data to obtain a plurality of first electroencephalogram data segments; Perform time-axis inversion processing on each of the first electroencephalogram data segments to obtain a plurality of inverted first electroencephalogram data segments; Perform independent component analysis on each of the inverted first electroencephalogram data segments to obtain inverted independent component data; Separate the artifact component data in the inverted independent component data to obtain inverted independent component data after artifact removal; Perform time-axis restoration on the inverted independent component data after artifact removal to obtain the transcranial magnetic stimulation combined electroencephalogram data after artifact removal.

[0096] In an alternative embodiment, the determination module is further configured to: Segment the transcranial magnetic stimulation combined electroencephalogram data after artifact removal to obtain a plurality of second electroencephalogram data segments; Perform time-axis inversion processing on each of the second electroencephalogram data segments to obtain a plurality of inverted second electroencephalogram data segments; Perform wavelet transform on each of the inverted second electroencephalogram data segments to obtain inverted wavelet coefficients; Perform time-axis restoration on the inverted wavelet coefficients to obtain wavelet coefficients; Determine the electroencephalogram potential data based on the wavelet coefficients.

[0097] In an alternative embodiment, the determination module is further configured to: Segment the artifact-removed transcranial magnetic stimulation (TMS) combined with electroencephalogram (EEG) data to obtain a plurality of third EEG data segments; Obtain event-related spectral perturbation (ERSP) data and inter-trial coherence (ITC) data based on the plurality of third EEG data segments; Determine the EEG oscillation data based on the ERSP data and the ITC data.

[0098] In an alternative embodiment, the TMS combined with EEG report includes at least one of a grand-average TMS-evoked potential topographic map, a spatio-temporal distribution map, a global average field power map, a local average field power map, an ERSP map, and an ITC map.

[0099] The device and method embodiments in this application are based on the same application concept.

[0100] The method embodiments provided in the embodiments of this application can be executed on a computer terminal, a server, or a similar computing device. Taking running on a server as an example, Figure 8 is a hardware structure block diagram of a server for the TMS combined with EEG data processing method provided in the embodiments of this application. As Figure 8 shown, the server 600 may vary greatly due to configuration or performance differences, and may include one or more central processing units (CPUs) 610 (the central processing unit 610 may include, but is not limited to, a processing device such as a microprocessor MCU or a field programmable gate array FPGA), a memory 630 for storing data, and one or more storage media 620 for storing application programs 623 or data 622 (such as one or more mass storage devices). Among them, the memory 630 and the storage media 620 may be transient storage or persistent storage. The program stored in the storage media 620 may include one or more modules, and each module may include a series of instruction operations on the server. Further, the central processing unit 610 may be configured to communicate with the storage media 620 and execute a series of instruction operations in the storage media 620 on the server 600. The server 600 may also include one or more power supplies 660, one or more wired or wireless network interfaces 650, one or more input / output interfaces 640, and / or one or more operating systems 621, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, and so on.

[0101] The input / output interface 640 can be used to receive or transmit data via a network. Specific examples of the above-mentioned network can include a wireless network provided by a communication provider of the server 600. In one example, the input / output interface 640 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the input / output interface 640 can be a RadioFrequency (RF) module, which is used to communicate with the Internet wirelessly.

[0102] Those of ordinary skill in the art can understand that Figure 8 The structure shown is only schematic and does not limit the structure of the above-mentioned electronic device. For example, the server 600 may further include more or fewer components than those shown in Figure 8 or have a different configuration from that shown in Figure 8 shown.

[0103] The embodiment of the present application provides an electronic device, which includes a processor and a memory. At least one instruction, at least one segment of program, code set or instruction set is stored in the memory, and the at least one instruction, at least one segment of program, code set or instruction set is loaded and executed by the processor to implement the above-mentioned data processing method.

[0104] The embodiment of the present application further provides a computer-readable storage medium. The storage medium can be disposed in the server to store at least one instruction, at least one segment of program, code set or instruction set related to a transcranial magnetic stimulation combined with electroencephalogram data processing method in the method embodiment. The at least one instruction, the at least one segment of program, the code set or instruction set is loaded and executed by the processor to implement the above-mentioned transcranial magnetic stimulation combined with electroencephalogram data processing method.

[0105] Optionally, in this embodiment, the above storage medium can be located in at least one of multiple network servers in a computer network. Optionally, in this embodiment, the above storage medium can include, but is not limited to: various media that can store program codes such as USB flash drives, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), mobile hard disks, magnetic disks or optical discs.

[0106] As can be seen from the embodiments of the transcranial magnetic stimulation combined with electroencephalogram data processing method, device, electronic device or storage medium provided by the present application above, in the present application, the transcranial magnetic stimulation parameters of the current cycle are obtained; the first electroencephalogram data under the transcranial magnetic stimulation parameters of the current cycle is obtained; the first electroencephalogram data is analyzed to determine the first electroencephalogram report; the first electroencephalogram report is used to reflect the activity state information of the brain of the target object under a preset task; based on the first electroencephalogram report, the transcranial magnetic stimulation parameters of the next cycle are determined; the transcranial magnetic stimulation parameters of the next cycle are used to obtain the first electroencephalogram data of the next cycle. By collecting electroencephalogram data while performing transcranial magnetic stimulation and processing the real-time electroencephalogram data, the transcranial magnetic stimulation parameters of the next cycle are adjusted, and the electroencephalogram signal is used as an important benchmark for transcranial magnetic stimulation feedback regulation, so that indicators such as the depth, intensity, and position accuracy of transcranial magnetic stimulation are effectively improved.

[0107] It should be noted that: the above order of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the specific embodiments of the present specification have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve the desired results. Additionally, the processes depicted in the figures do not necessarily require the particular order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0108] Each embodiment in this specification is described in a progressive manner. The same or similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0109] Those of ordinary skill in the art can understand that all or part of the steps to implement the above embodiments can be completed by hardware, or can be completed by a program instructing relevant hardware. The program can be stored in a computer-readable storage medium. The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disc, etc.

[0110] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A transcranial magnetic stimulation combined with electroencephalogram data processing method, characterized in that: include: Acquire transcranial magnetic stimulation combined with electroencephalogram (EEG) data; the transcranial magnetic stimulation combined with electroencephalogram (EEG) data is the EEG data of the target subject under transcranial magnetic stimulation with preset parameters; Determining EEG potential data and EEG oscillation data based on the transcranial magnetic stimulation combined with EEG data; Based on the EEG potential data and the EEG oscillation data, a transcranial magnetic stimulation combined with EEG report is generated; the transcranial magnetic stimulation combined with EEG report is used to perform a graded evaluation on the transcranial magnetic stimulation combined with EEG data.

2. A transcranial magnetic stimulation combined with electroencephalogram data processing method according to claim 1, characterized in that: The determining of EEG potential data and EEG oscillation data based on the transcranial magnetic stimulation combined with EEG data includes: Preprocessing the transcranial magnetic stimulation combined with electroencephalogram data to obtain preprocessed transcranial magnetic stimulation combined with electroencephalogram data; Performing inverse independent component analysis on the preprocessed transcranial magnetic stimulation combined with electroencephalogram data to obtain the transcranial magnetic stimulation combined with electroencephalogram data after artifact removal; Performing inverse wavelet transform processing on the artifact-removed transcranial magnetic stimulation combined with electroencephalogram data to determine the electroencephalogram potential data; The electroencephalogram (EEG) oscillation data is determined based on the artifact-removed transcranial magnetic stimulation combined with electroencephalogram (EEG) data.

3. A transcranial magnetic stimulation combined with electroencephalogram data processing method according to claim 2, characterized in that: The performing of inverse independent component analysis on the pre-processed transcranial magnetic stimulation combined with electroencephalogram data to obtain the transcranial magnetic stimulation combined with electroencephalogram data after removing artifacts includes: Segmenting the preprocessed transcranial magnetic stimulation combined with electroencephalogram (EEG) data to obtain a plurality of first EEG data segments; Performing time axis inversion processing on each of the first EEG data segments to obtain a plurality of inverted first EEG data segments; Performing independent component analysis on each of the inverted first EEG data segments to obtain inverted independent component data; Separating the artifact component data from the inverted independent component data to obtain the inverted independent component data after the artifacts are removed; The time axis of the inverted independent component data after the artifacts are removed is restored to obtain the transcranial magnetic stimulation combined with electroencephalogram data after the artifacts are removed.

4. A transcranial magnetic stimulation combined with electroencephalogram data processing method according to claim 2, characterized in that: The performing inverse wavelet transform processing on the artifact-removed transcranial magnetic stimulation combined with electroencephalogram data to determine the electroencephalogram potential data includes: Segmenting the artifact-removed transcranial magnetic stimulation combined with electroencephalogram (EEG) data to obtain a plurality of second EEG data segments; Performing time axis inversion processing on each of the second EEG data segments to obtain a plurality of inverted second EEG data segments; Performing wavelet transform on each of the inverted second EEG data segments to obtain inverted wavelet coefficients; Performing time axis restoration on the inverted wavelet coefficients to obtain wavelet coefficients; The brain potential data is determined based on the wavelet coefficients.

5. The method for processing transcranial magnetic stimulation combined with electroencephalogram data according to claim 2, characterized in that: The determining of the EEG oscillation data based on the TMS combined EEG data after removing the artifacts includes: Segmenting the artifact-removed transcranial magnetic stimulation combined with electroencephalogram (EEG) data to obtain a plurality of third EEG data segments; Acquiring event-related spectral perturbation data and inter-trial coherence based on the plurality of third EEG data segments; The EEG oscillation data is determined based on the event-related spectral perturbation data and the inter-trial coherence.

6. A transcranial magnetic stimulation combined with electroencephalogram data processing method according to claim 1, characterized in that: The transcranial magnetic stimulation combined with electroencephalogram report includes at least one of a total average transcranial magnetic stimulation evoked potential map, a spatiotemporal distribution map, a global average field power map, a local average field power map, an event-related spectral perturbation map, and an inter-trial coherence map.

7. A transcranial magnetic stimulation combined with electroencephalogram data processing device, characterized in that: include: An acquisition module is used to acquire transcranial magnetic stimulation combined with electroencephalogram data; the transcranial magnetic stimulation combined with electroencephalogram data is the electroencephalogram data of the target object under transcranial magnetic stimulation with preset parameters; A determination module, used to determine EEG potential data and EEG oscillation data based on the transcranial magnetic stimulation combined with EEG data; A report generation module is used to generate a transcranial magnetic stimulation combined with EEG report based on the EEG potential data and the EEG oscillation data; the transcranial magnetic stimulation combined with EEG report is used to perform a graded evaluation on the transcranial magnetic stimulation combined with EEG data.

8. An electronic device, characterized in that: The electronic device includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the transcranial magnetic stimulation combined with electroencephalographic data processing method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one instruction or at least one program, and the at least one instruction or the at least one program is loaded and executed by the processor to implement the transcranial magnetic stimulation combined with electroencephalographic data processing method as described in any one of claims 1-6.

10. A computer program product, characterized in that The computer program product includes computer instructions, which are stored in a computer-readable storage medium. The processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the transcranial magnetic stimulation combined with electroencephalogram data processing method as described in any one of claims 1-6.

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