TACS artifact removal method and device based on noise-assisted analysis, equipment and medium

Abstract

The invention discloses a tACS artifact removal method, device and equipment based on noise-assisted analysis and a medium. The method comprises the steps that an electroencephalogram signal is input; adding white noise into the single-channel electroencephalogram signal; processing the electroencephalogram signal added with the white noise by adopting a power spectrum interpolation method, and correcting a power spectrum by using interpolation to obtain a single-channel electroencephalogram signal without artifacts; and taking the obtained artifact-removed single-channel electroencephalogram signal as a new input signal, returning to iteratively execute the step of adding the white noise, and obtaining a new artifact-removed single-channel electroencephalogram signal until the number of iterations reaches a preset number of times, so as to obtain a new artifact-removed single-channel electroencephalogram signal. And averaging all the obtained single-channel electroencephalogram signals from which the artifacts are removed as final single-channel electroencephalogram data from which the artifacts are removed. According to the method, the definition and the accuracy of the signal can be effectively improved by utilizing repeated noise addition and subsequent averaging processes. The method can be widely applied to the field of electroencephalogram signal processing.

Description

Technical Field

[0001] The present invention relates to the field of electroencephalogram (EEG) signal processing, and particularly to a method, device, equipment and medium for removing tACS artifacts based on noise-assisted analysis. Background Art

[0002] Electroencephalogram (EEG) is a widely used brain imaging technology that records the electrical activities of large-scale neuronal synchronizations and can reflect rich neural activities during cognitive processes. Brain rhythms are unique patterns distributed in different frequency bands in EEG and are related to various cognitive activities. Transcranial alternating current stimulation (tACS) is an important means of brain rhythm regulation. By directly delivering continuous micro-amounts of alternating current to specific cerebral cortex regions through electrodes, the neuronal populations in the target regions are then entrained to the set alternating current frequency, thereby triggering the synchronization of oscillations in specific brain regions with the input current and effectively regulating the brain rhythms in the cortical regions. Recording EEG data while performing tACS regulation can well analyze and track the changes in the brain during the brain regulation process.

[0003] Electroencephalography (EEG) is a non-invasive neuroimaging technology that measures the postsynaptic potentials generated by the electrical activities of cortical neurons through electrodes placed on the scalp. Due to its relatively simple setup, EEG has become the main neuroimaging modality for recording and understanding the effects of tACS on the brain and its underlying mechanisms. However, there are artifacts in the EEG signals caused by tACS stimulation. The amplitudes of these artifacts are much larger than the signals of interest. And due to hardware limitations and physiological interferences (such as head movement, heartbeat, etc.), this current is non-linearly converted and mixed with normal brain activities. The artifacts not only appear at the fundamental stimulation frequency but also show high power at several of its harmonics. Therefore, the tACS artifacts overlap with the normal EEG activities in the frequency domain, and it is impossible to use methods of frequency domain filtering without removing some signals of interest for denoising. Summary of the Invention

[0004] To solve at least one of the technical problems existing in the prior art to a certain extent, the object of the present invention is to provide a method, device, equipment and medium for removing tACS artifacts based on noise-assisted analysis.

[0005] The first technical solution adopted by the present invention is as follows:

[0006] A method for removing tACS artifacts based on noise-assisted analysis, comprising the following steps:

[0007] Input the EEG signal;

[0008] Add white noise to the single-channel EEG signal;

[0009] Process the EEG signal with added white noise using the power spectrum interpolation method, correct the power spectrum using interpolation, and obtain a single-channel EEG signal with artifacts removed;

[0010] Use the obtained single-channel EEG signal with artifacts removed as the new input signal, return to the step of iteratively adding white noise, and obtain a new single-channel EEG signal with artifacts removed until the number of iterations reaches the preset number. Average all the obtained single-channel EEG signals with artifacts removed as the final single-channel EEG data after artifact removal.

[0011] Further, adding white noise to the single-channel EEG signal includes:

[0012] For the single-channel EEG signal x(t), white noise n(t) will be added to obtain the EEG signal with added white noise, and the expression is:

[0013] x'(t) = x(t) + α i ·n i (t)

[0014] Where α is a scaling factor and n(t) is white noise.

[0015] Further, the intensity of the white noise is 1 - 5%.

[0016] Further, processing the EEG signal with added white noise using the power spectrum interpolation method includes:

[0017] For the EEG signal with added white noise, use FFT to transform it to the frequency domain to obtain the power spectrum F1;

[0018] Perform median filtering on the power spectrum F1 to obtain the smoothed power spectrum F2;

[0019] Subtract the power spectrum F2 from the power spectrum F1 to obtain the power spectrum difference curve F3;

[0020] Detect abnormal frequency points for all points on the power spectrum difference curve F3 to obtain spectral abnormal points;

[0021] For each abnormal point, consider the preset bandwidth on its left and right sides as the points where tACS artifacts are located and delete them from the spectrum;

[0022] Based on the frequency points of the remaining spectrum, perform cubic spline interpolation on the phase and amplitude of the deleted frequency points respectively to complete the power spectrum and obtain the complete power spectrum F4;

[0023] Perform an inverse fast Fourier transform on the power spectrum F4 to transform the signal into the time domain and obtain a single-channel EEG signal with artifacts removed.

[0024] Further, the performing abnormal frequency point detection to obtain spectrum abnormal points includes:

[0025] Determine points with spectral values exceeding 1.5 to 3 times the interquartile range above the third quartile as spectrum abnormal points.

[0026] Further, the using interpolation to correct the power spectrum includes:

[0027] For the frequency points of tACS artifacts detected through abnormal point detection, use interpolation to correct the power spectrum to eliminate the spikes at these frequency points:

[0028] P 修正 (f) = spectrum_interp(P(f), f tACS )

[0029] where f tACS is the frequency of tACS artifacts detected by abnormal point detection, P(f) is the signal after the fast Fourier transform of x'(t), and spectrum_interp means deleting the spectrum within the preset bandwidth on both the left and right sides of f tACS as the center, and then performing cubic spline interpolation on the phase and amplitude of the deleted frequency points respectively based on the frequency points of the remaining spectrum to complete the power spectrum. tACS

[0030] Further, the averaging all the obtained single-channel EEG signals with artifacts removed as the final single-channel EEG data with artifacts removed includes:

[0031] After each EEG signal x'(t) with added white noise is processed by the power spectrum interpolation method, a single-channel EEG signal y i (t) is obtained, where i represents the iteration number;

[0032] After all iterations are completed, average all y i (t)

[0033]

[0034] where N is the total number of iterations.

[0035] The second technical solution adopted by the present invention is:

[0036] A tACS artifact removal device based on noise-assisted analysis, comprising:

[0037] A signal input module for inputting an EEG signal;

[0038] A noise addition module for adding white noise to a single-channel electroencephalogram (EEG) signal;

[0039] An artifact removal module for processing the EEG signal with added white noise using a power spectrum interpolation method, correcting the power spectrum using interpolation, and obtaining a single-channel EEG signal with artifacts removed;

[0040] A signal averaging module for taking the obtained single-channel EEG signal with artifacts removed as a new input signal, returning to iteratively execute the step of adding white noise, and obtaining a new single-channel EEG signal with artifacts removed until the number of iterations reaches a preset number, and averaging all the obtained single-channel EEG signals with artifacts removed as the final single-channel EEG data with artifacts removed.

[0041] The third technical solution adopted by the present invention is:

[0042] 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 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 a tACS artifact removal method based on noise-assisted analysis as described above.

[0043] The fourth technical solution adopted by the present invention is:

[0044] A computer-readable storage medium, in which at least one instruction, at least one program, a code set or an instruction set is stored, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by a processor to implement a tACS artifact removal method based on noise-assisted analysis as described above.

[0045] The fifth technical solution adopted by the present invention is:

[0046] A computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. The processor of a computer device can read the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions to enable the computer device to execute the above method.

[0047] The beneficial effects of the present invention are: By adding white noise with a certain intensity to the EEG signal, the weak effective components in the signal are amplified, and the signal-to-noise ratio of the data is improved. Subsequently, these signals are processed using power spectrum interpolation technology to remove the artifacts generated by tACS or other interference sources. In addition, by using the repeated noise addition and subsequent averaging process, the clarity and accuracy of the signal are improved. Description of the Drawings

[0048] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following introduces the accompanying drawings of the relevant technical solutions in the embodiments of the present invention or the prior art. It should be understood that the accompanying drawings in the following introduction are only for conveniently and clearly presenting some embodiments of the technical solutions of the present invention. For those skilled in the art, without creative work, other accompanying drawings can also be obtained based on these drawings.

[0049] Figure 1 is a schematic flowchart of a tACS artifact removal method based on noise-assisted analysis in an embodiment of the present invention;

[0050] Figure 2 is a flowchart of the power spectrum interpolation method in an embodiment of the present invention;

[0051] Figure 3 is a schematic diagram of EEG data segments before and after artifact removal in an embodiment of the present invention. Detailed implementation manners

[0052] The following details the embodiments of the present invention. The examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as a limitation of the present invention. For the step numbers in the following embodiments, they are only set for the convenience of elaboration and explanation, and no limitation is imposed on the order between the steps. The execution order of each step in the embodiments can be adaptively adjusted according to the understanding of those skilled in the art.

[0053] In the description of the present invention, it should be understood that for the orientation description, such as the orientation or positional relationship indicated by up, down, front, back, left, right, etc., is based on the orientation or positional relationship shown in the accompanying drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention.

[0054] In the description of the present invention, the meaning of several is one or more, the meaning of multiple is two or more, greater than, less than, exceeding, etc. are understood as not including the original number, and above, below, within, etc. are understood as including the original number. If there is a description of first and second, it is only for the purpose of distinguishing technical features and should not be understood as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features or implicitly indicating the sequence of the indicated technical features.

[0055] In the description of the present invention, unless otherwise clearly defined, terms such as "set", "installed", "connected", etc. should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention in combination with the specific content of the technical solution.

[0056] Term Explanation:

[0057] tACS: Abbreviation for transcranial alternating current stimulation, transcranial alternating current stimulation.

[0058] EEG: Abbreviation for Electroencephalography, electroencephalogram.

[0059] NA: Abbreviation for noise assisted, noise assisted.

[0060] Ideally, the artifact of a single-frequency tACS stimulation should be manifested as a single sine wave in the electroencephalogram and as a single peak at that frequency point in the frequency spectrum. Therefore, the method of spectral interpolation can be used to remove the contamination of a small number of frequency points. However, in actual situations, affected by the properties of the electrochemical interface of the conductive medium, the change of the contact area during the stimulation process, the dynamic range of the electroencephalogram acquisition amplifier, and the frequency response characteristics, strong spectral leakage and high-order harmonics often occur, resulting in that a single simple spectral interpolation cannot well remove the tACS artifact.

[0061] During the electroencephalogram data acquisition process, affected by the acquisition site and the equipment state, the signal will contain a certain amount of noise components, including scalp contact noise, electrolyte electrochemical interface noise, electroencephalogram amplifier circuit thermal noise, etc. Such noise generally appears as white noise. Noise-assisted (noise assisted, NA) analysis simulates the noise in the actual data collection process by adding a certain amount of white noise to the data, and then performs subsequent data analysis. Through the process of adding noise and data analysis multiple times, the analysis results of multiple times are averaged to offset the influence of the added noise. NA simulates the process of multiple signal resampling, can amplify the weak effective components in the signal, and improve the signal-to-noise ratio of the data.

[0062] Based on this, the present invention provides a tACS artifact removal scheme based on noise-assisted analysis. By adding a certain intensity of white noise (1-5%) to the electroencephalogram signal, and then processing these signals through the power spectrum interpolation technology to remove the artifacts generated by tACS (transcranial alternating current stimulation) or other interference sources. Compared with the prior art, the originality of the present invention lies in the reverse thinking of improving signal processing by increasing noise, and using the repeated process of noise addition and subsequent averaging to improve the clarity and accuracy of the signal.

[0063] Example 1

[0064] As shown Figure 1 in the figure, this embodiment provides a tACS artifact removal method based on noise-assisted analysis, including the following steps:

[0065] S1. Input the electroencephalogram (EEG) signal.

[0066] S2. Add white noise to the single-channel EEG signal.

[0067] For the single-channel EEG signal x(t), this embodiment adds white noise n(t) as follows:

[0068] x'(t) = x(t) + α i ·n i (t)

[0069] where α is a scaling factor, a random value between 0.01 and 0.05, and n(t) is white noise.

[0070] As an alternative implementation, white noise with an intensity of approximately 1 - 5% is added to the single-channel EEG signal.

[0071] S3. Use the power spectrum interpolation method to process the EEG signal with added white noise, and use interpolation to correct the power spectrum to obtain a single-channel EEG signal with artifacts removed.

[0072] As an alternative implementation, referring to Figure 2 , step S3 specifically includes the following steps:

[0073] S31. For the EEG signal with added white noise, use FFT (Fast Fourier Transform) to transform it into the frequency domain to obtain the power spectrum F1.

[0074] S32. Perform median filtering on the power spectrum F1 with a width of 0.1 Hz to obtain the smoothed power spectrum F2.

[0075] S33. Subtract the power spectrum F2 from the power spectrum F1 to obtain the power spectrum difference curve F3.

[0076] S34. Detect abnormal frequency points for all points on the power spectrum difference curve F3 to obtain spectral abnormal points. Exemplarily, points with spectral values exceeding the third quartile plus 1.5 to 3 times the interquartile range (IQR) are determined as spectral abnormal points.

[0077] S35. For each outlier, consider the preset bandwidths on its left and right sides as the points where the tACS artifacts are located, and delete them from the spectrum. Exemplarily, the preset bandwidth is generally 0.25 - 0.5 Hz.

[0078] S36. Based on the frequency points of the remaining spectrum, perform cubic spline interpolation on the phases and amplitudes of the deleted frequency points respectively to complete the power spectrum and obtain the complete power spectrum F4.

[0079] In some embodiments, for the frequency points of the tACS artifacts detected through outlier detection, interpolation is used to correct the power spectrum to eliminate the spikes at these frequency points:

[0080] P 修正 (f) = spectrum_interp(P(f), f tACS )

[0081] where f tACS is the frequency of the tACS artifacts detected through outlier detection, and P(f) is the signal after the fast Fourier transform of x'(t).

[0082] S37. Perform an inverse fast Fourier transform on the power spectrum F4 to transform the signal into the time domain and obtain the single-channel EEG signal with artifacts removed.

[0083] S4. Use the obtained single-channel EEG signal with artifacts removed as the new input signal, return to iteratively execute the step of adding white noise, and obtain the new single-channel EEG signal with artifacts removed until the number of iterations reaches the preset number. Average all the obtained single-channel EEG signals with artifacts removed as the final single-channel EEG data with artifacts removed.

[0084] In this embodiment, the above process is repeated 60 to 100 times, and such analysis is performed on the interpolated signal x'(t) each time. After obtaining a corrected signal each time, perform an inverse Fourier transform y i (t), where i represents the number of iterations. After all iterations are completed, average all y i (t) to reduce the influence of random noise:

[0085]

[0086] where N is the number of iterations, usually between 60 and 100.

[0087] Generally speaking, by adding white noise (1 - 5%) with a certain intensity to the electroencephalogram (EEG) signals, and then processing these signals through power spectrum interpolation technology to remove the artifacts generated by transcranial alternating current stimulation (tACS) or other interference sources. Compared with the prior art, the originality of the present invention lies in the reverse thinking of improving signal processing by adding noise, and the use of repeated noise addition and subsequent averaging process to improve the clarity and accuracy of the signals.

[0088] Comparing the methods with and without noise assistance, it is found that adding noise can further improve the artifact removal effect, indicating that adding random noise can alleviate the underdetermined rank problem of component decomposition, and further enhance the signal-to-noise ratio of the existing components in the signal in the form of superposition averaging. Generally speaking, the noise-assisted spectral interpolation (NA Interp) scheme shows the lowest spectral leakage, good artifact suppression at the stimulation frequency point, and power spectrum distribution. A 5s EEG segment was selected, and the time-domain waveforms before and after artifact removal are as Figure 3 shown. It should be noted that in Figure 3 (a), the fluctuation scale range is 2000uV, Figure 3 and in (b), the fluctuation scale range is 55uV. It can be seen that after artifact removal by the NA Interp scheme, the EEG amplitude range of each channel is more reasonable, and at the same time, the electrooculogram artifacts caused by blinking can be clearly seen, indicating that the strong tACS artifacts are effectively removed, and the EEG components in each rhythm range are well retained, intuitively demonstrating the effectiveness of this scheme.

[0089]

[0090] Embodiment 2

[0091] A signal input module, used for inputting EEG signals;

[0092] A noise addition module, used for adding white noise to the single-channel EEG signal;

[0093] An artifact removal module, used for processing the EEG signal with added white noise by using the power spectrum interpolation method, correcting the power spectrum by using interpolation, and obtaining a single-channel EEG signal with artifacts removed;

[0094] A signal averaging module, used for taking the obtained single-channel EEG signal with artifacts removed as a new input signal, returning to iteratively execute the step of adding white noise, and obtaining a new single-channel EEG signal with artifacts removed until the number of iterations reaches the preset number, and averaging all the obtained single-channel EEG signals with artifacts removed as the final single-channel EEG data with artifacts removed.

[0095] Since this device is a tACS artifact removal device based on noise-assisted analysis in an embodiment of the present invention, and the principle of how this device solves problems is similar to that of the method, the implementation of this device can refer to the implementation process of the above method embodiment, and repeated parts will not be elaborated again.

[0096] Embodiment 3

[0097] An embodiment of the present invention further provides an electronic device. The electronic device 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. 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 Figure 1 a tACS artifact removal method based on noise-assisted analysis as shown.

[0098] It can be understood that the memory may include a random access memory (RAM), and may also include a read-only memory. Optionally, the memory includes a non-transitory computer-readable storage medium. The memory can be used to store instructions, programs, codes, code sets, or instruction sets. The memory may include a program storage area and a data storage area. Among them, the program storage area may store instructions for implementing an operating system, instructions for at least one function, instructions for implementing the above various method embodiments, etc.; the data storage area may store data created according to the use of the server, etc.

[0099] The processor may include one or more processing cores. The processor connects various parts within the entire server using various interfaces and lines. By running or executing instructions, programs, code sets, or instruction sets stored in the memory, and by calling data stored in the memory, the processor executes various functions of the server and processes data. Optionally, the processor may be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), or programmable logic array (PLA). The processor may integrate a central processing unit (CPU) and a modem, etc. in one or several combinations. Among them, the CPU mainly processes the operating system and application programs, etc.; the modem is used to process wireless communications. It can be understood that the above modem may not be integrated into the processor and may be implemented separately through a single chip.

[0100] Since this electronic device is the electronic device corresponding to a tACS artifact removal method based on noise-assisted analysis in an embodiment of the present invention, and the principle of the electronic device to solve problems is similar to that of this method, the implementation of this electronic device can refer to the implementation process of the above method embodiment, and the repeated parts will not be described again.

[0101] Embodiment 4

[0102] An embodiment of the present invention further provides a computer-readable storage medium, in which at least one instruction, at least one segment of program, code set or instruction set is stored, and the at least one instruction, the at least one segment of program, the code set or instruction set are loaded and executed by a processor to implement Figure 1 a tACS artifact removal method based on noise-assisted analysis as shown.

[0103] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program, and this program can be stored in a computer-readable storage medium. The storage medium includes read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc memories, magnetic disk memories, tape memories, or any other computer-readable medium capable of carrying or storing data.

[0104] Since this storage medium is the storage medium corresponding to a tACS artifact removal method based on noise-assisted analysis in an embodiment of the present invention, and the principle of the storage medium to solve problems is similar to that of this method, the implementation of this storage medium can refer to the implementation process of the above method embodiment, and the repeated parts will not be described again.

[0105] Embodiment 5

[0106] In some possible embodiments, aspects of the method of the embodiments of the present invention can also be implemented in the form of a program product, which includes program code. When the program product runs on a computer device, the program code is used to cause the computer device to execute the steps of a method for removing tACS artifacts based on noise-assisted analysis according to various exemplary embodiments of the present application described above in this specification. Among them, the executable computer program code or "code" for executing each embodiment can be written in high-level programming languages such as C, C++, C#, Smalltalk, Java, JavaScript, Visual Basic, Structured Query Language (e.g., Transact-SQL), Perl, or in various other programming languages.

[0107] It should be understood that each part of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application-specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0108] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0109] The above embodiments are only for illustrating the technical concept and characteristics of the present invention, and their purpose is to enable ordinary technical personnel in the art to understand the content of the present invention and implement it accordingly. However, the protection scope of the present invention cannot be limited by this. Any equivalent changes or modifications made according to the essence of the content of the present invention should be covered by the protection scope of the present invention.

Claims

1. A tACS artifact removal method based on noise-assisted analysis, characterized in that, It includes the following steps: Input the electroencephalogram (EEG) signal; Add white noise to the single-channel EEG signal; Process the EEG signal with added white noise using the power spectrum interpolation method, and use interpolation to correct the power spectrum to obtain a single-channel EEG signal with artifacts removed; Take the obtained single-channel EEG signal with artifacts removed as the new input signal, return to iteratively execute the step of adding white noise, and obtain a new single-channel EEG signal with artifacts removed until the number of iterations reaches the preset number, and average all the obtained single-channel EEG signals with artifacts removed as the final single-channel EEG data with artifacts removed.

2. The tACS artifact removal method based on noise-assisted analysis according to claim 1, wherein, The adding of white noise to the single-channel EEG signal includes: For the single-channel EEG signal x(t), white noise n(t) will be added to obtain the EEG signal with added white noise, and the expression is: x'(t) = x(t) + α i ·n i (t) where α is a scaling factor and n(t) is white noise.

3. A tACS artifact removal method based on noise-assisted analysis according to claim 1, characterized in that, The intensity of the white noise is 1 - 5%.

4. A tACS artifact removal method based on noise-assisted analysis according to claim 1, wherein The processing of the EEG signal with added white noise using the power spectrum interpolation method includes: For the EEG signal with added white noise, use the Fast Fourier Transform (FFT) to transform it to the frequency domain to obtain the power spectrum F1; Perform median filtering on the power spectrum F1 to obtain the smoothed power spectrum F2; Subtract the power spectrum F2 from the power spectrum F1 to obtain the power spectrum difference curve F3; Detect abnormal frequency points for all points on the power spectrum difference curve F3 to obtain the spectral abnormal points; For each abnormal point, consider the preset bandwidth on its left and right sides as the points where the transcranial alternating current stimulation (tACS) artifacts are located and delete them from the spectrum; Based on the frequency points of the remaining spectrum, perform cubic spline interpolation on the phase and amplitude of the deleted frequency points respectively to complete the power spectrum and obtain the complete power spectrum F4; Perform the inverse fast Fourier transform on the power spectrum F4 to transform the signal back to the time domain to obtain a single-channel EEG signal with artifacts removed.

5. A method for removing tACS artifacts based on noise-assisted analysis according to claim 4, characterized in that, The detecting of abnormal frequency points to obtain the spectral abnormal points includes: Determine the points whose spectral values exceed the third quartile plus 1.5 to 3 times the interquartile range as the spectral abnormal points.

6. The tACS artifact removal method based on noise-assisted analysis according to claim 1, wherein The using of interpolation to correct the power spectrum includes: For the frequency points of the tACS artifacts detected through abnormal point detection, use interpolation to correct the power spectrum to eliminate the spikes at these frequency points: P 修正 (f) = spectrum_interp(P(f), f tACS ) In the formula, f tACS is the frequency of the tACS artifact detected at the outlier point, P(f) is the signal of x'(t) after fast Fourier transformation, and spectrum_interp represents the frequency of the tACS artifact detected at the outlier point. tACS Delete f for the center tACS The preset bandwidths on the left and right sides are extracted from the spectrum, and then based on the frequency points of the remaining spectrum, cubic spline interpolation is performed on the phase and amplitude of the deleted frequency points to complete the power spectrum.

7. A tACS artifact removal method based on noise-assisted analysis according to claim 1, characterized in that The averaging of all the obtained single-channel EEG signals with artifacts removed as the final single-channel EEG data with artifacts removed includes: After the EEG signal x'(t) with added white noise each time is processed by the power spectrum interpolation method, the single-channel EEG signal y i (t) without artifacts is obtained, where i represents the number of iterations; After all iterations are completed, average all y i (t) where N is the total number of iterations.

8. An apparatus for removing tACS artifacts based on noise-assisted analysis, characterized in that, It includes: A signal input module for inputting the EEG signal; A noise adding module for adding white noise to the single-channel EEG signal; An artifact removal module for processing the EEG signal with added white noise using the power spectrum interpolation method and using interpolation to correct the power spectrum to obtain a single-channel EEG signal with artifacts removed; A signal averaging module for taking the obtained single-channel EEG signal with artifacts removed as the new input signal, returning to iteratively execute the step of adding white noise, and obtaining a new single-channel EEG signal with artifacts removed until the number of iterations reaches the preset number, and averaging all the obtained single-channel EEG signals with artifacts removed as the final single-channel EEG data with artifacts removed.

9. An electronic device, characterized in that, The electronic device 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 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 method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, At least one instruction, at least one program, a code set, or an instruction set is stored in the storage medium, and the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by a processor to implement the method according to any one of claims 1 to 7.

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