A method and device for visualizing electroencephalogram signals

Abstract

The present invention provides an EEG signal visualization method and device, which solves the problem that the existing technology cannot observe and analyze the EEG signal data collected in real time. First, the patient's CT image data and magnetic resonance image data are obtained, and then the patient's brain area image and the electrode distribution position of the patient's brain are constructed; then, the patient's EEG signal data is obtained in real time and calculated to generate data for reflecting the active state of the patient's brain area; finally, the data for reflecting the active state of the patient's brain area is used to display the state of the brain area in real time through the brain area image. Through the above steps, real-time observation and analysis and processing of the patient's brain signals are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of electroencephalogram (EEG) signal processing, and in particular to an EEG signal visualization method and device. Background Art

[0002] With the rapid development of neuroscience and information technology, the study of electroencephalogram (EEG) has become one of the important means to explore brain function. EEG records the weak current changes generated by the cerebral cortex through electrodes placed on the scalp. These changes can reflect the state of brain activity. However, the original EEG data is usually presented in the form of a time series, which is difficult for non-professionals to understand intuitively. Therefore, the development of effective EEG signal visualization methods and devices has become a research focus, aiming to convert complex EEG data into easy-to-understand images or animations to help researchers, doctors and patients better analyze and interpret brain activity patterns.

[0003] However, in the prior art, relevant staff effectively observes, analyzes and processes the EEG signal data collected in real time. Summary of the invention

[0004] The present invention provides an electroencephalogram (EEG) signal visualization method and device to solve the problem that the prior art cannot observe and analyze the EEG signal data collected in real time.

[0005] In a first aspect, the present invention provides a method for visualizing an electroencephalogram signal, which specifically comprises the following steps:

[0006] Step S1, acquiring brain CT image data DATA1 and corresponding magnetic resonance image data DATA2;

[0007] Step S2, processing the data DATA1 and DATA2, and drawing and displaying an electrode point map, a brain region map and a cerebral cortex map according to the processing results of the data DATA1 and DATA2;

[0008] Step S3, obtaining EEG signal data of any two frequency bands F1 and F2, performing standardization processing, and forming data DATA3;

[0009] Step S4: display the brain region information and electrode information in real time according to the data DATA3 until the real-time display of all brain region information and electrode information is completed.

[0010] In this application, the “correspondence” means that, for patient A, the CT image data of his brain is DATA1, and the magnetic resonance image data of his brain is DATA2.

[0011] Preferably, in step S1, the data DATA2 is a T1-weighted magnetic resonance image.

[0012] Preferably, in step S2, the data DATA1 and DATA2 are processed, and according to the processing results of the data DATA1 and DATA2, an electrode point map, a brain region map and a cerebral cortex map are drawn and displayed, which specifically includes the following steps:

[0013] Step S201, three-dimensionally reconstructing the data DATA2 through FreeSurfer software to form a registration matrix, mesh files lh.pial (left brain mesh file) and rh.pial (right brain mesh file), and obtaining vertex coordinates and triangulation according to the mesh files, and drawing and displaying a cerebral cortex map through the vertex coordinates and the triangulation;

[0014] Step S202, marking the electrode sites of the data DATA1 by VERA software to form an electrode coordinate file, and drawing and displaying an electrode point map by using the electrode coordinate file;

[0015] Step S203, performing brain region calibration processing on the data DATA2 through FreeSurfer software to form a brain region division file, and drawing and displaying a brain region map through the brain region division file;

[0016] Step S204: displaying the cerebral cortex map, the electrode point map and the brain region map in the same coordinate system according to the registration matrix.

[0017] Preferably, in step S3, the EEG signal data of any two frequency bands F1 and F2 are obtained and standardized to form data DATA3, which specifically includes the following steps:

[0018] Step S301: Obtain EEG signal data of any two frequency bands F1 and F2, and generate corresponding complex domain signal data through Hilbert transform. and data ;

[0019] Step S302: and the data Coupled processing to form data , and calculate the data The mean ;

[0020] Step S303: At a random point in time Split the signal into two segments, and swap the order of the signal to form data ;

[0021] Step S304: and the data Perform coupling processing to form coupled EEG signals , repeatedly generate N times of random coupled EEG signals , and calculate the coupled EEG signal The mean and variance ;

[0022] Step S305: according to the mean , and the variance , forming data DATA3.

[0023] Preferably, in step S301, the EEG signal data of any two frequency bands F1 and F2 are transformed by Hilbert transform to form corresponding complex domain signal data and data , the specific calculation formula is as follows:

[0024]

[0025]

[0026] Wherein, t represents time; Indicates the amplitude of the signal in the F1 frequency band; Indicates the amplitude of the signal in the F2 frequency band; Indicates the phase of the signal in the F1 frequency band; Indicates the phase of the signal in the F2 frequency band.

[0027] Preferably, in step S302, the data and the data Coupled processing to form data and its mean , the specific calculation formula is as follows:

[0028]

[0029]

[0030] in, Representation data The mean of .

[0031] Preferably, in step S303, At a random point in time Split the signal into two segments, and swap the order of the signal to form data , specifically expressed as follows:

[0032]

[0033]

[0034] in, Represents a randomly selected time division point.

[0035] Preferably, in step S304, the data and the data Perform coupling processing to form coupled EEG signals , repeatedly generate N times of random coupled EEG signals , and calculate the coupled EEG signal The mean and variance , specifically expressed as follows:

[0036]

[0037]

[0038]

[0039] Wherein, N is a positive integer.

[0040] Preferably, in step S305, according to the mean , and the variance , forming data DATA3, which is specifically represented as follows:

[0041]

[0042] The data DATA3 is also called a standardized modulation coefficient, and the size of the data DATA3 reflects the activity state of the brain.

[0043] Preferably, in step S4, the displayed brain region information and electrode information include brain regions, electrode points under the brain regions, single electrode points, whether electrode points and brain regions are displayed, the colors of the brain regions and electrode points, and displayed graphic logos; at the same time, since the display processing time of the brain region information and electrode information is less than the time for collecting and processing the EEG signal data, the EEG signal data can be displayed in real time.

[0044] In a second aspect, the present invention further provides an electroencephalogram signal visualization device, which specifically includes the following modules:

[0045] An image data acquisition module, used to acquire CT image data DATA1 and corresponding magnetic resonance image data DATA2 of the brain;

[0046] A graphics drawing and display module, used for processing the data DATA1 and DATA2, and drawing and displaying an electrode point map, a brain region map and a cerebral cortex map according to the processing results of the data DATA1 and DATA2;

[0047] A data standardization processing module is used to obtain the EEG signal data of any two frequency bands F1 and F2, perform standardization processing, and form data DATA3;

[0048] The EEG signal real-time display module is used to display the brain region information and electrode information in real time according to the data DATA3 until the real-time display of all brain region information and electrode information is completed.

[0049] Preferably, in the image data acquisition module, the data DATA2 is a T1-weighted magnetic resonance image.

[0050] Preferably, the graphics drawing and display module specifically includes the following submodules:

[0051] The first image processing submodule is used to perform three-dimensional reconstruction on the data DATA2 through FreeSurfer software to form a registration matrix, grid files lh.pial (left brain grid file) and rh.pial (right brain grid file), and obtain vertex coordinates and triangulation according to the grid files, and draw and display a cerebral cortex map through the vertex coordinates and the triangulation;

[0052] The second image processing submodule is used to mark the electrode sites of the data DATA1 through VERA software to form an electrode coordinate file, and draw and display an electrode point map through the electrode coordinate file;

[0053] The third image processing submodule is used to perform brain region calibration processing on the data DATA2 through FreeSurfer software to form a brain region division file, and draw and display a brain region map through the brain region division file;

[0054] The fourth image processing submodule is used to display the cerebral cortex map, the electrode point map and the brain area map in the same coordinate system according to the registration matrix.

[0055] Preferably, in the fourth image processing submodule, an electrode point map is drawn using the data DATA1, the data DATA2 and the coordinate data of the electrodes; and a brain region map is drawn using the grid file and the conversion matrix.

[0056] Preferably, the data standardization processing module specifically includes the following submodules:

[0057] The first data processing submodule is used to obtain the EEG signal data of any two frequency bands F1 and F2, and form the corresponding complex domain signal data through Hilbert transform and data ;

[0058] The second data processing submodule is used to convert the data and the data Coupled processing to form data , and calculate the data The mean ;

[0059] The third data processing submodule is used to At a random point in time Split the signal into two segments, and swap the order of the signal to form data ;

[0060] The fourth data processing submodule is used to convert the data and the data Perform coupling processing to form coupled EEG signals , repeatedly generate N times of random coupled EEG signals , and calculate the coupled EEG signal The mean and variance ;

[0061] The fifth data processing submodule is used to process the data according to the mean value. , and the variance , forming data DATA3.

[0062] Preferably, in the first data processing submodule, the EEG signal data of any two frequency bands F1 and F2 are transformed by Hilbert transform to form corresponding complex domain signal data and data , the specific calculation formula is as follows:

[0063]

[0064]

[0065] Wherein, t represents time; Indicates the amplitude of the signal in the F1 frequency band; Indicates the amplitude of the signal in the F2 frequency band; Indicates the phase of the signal in the F1 frequency band; Indicates the phase of the signal in the F2 frequency band.

[0066] Preferably, in the second data processing submodule, the data and the data Coupled processing to form data and its mean , the specific calculation formula is as follows:

[0067]

[0068]

[0069] in, Representation data The mean of .

[0070] Preferably, in the third data processing submodule, At a random point in time Split the signal into two segments, and swap the order of the signal to form data , specifically expressed as follows:

[0071]

[0072]

[0073] in, Represents a randomly selected time division point.

[0074] Preferably, in the fourth data processing submodule, the data and the data Perform coupling processing to form coupled EEG signals , repeatedly generate N times of random coupled EEG signals , and calculate the coupled EEG signal The mean and variance , specifically expressed as follows:

[0075]

[0076]

[0077]

[0078] Wherein, N is a positive integer.

[0079] Preferably, in the fifth data processing submodule, according to the mean , and the variance , forming data DATA3, which is specifically represented as follows:

[0080]

[0081] The data DATA3 is also called a standardized modulation coefficient, and the size of the data DATA3 reflects the activity state of the brain.

[0082] Preferably, in the EEG signal real-time display module, the displayed brain area information and electrode information include brain areas, electrode points under the brain areas, single electrode points, whether the electrode points and brain areas are displayed, the colors of the brain areas and electrode points, and displayed graphic logos; at the same time, since the display processing time of the brain area information and electrode information is less than the time for collecting and processing the EEG signal data, the EEG signal data can be displayed in real time.

[0083] In a third aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements an EEG signal visualization method as described in any one of the first aspects of the present application.

[0084] In a fourth aspect, the present invention further provides an electronic device, comprising: a memory storing a computer program; and a processor communicatively connected to the memory, for executing an EEG signal visualization method described in any one of the first aspects of the present application when the computer program is called.

[0085] Compared with the prior art, the present invention has the following obvious outstanding substantive features and significant advantages:

[0086] The present invention provides an EEG signal visualization method and device, which solves the problem that the existing technology cannot observe and analyze the EEG signal data collected in real time. First, the patient's CT image data and magnetic resonance image data are obtained, and then the patient's brain area image and the electrode distribution position of the patient's brain are constructed; then, the patient's EEG signal data is obtained in real time and calculated to generate data for reflecting the active state of the patient's brain area; finally, the data for reflecting the active state of the patient's brain area is used to display the state of the brain area in real time through the brain area image. Through the above steps, real-time observation and analysis and processing of the patient's brain signals are realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] The accompanying drawings, which constitute part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention. In the accompanying drawings:

[0088] Figure 1 This is a flow chart of a method for visualizing an electroencephalogram signal according to a preferred embodiment of the present invention.

[0089] Figure 2 It is a schematic diagram of brain and electrode distribution in a method for visualizing EEG signals according to a preferred embodiment of the present invention.

[0090] Figure 3 It is a schematic diagram of brain area activity and electrode distribution in an EEG signal visualization method in a preferred embodiment of the present invention.

[0091] Figure 4 This is another schematic diagram of brain area activity and electrode distribution in an EEG signal visualization method in a preferred embodiment of the present invention.

[0092] Figure 5 This is another schematic diagram of brain area activity and electrode distribution in an EEG signal visualization method in a preferred embodiment of the present invention.

[0093] Figure 6 It is a schematic diagram of the structure of an electroencephalogram signal visualization device according to a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0094] The present invention provides an EEG signal visualization method and device. To make the purpose, technical solution and effect of the present invention clearer and more specific, the present invention is further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0095] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0096] Embodiment 1:

[0097] like Figure 1-Figure 5 As shown, the EEG signal visualization method described in this embodiment specifically includes the following steps:

[0098] Step S1, obtaining brain CT image data DATA1 and corresponding magnetic resonance image data DATA2; in this embodiment, the data DATA2 is a T1-weighted magnetic resonance image, and the T1-weighted image can indeed better reflect the anatomical characteristics of brain tissue.

[0099] Step S2, processing the data DATA1 and DATA2, and drawing and displaying an electrode point map, a brain region map and a cerebral cortex map according to the processing results of the data DATA1 and DATA2.

[0100] Optionally, step S2 specifically includes the following steps:

[0101] Step S201, three-dimensionally reconstruct the data DATA2 through FreeSurfer software to form a registration matrix, mesh files lh.pial (left brain mesh file) and rh.pial (right brain mesh file), and obtain vertex coordinates and triangulation according to the mesh files, and draw and display the cerebral cortex map through the vertex coordinates and the triangulation.

[0102] Step S202: annotate the electrode sites of the data DATA1 through VERA software to form an electrode coordinate file, and draw and display an electrode point map through the electrode coordinate file.

[0103] Step S203: The data DATA2 is processed by FreeSurfer software to perform brain region calibration to form a brain region division file, and a brain region map is drawn and displayed using the brain region division file.

[0104] Step S204: displaying the cerebral cortex map, the electrode point map and the brain region map in the same coordinate system according to the registration matrix.

[0105] Step S3, obtaining EEG signal data of any two frequency bands F1 and F2, performing standardization processing, and forming data DATA3;

[0106] Optionally, step S3 specifically includes the following steps:

[0107] Step S301: Obtain EEG signal data of any two frequency bands F1 and F2, and generate corresponding complex domain signal data through Hilbert transform. and data , the specific calculation formula is as follows:

[0108]

[0109]

[0110] Wherein, t represents time; Indicates the amplitude of the signal in the F1 frequency band; Indicates the amplitude of the signal in the F2 frequency band; Indicates the phase of the signal in the F1 frequency band; Indicates the phase of the signal in the F2 frequency band.

[0111] Step S302: and the data Coupled processing to form data , and calculate the data The mean , the specific calculation formula is as follows:

[0112]

[0113]

[0114] in, Representation data The mean of .

[0115] Step S303: At a random point in time Split the signal into two segments, and swap the order of the signal to form data , specifically expressed as follows:

[0116]

[0117]

[0118] in, Represents a randomly selected time division point.

[0119] Step S304: and the data Perform coupling processing to form coupled EEG signals , repeatedly generate N times of random coupled EEG signals , and calculate the coupled EEG signal The mean and variance , specifically expressed as follows:

[0120]

[0121]

[0122]

[0123] Wherein, N is a positive integer.

[0124] Step S305: according to the mean , and the variance , forming data DATA3, which is specifically represented as follows:

[0125]

[0126] The data DATA3 is also called a standardized modulation coefficient, and the size of the data DATA3 reflects the activity state of the brain.

[0127] Step S4, according to the data DATA3, the brain region information and the electrode information are displayed in real time until the real-time display of all the brain region information and the electrode information is completed; wherein the displayed brain region information and the electrode information include the brain region, the electrode points under the brain region, the single electrode point, whether the electrode point and the brain region are displayed, the color of the brain region and the electrode point, and the displayed graphic identification; at the same time, since the display processing time of the brain region information and the electrode information is less than the time of collecting and processing the EEG signal data, the EEG signal data can be displayed in real time.

[0128] like Figure 2 As shown in the figure, the gray-white part represents the brain area, and the red part represents the location of the brain electrode. Figure 3-Figure 5 As shown in the figure, the gray-white brain area contains several light green, blue, purple and yellow areas, each of which represents a different brain tissue area. The size of the red part indicates the level of activity of each brain tissue, and the location of the red part indicates that the activity is concentrated in a single brain tissue.

[0129] Figure 3-Figure 5 The graph shown can be presented in three forms:

[0130] (1) If Figure 3 As shown in the figure, each brain area corresponds to a color. The table shown in the right figure lists 5 brain areas, which correspond to the 5 color brain areas in the visualization. Among them, the higher the pac value (that is, the value of DATA3, also known as the standardized modulation coefficient), the higher the activity of the electrode point at this moment. In the visualization, it is represented by the size of the sphere. The larger the sphere, the higher the activity. Figure 3 Note: The largest electrode point sphere circled in yellow corresponds to the highest point below the brain area circled in yellow in the diagram on the right.

[0131] (2) If Figure 4 As shown, the higher the average PAC value, the larger the average radius of the sphere in the brain area, the higher the activity. The blue marked circle indicates that the average PAC value of this brain area is the highest among all brain areas.

[0132] (3) If Figure 5 As shown, it reflects the activity of each electrode point in this brain area. The higher the value, the larger the radius of the electrode point sphere and the higher the activity. The purple marked circle indicates that the electrode point has the highest activity in this brain area.

[0133] Embodiment 2:

[0134] like Figure 6 As shown, the electroencephalogram signal visualization device described in this embodiment specifically includes the following modules:

[0135] The image data acquisition module is used to acquire CT image data DATA1 and corresponding magnetic resonance image data DATA2 of the brain; wherein the data DATA2 is a T1-weighted magnetic resonance image.

[0136] A graphics drawing and display module, used for drawing and displaying an electrode point diagram and a brain area diagram according to the data DATA1 and the data DATA2;

[0137] Optionally, the graphics drawing and display module specifically includes the following submodules:

[0138] The first image processing submodule is used to perform three-dimensional reconstruction of the data DATA2 through FreeSurfer software to form a registration matrix, grid files lh.pial (left brain grid file) and rh.pial (right brain grid file), and obtain vertex coordinates and triangulation according to the grid files, and draw and display the cerebral cortex map through the vertex coordinates and the triangulation.

[0139] The second image processing submodule is used to mark the electrode sites of the data DATA1 through VERA software to form an electrode coordinate file, and to draw and display an electrode point map through the electrode coordinate file.

[0140] The third image processing submodule is used to perform brain region calibration processing on the data DATA2 through FreeSurfer software to form a brain region division file, and draw and display a brain region map through the brain region division file.

[0141] The fourth image processing submodule is used to display the cerebral cortex map, the electrode point map and the brain area map in the same coordinate system according to the registration matrix.

[0142] The data standardization processing module is used to obtain the EEG signal data of any two frequency bands F1 and F2, perform standardization processing, and form data DATA3.

[0143] Optionally, the data standardization processing module specifically includes the following submodules:

[0144] The first data processing submodule is used to obtain the EEG signal data of any two frequency bands F1 and F2, and form the corresponding complex domain signal data through Hilbert transform and data , the specific calculation formula is as follows:

[0145]

[0146]

[0147] Wherein, t represents time; Indicates the amplitude of the signal in the F1 frequency band; Indicates the amplitude of the signal in the F2 frequency band; Indicates the phase of the signal in the F1 frequency band; Indicates the phase of the signal in the F2 frequency band.

[0148] The second data processing submodule is used to convert the data and the data Coupled processing to form data and its mean , the specific calculation formula is as follows:

[0149]

[0150]

[0151] in, Representation data The mean of .

[0152] The third data processing submodule is used to At a random point in time Split the signal into two segments, and swap the order of the signal to form data , specifically expressed as follows:

[0153]

[0154]

[0155] in, Represents a randomly selected time division point.

[0156] The fourth data processing submodule is used to convert the data and the data Perform coupling processing to form coupled EEG signals , repeatedly generate N times of random coupled EEG signals , and calculate the coupled EEG signal The mean and variance , specifically expressed as follows:

[0157]

[0158]

[0159]

[0160] Wherein, N is a positive integer.

[0161] The fifth data processing submodule is used to process the data according to the mean value. , and the variance , forming data DATA3, which is specifically represented as follows:

[0162]

[0163] The data DATA3 is also called a standardized modulation coefficient, and the size of the data DATA3 reflects the activity state of the brain.

[0164] The EEG signal real-time display module is used to display the brain region information and electrode information in real time according to the data DATA3 until the real-time display of all brain region information and electrode information is completed; wherein the displayed brain region information and electrode information include brain region, electrode points under the brain region, single electrode point, whether the electrode point and brain region are displayed, the color of the brain region and electrode point, and the displayed graphic identification; at the same time, since the display processing time of the brain region information and electrode information is less than the time of EEG signal data acquisition and processing, the EEG signal data can be displayed in real time.

[0165] The specific embodiments of the present invention are described in detail above, but they are only examples, and the present invention is not limited to the specific embodiments described above. For those skilled in the art, any equivalent modifications and substitutions made to the present invention are also within the scope of the present invention. Therefore, the equalization changes and modifications made without departing from the spirit and scope of the present invention should be included in the scope of the present invention.

Claims

1. A method for visualizing an electroencephalogram signal, characterized in that: The specific steps include: Step S1, acquiring brain CT image data DATA1 and corresponding magnetic resonance image data DATA2; Step S2, processing the data DATA1 and DATA2, and drawing and displaying an electrode point map, a brain region map and a cerebral cortex map according to the processing results of the data DATA1 and DATA2; Step S3, obtaining EEG signal data of any two frequency bands F1 and F2, performing standardization processing, and forming data DATA3; Step S4, displaying the brain region information and the electrode information in real time according to the data DATA3, until the real-time display of all the brain region information and the electrode information is completed; In step S3, the EEG signal data of any two frequency bands F1 and F2 are obtained and standardized to form data DATA3, which specifically includes the following steps: Step S301: Obtain EEG signal data of any two frequency bands F1 and F2, and generate corresponding complex domain signal data through Hilbert transform. and data ; Step S302: and the data Coupled processing is performed to form data , and calculate the data The mean ; Step S303: At a random point in time Split to form two EEG signal sequences, swap the order of the EEG signal sequences, and form data ; Step S304: and the data Perform coupling processing to form coupled EEG signals , repeatedly generate N times of random coupled EEG signals , and calculate the coupled EEG signal The mean and variance ; Step S305: according to the mean , and the variance , forming data DATA3; Wherein, t represents time; Indicates the amplitude of the signal in the F1 frequency band; In step S4, the displayed brain region information and electrode information include the brain region, electrode points under the brain region, a single electrode point, whether the electrode point and the brain region are displayed, the color of the brain region and the electrode point, and the displayed graphic identification; at the same time, since the display processing time of the brain region information and the electrode information is less than the time for collecting and processing the EEG signal data, the EEG signal data is displayed in real time.

2. The method for visualizing an electroencephalogram signal according to claim 1, characterized in that: In step S1, the data DATA2 is a T1-weighted magnetic resonance image.

3. The method for visualizing an electroencephalogram signal according to claim 1, characterized in that: In step S2, the data DATA1 and DATA2 are processed, and according to the processing results of the data DATA1 and DATA2, an electrode point map, a brain region map and a cerebral cortex map are drawn and displayed, which specifically includes the following steps: Step S201, three-dimensionally reconstructing the data DATA2 through FreeSurfer software to form a registration matrix, grid files lh.pial and rh.pial, and obtaining vertex coordinates and triangulation according to the grid files, and drawing and displaying a cerebral cortex map through the vertex coordinates and the triangulation; Step S202, marking the electrode sites of the data DATA1 by VERA software to form an electrode coordinate file, and drawing and displaying an electrode point map by using the electrode coordinate file; Step S203, performing brain region calibration processing on the data DATA2 through FreeSurfer software to form a brain region division file, and drawing and displaying a brain region map through the brain region division file; Step S204: display the cerebral cortex map, the electrode point map and the brain region map in the same coordinate system according to the registration matrix.

4. The method for visualizing an electroencephalogram signal according to claim 3, characterized in that: In step S204, an electrode point map is drawn using the data DATA1, the data DATA2 and the coordinate data of the electrodes; and a brain region map is drawn using the grid file and the registration matrix.

5. The method for visualizing an electroencephalogram signal according to claim 1, characterized in that: In step S301, the EEG signal data of any two frequency bands F1 and F2 are transformed by Hilbert transform to form corresponding complex domain signal data and data , the specific calculation formula is as follows: ； ； Wherein, t represents time; Indicates the amplitude of the signal in the F1 frequency band; Indicates the amplitude of the signal in the F2 frequency band; Indicates the phase of the signal in the F1 frequency band; Indicates the phase of the signal in the F2 frequency band; In step S302, the data and the data Coupled processing is performed to form data and its mean , the specific calculation formula is as follows: ； ； in, Representation data The mean of In step S303, At a random point in time Split to form two EEG signal sequences, swap the order of the EEG signal sequences, and form data , specifically expressed as follows: ； ； in, represents a randomly selected time division point; In step S304, the data and the data Perform coupling processing to form coupled EEG signals , repeatedly generate N times of random coupled EEG signals , and calculate the coupled EEG signal The mean and variance , specifically expressed as follows: ； ； ； Wherein, N is a positive integer; In step S305, according to the mean , and the variance , forming data DATA3, which is specifically represented as follows: ； The data DATA3 is also called a standardized modulation coefficient, and the size of the data DATA3 reflects the activity state of the brain.

6. A device for visualizing electroencephalogram signals, characterized in that: Specifically, it includes the following modules: an image data acquisition module, which is used to acquire CT image data DATA1 and corresponding magnetic resonance image data DATA2 of the brain; A graphics drawing and display module, used for processing the data DATA1 and DATA2, and drawing and displaying an electrode point map, a brain region map and a cerebral cortex map according to the processing results of the data DATA1 and DATA2; A data standardization processing module is used to obtain the EEG signal data of any two frequency bands F1 and F2, perform standardization processing, and form data DATA3; The EEG signal real-time display module is used to display the brain region information and the electrode information in real time according to the data DATA3 until the real-time display of all the brain region information and the electrode information is completed; The data standardization processing module specifically includes the following sub-modules: The first data processing submodule is used to obtain the EEG signal data of any two frequency bands F1 and F2, and form the corresponding complex domain signal data through Hilbert transform and data ; The second data processing submodule is used to convert the data and the data Coupled processing is performed to form data , and calculate the data The mean ; The third data processing submodule is used to At a random point in time Split to form two EEG signal sequences, swap the order of the EEG signal sequences, and form data ; The fourth data processing submodule is used to convert the data and the data Perform coupling processing to form coupled EEG signals , repeatedly generate N times of random coupled EEG signals , and calculate the coupled EEG signal The mean and variance ; The fifth data processing submodule is used to process the data according to the mean value. , and the variance , forming data DATA3; Wherein, t represents time; Indicates the amplitude of the signal in the F1 frequency band; In the EEG signal real-time display module, the displayed brain area information and electrode information include brain areas, electrode points under the brain areas, single electrode points, whether the electrode points and brain areas are displayed, the colors of the brain areas and electrode points, and displayed graphic logos; at the same time, since the display processing time of the brain area information and electrode information is less than the time for EEG signal data acquisition and processing, the EEG signal data is displayed in real time.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for visualizing an electroencephalogram signal according to any one of claims 1 to 5 is implemented.

8. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, a method for visualizing an electroencephalogram signal as described in any one of claims 1 to 5 is implemented.

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