CES treatment electroencephalogram signal monitoring and reliable electroencephalogram recording method and system

Abstract

The invention discloses a CES treatment electroencephalogram signal monitoring and reliable electroencephalogram recording method, which comprises the following steps: collecting CES treatment electroencephalogram signal data, segmenting into electroencephalogram signal data before stimulation, during stimulation and after stimulation according to starting and ending time of micro-current stimulation, and checking all segmented electroencephalogram signal data; corrected electroencephalogram signal data during stimulation are selected, and stable electroencephalogram signals are segmented according to time and analyzed and extracted based on data signals; reliable electroencephalogram signals in the stable electroencephalogram signals are screened based on filtering, and data enhancement is carried out; integrating the enhanced reliable electroencephalogram signal and the corrected electroencephalogram signal data before and after stimulation based on time alignment to obtain a complete reliable electroencephalogram signal change curve; and processing the complete reliable electroencephalogram signal change curve based on feature analysis, and obtaining a visual monitoring result of the target electroencephalogram activity.

Description

Technical Field

[0001] The present invention relates to the field of biomedical signal processing, and in particular to a method and system for monitoring and reliably recording EEG signals during CES treatment. Background Art

[0002] As a non-invasive neuromodulation technology, CES has been widely used to treat neurological disorders such as depression and anxiety. CES uses a variable signal with significantly higher signal strength than electroencephalogram (EEG) signals. Therefore, during stimulation, the CES signal can overwhelm the EEG signal, severely interfering with EEG acquisition. This makes it difficult for traditional EEG signal processing techniques to extract usable information during stimulation.

[0003] Currently, analysis of stimulation effects primarily relies on pre- and post-stimulation EEG data. However, a significant amount of data during the stimulation process is discarded due to interference, resulting in a limited amount of usable signal and an inability to monitor the continuous dynamic changes in the EEG signals during stimulation. Existing methods can only observe "jump-like" results before and after stimulation, lacking control over the intermediate processes and making it difficult to reveal the real-time mechanism of stimulation. However, stimulation signals severely interfere with electroencephalogram (EEG) signal acquisition, making it difficult for traditional methods to extract effective information about the stimulation process. Current research primarily relies on pre- and post-stimulation EEG data, discarding a significant amount of interference during the stimulation process. This not only reduces data utilization but also makes it impossible to monitor the continuous dynamic changes in the EEG signals. This "jump-like" analysis makes it difficult to reveal the real-time mechanism of stimulation. Summary of the Invention

[0004] In order to overcome the technical problem in the prior art that it is difficult to extract usable EEG signals during CES treatment, the present invention provides a method and system for monitoring and reliably recording EEG signals during CES treatment. The method extracts stable EEG signals and directly extracts reliable EEG signals during the stimulation process based on the target EEG activity to reflect effective neural activity information. At the same time, the method can dynamically monitor the continuous changes of EEG signals during the stimulation process, which is of great significance for revealing the real-time dynamic effects of the stimulation and provides technical support for monitoring the entire CES treatment process and judging the treatment effect.

[0005] According to one aspect of the present invention, a method for monitoring and reliably recording EEG signals during CES treatment is provided, comprising:

[0006] Collect CES treatment EEG signal data and segment it into EEG signal data before, during, and after stimulation according to the start and end time of microcurrent stimulation. Then proofread all segmented EEG signal data.

[0007] Select the corrected EEG signal data during stimulation, segment it by time, and extract the stable EEG signal based on data signal analysis;

[0008] Based on filtering to screen reliable EEG signals from stable EEG signals and perform data enhancement;

[0009] Based on the time alignment and integration of the enhanced reliable EEG signal and the corrected EEG signal data before and after stimulation, a complete reliable EEG signal change curve is obtained;

[0010] Based on feature analysis and processing, a complete and reliable EEG signal change curve is obtained to obtain the visual monitoring results of the target EEG activity.

[0011] As a further embodiment, the step of calibrating the EEG signal data includes:

[0012] Save EEG signal data and perform preprocessing;

[0013] The channels and time periods containing significant artifacts in the preprocessed EEG signal data are marked and removed to obtain the corrected EEG signal data.

[0014] As a further embodiment, the step of extracting a stable EEG signal includes:

[0015] The length of the time window and the sliding step size are preset to divide the corrected EEG signal data during stimulation into several short time period signals, wherein the sliding step size of the time window is smaller than the length of the time window;

[0016] Calculate the comprehensive stability index of each short-time period signal, preset the threshold of the comprehensive stability index, filter the short-time period signals based on the threshold, and use the filtered results as stable EEG signals.

[0017] As a further implementation scheme, the comprehensive stability index is a weighted result of the local mean and local variance of the signal in a short time period.

[0018] As a further embodiment, the step of screening reliable EEG signals from stable EEG signals based on filtering includes:

[0019] Band-pass filtering is performed on stable EEG signals based on the EEG frequency band, retaining stable EEG signals within the frequency band;

[0020] Use wavelet decomposition to decompose the stable EEG signal after bandpass filtering into multiple frequency bands, screen the frequency bands related to the target EEG activity, and reconstruct the stable EEG signal based on the screened frequency bands to obtain a reliable EEG signal;

[0021] An adaptive filter is used to remove residual noise from the reconstructed EEG signal to obtain an enhanced and reliable EEG signal.

[0022] As a further implementation scheme, the integration process of a complete and reliable EEG signal change curve includes:

[0023] The enhanced reliable EEG signals are arranged in time sequence and time-aligned to obtain a continuous EEG signal time series as the EEG signal curve during stimulation;

[0024] The EEG signals before, during and after stimulation are integrated along the time axis to generate a complete and reliable EEG signal change curve.

[0025] As a further implementation scheme, the steps for obtaining the visual monitoring results are:

[0026] Characteristic parameters are set according to the target EEG activity, and the characteristic parameters in the complete and reliable EEG signal change curve are extracted and visualized to obtain the visual monitoring results of the characteristic parameters during the CES process.

[0027] According to another aspect of the present invention, a CES treatment EEG signal monitoring and reliable EEG recording system is provided, comprising:

[0028] EEG data acquisition module, CES treatment EEG data acquisition and segmentation;

[0029] The stable EEG signal extraction module divides the corrected EEG signal data during stimulation into time segments and extracts stable EEG signals based on data signal analysis and data enhancement;

[0030] Reliable EEG signal screening module, screening reliable EEG signals from stable EEG signals and performing data enhancement;

[0031] EEG signal curve integration module, used to integrate complete and reliable EEG signal change curves;

[0032] Visual monitoring module, feature analysis obtains visual monitoring results of target EEG activity.

[0033] As a further embodiment, the steps for screening reliable EEG signals are:

[0034] Band-pass filtering is performed on stable EEG signals based on the EEG frequency band, retaining stable EEG signals within the frequency band;

[0035] Wavelet decomposition is used to decompose the stable EEG signal after bandpass filtering into multiple frequency bands, and the frequency bands related to the target EEG activity are screened. The stable EEG signal based on the screened frequency bands is reconstructed to obtain a reliable EEG signal.

[0036] According to another aspect of the present invention, a device for monitoring and reliably recording EEG signals during CES treatment is provided, comprising:

[0037] CES brain electrical stimulation therapy device, used for CES treatment;

[0038] The CES treatment EEG signal detection device is used to collect CES treatment EEG signals and provide visual monitoring results of target EEG activities.

[0039] Compared with the existing technology, the beneficial effects of the present invention are: the present invention reflects effective neural activity information by extracting stable EEG signals that are not affected by microcurrent stimulation and directly extracting reliable EEG signals during the stimulation process based on the target EEG activity. At the same time, it can dynamically monitor the continuous changes of EEG signals during the stimulation process, which is of great significance for revealing the real-time dynamic effects of stimulation, and provides technical support for monitoring the entire CES treatment process and judging the treatment effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, a brief introduction will be given below to the drawings used in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0041] Figure 1 Schematic diagram of the process of monitoring and reliably recording EEG signals during CES treatment according to an embodiment of the present invention;

[0042] Figure 2 This is a flow chart of brain electrical stimulation signal monitoring according to an embodiment of the present invention;

[0043] Figure 3 A schematic diagram of data segmentation by setting markers according to an embodiment of the present invention;

[0044] Figure 4 Schematic diagram of data segmentation through waveform detection and judgment according to an embodiment of the present invention;

[0045] Figure 5 Schematic diagram of segmenting a long signal using a sliding window method in an embodiment of the present invention;

[0046] Figure 6 Schematic diagram of the results of stability testing in an embodiment of the present invention;

[0047] Figure 7 is a schematic diagram of arranging stable signals during multiple relative stimulation processes in a time series according to an embodiment of the present invention;

[0048] Figure 8 This is the alpha wave data analysis result after the signals before, during and after stimulation are merged in the embodiment of the present invention;

[0049] Figure 9This is the beta wave data analysis result after the signals before, during and after stimulation are combined in the embodiment of the present invention;

[0050] Figure 10 This is a structural diagram of a CES treatment EEG signal monitoring and reliable EEG recording system according to an embodiment of the present invention;

[0051] Figure 11 Schematic diagram of a device for monitoring and reliably recording EEG signals during CES treatment in an embodiment of the present invention. DETAILED DESCRIPTION

[0052] It should be noted that:

[0053] The terms "including" and "having" and any variations thereof in the description and claims of the present invention and the above-mentioned drawings are intended to cover non-exclusive inclusions, for example, a process, method, system, product or apparatus that includes a series of steps or units is not necessarily limited to the steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products or apparatuses.

[0054] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices. The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily need to be executed in the order described. For example, some operations / steps may be further decomposed, while others may be combined or partially combined, so the actual execution order may vary depending on the actual situation.

[0055] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. In addition, the technical features in the various embodiments or single embodiments provided by the present invention are arbitrarily combined with each other to form a new technical solution. This combination is not restricted by the sequence of steps and / or structural composition mode, but must be based on the ability of ordinary technicians in this field to implement it. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that this combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0056] According to one aspect of the present invention, a method for monitoring and reliably recording EEG signals during CES treatment is provided, which is characterized by comprising:

[0057] Collect CES treatment EEG signal data and segment it into EEG signal data before, during, and after stimulation according to the start and end time of microcurrent stimulation. Then proofread all segmented EEG signal data.

[0058] Select the corrected EEG signal data during stimulation, segment it by time, and extract the stable EEG signal based on data signal analysis;

[0059] Based on filtering to screen reliable EEG signals from stable EEG signals and perform data enhancement;

[0060] Based on the time alignment and integration of the enhanced reliable EEG signal and the corrected EEG signal data before and after stimulation, a complete reliable EEG signal change curve is obtained;

[0061] Based on feature analysis and processing, a complete and reliable EEG signal change curve is obtained to obtain the visual monitoring results of the target EEG activity.

[0062] Furthermore, the steps of checking the EEG signal data include:

[0063] Save EEG signal data and perform preprocessing;

[0064] The channels and time periods containing significant artifacts in the preprocessed EEG signal data are marked and removed to obtain the corrected EEG signal data.

[0065] Furthermore, the steps of extracting stable EEG signals include:

[0066] The length of the time window and the sliding step size are preset to divide the corrected EEG signal data during stimulation into several short time period signals, wherein the sliding step size of the time window is smaller than the length of the time window;

[0067] Calculate the comprehensive stability index of each short-time period signal, preset the threshold of the comprehensive stability index, filter the short-time period signals based on the threshold, and use the filtered results as stable EEG signals.

[0068] Furthermore, the comprehensive stability index is the weighted result of the local mean and local variance of the signal in a short time period.

[0069] Furthermore, the steps of filtering and screening reliable EEG signals from stable EEG signals include:

[0070] Band-pass filtering is performed on stable EEG signals based on the EEG frequency band, retaining stable EEG signals within the frequency band;

[0071] Use wavelet decomposition to decompose the stable EEG signal after bandpass filtering into multiple frequency bands, screen the frequency bands related to the target EEG activity, and reconstruct the stable EEG signal based on the screened frequency bands to obtain a reliable EEG signal;

[0072] An adaptive filter is used to remove residual noise from the reconstructed EEG signal to obtain an enhanced and reliable EEG signal.

[0073] Furthermore, the integration process of a complete and reliable EEG signal change curve includes:

[0074] The enhanced reliable EEG signals are arranged in time sequence and time-aligned to obtain a continuous EEG signal time series as the EEG signal curve during stimulation;

[0075] The EEG signals before, during and after stimulation are integrated along the time axis to generate a complete and reliable EEG signal change curve.

[0076] Furthermore, the steps for obtaining the visual monitoring results are as follows:

[0077] Characteristic parameters are set according to the target EEG activity, and complete and reliable characteristic parameters of the EEG signal change curve are extracted and visualized to obtain the visual monitoring results of the characteristic parameters during the CES process.

[0078] like Figure 2 As shown, a CES treatment EEG signal monitoring device and a reliable EEG recording method include the following steps:

[0079] Step 1: CES treatment EEG data collection and segmentation;

[0080] In this embodiment, the specific implementation of step 1 includes the following sub-steps:

[0081] Step 1.1: Use EEG data acquisition equipment that meets international standards to collect EEG data in EDF format. Simultaneously record the timestamps and parameters (such as intensity, frequency, and duration) of the microcurrent stimulation signal for subsequent alignment and analysis. The EEG acquisition time ranges from 20 to 60 minutes.

[0082] Step 1.2: Use the EDF file reading tool to perform preliminary data preprocessing, including but not limited to detrending and filtering (0.5 Hz-50 Hz bandpass filtering);

[0083] Step 1.3: Segment the data based on the waveform or by setting labels, so that the data is divided into three segments: pre-stimulus data, stimulation data, and post-stimulus data. The segmented data facilitates subsequent separate processing and analysis of EEG signals at different stages; see Figure 3 、 Figure 4 , Figure 3Figure 2 is a schematic diagram of data segmentation by setting markers in an embodiment of the present invention, where ECS_Start and CES_End respectively mark the start time (17 minutes 58.433 seconds) and end time (38 minutes 10.707 seconds) of micro-electrical stimulation, and these two markers separate the data into three segments. Figure 4 This is a schematic diagram of data segmentation through waveform detection and judgment in an embodiment of the present invention. It can be clearly observed or detected that the amplitude of the EEG data during micro-electrical stimulation is much larger than the amplitude during resting EEG measurement. Therefore, the data can be easily divided into three segments: before, during, and after stimulation based on the waveform and amplitude.

[0084] Step 1.4: Data quality check: Check the signal quality of each channel in the EDF file, mark and remove channels or time periods containing significant artifacts, and obtain the EEG signal data after preliminary processing and proofreading.

[0085] Step 2: Based on data signal analysis, extract the signal of the stable part;

[0086] In this embodiment, the specific implementation of step 2 includes the following sub-steps:

[0087] Step 2.1: Use the sliding window technique to segment the entire EEG signal by time. The entire EEG signal is segmented by time, and a sliding window with a window length of 0.5 seconds and a sliding step of 0.25 seconds is used to divide the long signal into short time periods, which is convenient for analyzing the signal stability in each time period; see Figure 5 , Figure 5 This figure is a schematic diagram of segmenting a long signal using a sliding window method for stability testing in an embodiment of the present invention. The red box at the bottom indicates the start time, end time, and duration of each small segment of data.

[0088] Step 2.2: Determine whether it is a usable stable signal by detecting the statistical characteristics of the signal. First, calculate the stability index of the signal in each time period, including the local mean and local variance, and weight the local mean and local variance to form a comprehensive quantitative index. , the calculation formula is: , where and denote the local mean and local variance respectively, and is the corresponding weight.

[0089] Step 2.3: Use comprehensive quantitative indicators to filter out signal segments with higher stability, smaller variance, and smaller mean changes, i.e. ,in is the threshold of the comprehensive quantitative index, and the stable EEG signal after stability detection screening is as follows Figure 6 As shown;

[0090] Step 3: Processing and enhancing of stable EEG signals;

[0091] In this embodiment, the specific implementation of step 3 includes the following sub-steps:

[0092] Step 3.1: Bandpass filter the extracted stable EEG signal (0.5-50 Hz) to remove low-frequency drift and high-frequency noise, retaining the frequency band related to EEG activity;

[0093] Step 3.2: Use wavelet decomposition to decompose the signal into multiple frequency bands. Select the frequency bands related to the target EEG activity (such as alpha waves and beta waves) for reconstruction to enhance the useful signal.

[0094] Step 3.3: Use an adaptive filter to remove residual noise and further improve signal quality;

[0095] Step 4: Arrange the EEG signals in time series, perform feature analysis on the EEG data and provide feedback.

[0096] In this embodiment, the specific implementation of step 4 includes the following sub-steps:

[0097] Step 4.1: Time-align multiple processed data segments during the stimulation process and arrange them in chronological order to form a continuous EEG signal time series; see Figure 7 , Figure 7 is a schematic diagram of arranging stable signals during multiple relative stimulation processes in a time series according to an embodiment of the present invention;

[0098] Step 4.2: Integrate the EEG signals before, during, and after stimulation along the time axis to generate a complete EEG signal change curve;

[0099] Step 4.3: Perform time-frequency analysis and power spectrum density analysis on the arranged full-process EEG signals to extract characteristic parameters;

[0100] Step 4.4: Use visualization tools (such as spectrograms and time-frequency graphs) to display the dynamic changes of EEG signals during stimulation, revealing the real-time and overall effects of stimulation. Figure 8 、 Figure 9 Since the difference between the front, middle and back parts of the connected EEG signal is not significant, the EEG signal characteristics are directly used as the display. Figure 8 This is the alpha wave data analysis result after the signals before, during and after stimulation are merged in the embodiment of the present invention; Figure 9 This is the beta wave data analysis result after the signals before, during and after stimulation are merged in the embodiment of the present invention.

[0101] The implementation basis of each embodiment of the present invention is achieved through programmed processing by a system with processor functionality. Therefore, in practical engineering, the technical solutions and functions of each embodiment of the present invention are encapsulated into various modules. Based on this reality, on the basis of the above-mentioned embodiments, an embodiment of the present invention provides a CES treatment EEG signal monitoring and reliable EEG recording system, which is used to implement the CES treatment EEG signal monitoring and reliable EEG recording method described in the above-mentioned method embodiment.

[0102] See also Figure 10 , the system comprises:

[0103] EEG data acquisition module, CES treatment EEG data acquisition and segmentation;

[0104] The stable EEG signal extraction module divides the corrected EEG signal data during stimulation into time segments and extracts stable EEG signals based on data signal analysis and data enhancement;

[0105] Reliable EEG signal screening module, screening reliable EEG signals from stable EEG signals and performing data enhancement;

[0106] EEG signal curve integration module, used to integrate complete and reliable EEG signal change curves;

[0107] Visual monitoring module, feature analysis obtains visual monitoring results of target EEG activity.

[0108] It should be noted that the system embodiments provided by the present invention are not only used to implement the methods in the above-mentioned method embodiments, but also used to implement the methods in other method embodiments provided by the present invention. The only difference lies in the setting of corresponding functional modules, and its principles are basically the same as the principles of the above-mentioned system embodiments provided by the present invention. As long as those skilled in the art refer to the specific technical solutions in other method embodiments on the basis of the above-mentioned system embodiments, obtain corresponding technical means and technical solutions composed of these technical means by combining technical features, and on the premise of ensuring the practicality of the technical solutions, they will improve the system in the above-mentioned system embodiments to obtain corresponding system class embodiments for implementing the methods in other method class embodiments.

[0109] Based on the contents of the above system embodiment, as a preferred embodiment, the CES treatment EEG signal monitoring and reliable EEG recording system provided in the embodiment of the present invention further includes:

[0110] Furthermore, the steps for screening reliable EEG signals are as follows:

[0111] Band-pass filtering is performed on stable EEG signals based on the EEG frequency band, retaining stable EEG signals within the frequency band;

[0112] Wavelet decomposition is used to decompose the stable EEG signal after bandpass filtering into multiple frequency bands, and the frequency bands related to the target EEG activity are screened. The stable EEG signal based on the screened frequency bands is reconstructed to obtain a reliable EEG signal.

[0113] The method of the embodiment of the present invention is implemented by electronic devices, so it is necessary to introduce the relevant electronic devices. Based on this purpose, the embodiment of the present invention provides a CES treatment EEG signal monitoring and reliable EEG recording device, such as Figure 11 As shown, the device includes:

[0114] CES brain electrical stimulation therapy device, used for CES treatment;

[0115] The CES treatment EEG signal detection device is used to collect CES treatment EEG signals and provide visual monitoring results of target EEG activities.

[0116] The CES treatment EEG signal monitoring device of the present invention can detect part of the EEG signals in real time during the micro-current stimulation process. The signal is not affected by the micro-electric stimulation, thereby realizing continuous recording and analysis of high-quality EEG signals.

[0117] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring and reliably recording EEG signals during CES treatment, characterized in that: include: Collect CES treatment EEG signal data and segment it into EEG signal data before, during and after stimulation according to the start and end time of microcurrent stimulation. Then proofread the segmented EEG signal data. Select the corrected EEG signal data during stimulation, segment it by time, and extract the stable EEG signal based on data signal analysis; Based on filtering to screen reliable EEG signals from stable EEG signals and perform data enhancement; Based on the time alignment and integration of enhanced reliable EEG signals and the corrected EEG signal data before and after stimulation, a complete and reliable EEG signal change curve is obtained; Based on feature analysis and processing, a complete and reliable EEG signal change curve is obtained to obtain the visual monitoring results of the target EEG activity.

2. The method for monitoring and reliably recording EEG signals during CES treatment according to claim 1, wherein: The step of checking the EEG signal data includes: Save EEG signal data and perform preprocessing; The channels and time periods containing significant artifacts in the preprocessed EEG signal data are marked and removed to obtain the corrected EEG signal data.

3. The method for monitoring and reliably recording EEG signals during CES therapy according to claim 2, wherein: The step of extracting the stable EEG signal includes: The length of the time window and the sliding step size are preset to divide the corrected EEG signal data during stimulation into several short time period signals, wherein the sliding step size of the time window is smaller than the length of the time window; Calculate the comprehensive stability index of each short-time period signal, preset the threshold of the comprehensive stability index, filter the short-time period signals based on the threshold, and use the filtered results as stable EEG signals.

4. The method for monitoring and reliably recording EEG signals during CES treatment according to claim 3, wherein: The comprehensive stability index is a weighted result of the local mean and local variance of the signal in a short time period.

5. The method for monitoring and reliably recording EEG signals during CES therapy according to claim 4, wherein: The step of filtering and screening reliable EEG signals in stable EEG signals comprises: Band-pass filtering is performed on stable EEG signals based on the EEG frequency band, retaining stable EEG signals within the frequency band; Wavelet decomposition is used to decompose the stable EEG signal after bandpass filtering into multiple frequency bands, and the frequency bands related to the target EEG activity are screened. The stable EEG signal based on the screened frequency bands is reconstructed to obtain a reliable EEG signal.

6. The method for monitoring and reliably recording EEG signals during CES therapy according to claim 1, wherein: The integration process of the complete and reliable EEG signal change curve includes: The enhanced reliable EEG signals are arranged in time sequence and time-aligned to obtain a continuous EEG signal time series as the EEG signal curve during stimulation; The EEG signals before, during and after stimulation are integrated along the time axis to generate a complete and reliable EEG signal change curve.

7. The method for monitoring and reliably recording EEG signals during CES therapy according to claim 1, wherein: The steps for obtaining the visual monitoring results are: Characteristic parameters are set according to the target EEG activity, and the characteristic parameters in the complete and reliable EEG signal change curve are extracted and visualized to obtain the visual monitoring results of the characteristic parameters during the CES process.

8. CES treatment EEG signal monitoring and reliable EEG recording system, characterized by: include: EEG data acquisition module, CES treatment EEG data acquisition and segmentation; The stable EEG signal extraction module divides the corrected EEG signal data during stimulation into time segments and extracts stable EEG signals based on data signal analysis and data enhancement; Reliable EEG signal screening module, screening reliable EEG signals from stable EEG signals and performing data enhancement; EEG signal curve integration module, used to integrate complete and reliable EEG signal change curves; Visual monitoring module, feature analysis obtains visual monitoring results of target EEG activity.

9. The CES treatment EEG signal monitoring and reliable EEG recording system according to claim 8, characterized in that: The steps of screening the reliable EEG signals are as follows: Band-pass filtering is performed on stable EEG signals based on the EEG frequency band, retaining stable EEG signals within the frequency band; Wavelet decomposition is used to decompose the stable EEG signal after bandpass filtering into multiple frequency bands, and the frequency bands related to the target EEG activity are screened. The stable EEG signal based on the screened frequency bands is reconstructed to obtain a reliable EEG signal.

10. A device for monitoring and reliably recording EEG signals during CES treatment, for implementing the method for monitoring and reliably recording EEG signals during CES treatment according to any one of claims 1 to 7, characterized in that: include: CES brain electrical stimulation therapy device, used for CES treatment; The CES treatment EEG signal detection device is used to collect CES treatment EEG signals and provide visual monitoring results of target EEG activities.

Images