CN117503162B - Method for determining position of ocular artifacts in single-channel electroencephalogram signals - Google Patents
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Abstract
本申请提出一种单通道脑电信号中的眼电伪迹位置确定方法，先通过计算滑动窗口内的高阶累积量来初步定位眼电发生的区间，然后再结合该区间内眼电的峰值，来调整初步起始位置和终止位置，准确识别眼电伪迹的区间的两端，最终实现眼电伪迹位置准确确定。
The present application proposes a method for determining the position of electrooculogram artifacts in a single-channel EEG signal. The method first calculates the high-order cumulative amount in the sliding window to preliminarily locate the interval where the electrooculogram occurs, and then adjusts the preliminary starting position and ending position based on the peak value of the electrooculogram in the interval, accurately identifies the two ends of the interval of the electrooculogram artifact, and finally achieves accurate determination of the position of the electrooculogram artifact.
Description
Technical Field
The application relates to a processing technology of electroencephalogram signals, in particular to a method for determining the position of an electro-oculogram artifact in a single-channel electroencephalogram signal.
Background
The single-lead electroencephalogram system in forehead She Fanwei is the brain region range most often involved in the realization and application process of portable electroencephalogram, can realize long-time and movement detection, and is widely applied to various mobile non-clinical environments. However, since the forehead lobe is relatively close to the eye, it is more susceptible to interference from ocular artifacts.
For single-channel electroencephalogram artifact removal, decomposition methods such as wavelet decomposition, modal decomposition, independent component decomposition and the like are commonly used at present. However, the method based on signal decomposition always carries out artifact filtering on the whole section of polluted brain electricity, because the method is not limited to carrying out artifact removal in the actual occurrence interval of the eye electricity artifacts, and the non-artifact components in the brain electricity signals are easily filtered out while the eye electricity artifacts are removed.
Therefore, in order to reduce the influence on the effective electroencephalogram signal, in recent years, there has been studied to limit the artifact removal range to an actual occurrence range of the ocular artifacts, and thus detection and identification of the actual occurrence range of the ocular artifacts are involved. At present, the detection of the ocular artifacts mainly comprises methods of amplitude threshold value, template matching, peak detection and the like. However, the above methods have respective disadvantages, and the method based on the amplitude threshold has limitations due to the difference of the ocular artifact amplitudes; the effect of the template matching based algorithm depends on the correct definition of the template and the threshold; after the peak value is detected by the peak value detection algorithm, the generation interval of the electrooculogram needs to be estimated, and the detection is inaccurate.
Disclosure of Invention
In view of the above problems, the application aims to provide an electro-oculogram artifact position determining method in a single-channel electroencephalogram signal, which can accurately determine the position of the electro-oculogram artifact in the electroencephalogram signal and lays a foundation for realizing local filtering of the electro-oculogram artifact.
The application relates to a method for determining the position of an ocular artifact in a single-channel electroencephalogram signal, which comprises the following steps:
sliding window processing is carried out on the single-channel electroencephalogram signals, and high-order accumulation amounts in each window are calculated respectively;
Determining a starting endpoint and a terminating endpoint of the electro-oculogram artifact through a high-order accumulation local maximum value, thereby determining a preliminary starting position (D) and a preliminary terminating position (D1) of the electro-oculogram artifact in the single-channel electroencephalogram signal;
calculating the position (O) of the peak value (P) of the ocular artifacts;
Executing a judging step of whether the preliminary starting position (D) is correct or not; the judging step comprises the following steps: judging whether the corresponding electrooculogram amplitude value at the midpoint position of the position (O) of the initial starting position (D) and the electrooculogram peak value (P) is 0.4-0.6 times of the electrooculogram peak value (P); if the judgment result is yes, the preliminary initial position (D) is considered to be accurate, and the preliminary initial position (D) is taken as an eye artifact starting point; if the judgment result is negative, the judgment step of judging whether the preliminary initial position (D) is correct or not is re-executed after the position of the preliminary initial position (D) is adjusted until the judgment result is positive;
Executing a judging step of whether the preliminary termination position (D1) is correct or not; the judging step comprises the following steps: judging whether the corresponding electrooculogram amplitude value at the midpoint position of the position (O) of the preliminary termination position (D) and the electrooculogram peak value (P) is 0.4-0.6 times of the electrooculogram peak value (P); if the judgment result is yes, the preliminary termination position (D1) is considered to be accurate, and the preliminary termination position (D1) is taken as an eye artifact end point; if the judgment result is negative, the judgment step of whether the preliminary termination position (D1) is correct or not is re-executed after the position of the preliminary termination position (D1) is adjusted until the judgment result is positive.
Preferably, the method of adjusting the position of the preliminary starting position (D) is to move the preliminary starting position (D) in a direction approaching the position (O) of the eye artifact peak (P) if the corresponding eye electrical amplitude at the midpoint position of the position (O) of the preliminary starting position (D) and the eye artifact peak (P) is less than 0.4 times the eye electrical artifact peak (P); if the corresponding electrooculogram amplitude at the midpoint position of the preliminary starting position (D) and the position (O) of the electrooculogram peak (P) is greater than 0.6 times the electrooculogram peak (P), the preliminary starting position (D) is moved in a direction away from the position (O) of the electrooculogram peak (P).
Preferably, the method of adjusting the position of the preliminary termination position (D1) is that if the corresponding electrooculogram amplitude at the midpoint position of the preliminary termination position (D1) and the position (O) of the electrooculogram peak (P) is less than 0.4 times the electrooculogram peak (P), the preliminary termination position (D1) is moved in a direction approaching the position (O) of the electrooculogram peak (P); if the corresponding electrooculogram amplitude at the midpoint position of the preliminary termination position (D1) and the position (O) of the electrooculogram artifact peak value (P) is greater than 0.6 times the electrooculogram artifact peak value (P), the preliminary termination position (D1) is moved in a direction away from the position (O) of the electrooculogram artifact peak value (P).
Preferably, the preliminary start position (D) or the preliminary end position (D1) is moved in units of sampling points.
Preferably, the window length of the sliding window is set to 0.4 xfs, where Fs is the sampling rate of the single channel electroencephalogram signal.
Preferably, the higher order cumulative amount is a third order cumulative amount.
According to the method for determining the position of the electro-oculogram artifact in the single-channel electroencephalogram signal, the region where the electro-oculogram occurs is initially positioned by calculating the high-order accumulation amount in the sliding window, then the initial starting position and the final end position are adjusted by combining the peak value of the electro-oculogram in the region, two ends of the region of the electro-oculogram artifact are accurately identified, and finally the accurate determination of the position of the electro-oculogram artifact is realized.
Drawings
FIG. 1 is a schematic diagram of an EEG signal contaminated by ocular artifacts and its short-term third-order cumulative amount;
FIG. 2 is a schematic diagram of an EEG signal contaminated by ocular artifacts and its short-term fourth-order cumulative amount;
FIG. 3 is a graph of results of preliminary identification of an electro-oculogram interval after calculation of an electro-oculogram signal contaminated by electro-oculogram artifacts;
FIG. 4 is a schematic illustration of an adjustment to identify the start and end points of an electro-oculogram;
FIG. 5 is a graph showing the contaminated EEG signal and the corresponding sliding window high-order cumulants and further adjusting the recognition endpoints.
Detailed Description
The method for determining the position of the ocular artifacts in the single-channel electroencephalogram signal is described in detail below with reference to the accompanying drawings.
Fig. 1 is an electroencephalogram signal contaminated with ocular artifacts and a short-time third-order cumulative amount. The contaminated electroencephalogram signals in (a) are respectively calculated to be short-time third-order accumulation amounts (b) through sliding windows, and the third-order accumulation amounts corresponding to the fragments 1,2 and 3 in (a) are respectively marked in (b).
Higher order cumulants are important tools for processing non-gaussian, non-linear signals. The first-order and second-order cumulants of the gaussian-distributed random variables are exactly equal to their mean and variance, respectively, and the higher-order cumulants (order greater than 2) of the gaussian random variables are identical to zero. The higher order cumulants are insensitive to gaussian random processes and theoretically, the higher order cumulants can effectively suppress gaussian signals. The electroencephalogram signal has certain Gaussian characteristics, the amplitude distribution of the electroencephalogram signal is similar to the statistical characteristics of Gaussian distribution, and the electroencephalogram signal does not accord with the characteristics of Gaussian distribution. The invention proposes to detect the eye electric signal by calculating the high-order accumulation amount of the sliding window, specifically, the contaminated brain electric windowing is processed, the high-order accumulation amount in each window is calculated respectively, as shown in fig. 1, and the high-order accumulation amounts corresponding to the brain electric fragments 1,2 and 3 in the (a) diagram are marked in the (b) diagram respectively.
In a specific implementation, it is the order of the higher order cumulants and the size of the sliding window that need to be determined. For the determination of the order of the higher-order cumulant, the higher-order cumulant which is theoretically larger than the 2 nd order can well suppress noise (as shown in fig. 2), but the higher-order calculation amount is larger, so that the third-order cumulant is selected to be optimal, and the calculation of the third-order cumulant can be obtained through a cut 3est function in a high-order spectrum toolbox of matlab.
For the determination of the size of the sliding window, if the window length is too short, the signal in the window is more approximate to non-Gaussian distribution and is not easy to be restrained; if the window length is too long, the resolution of the identified eye power is reduced. In this design we set the window length to 0.4 xfs, since there is a study that indicated that the duration of the ocular artifacts is typically 200-400ms, the window length was chosen to be 0.4 xfs for more coverage of the ocular artifact occurrence range.
As can be seen from fig. 1, if the electroencephalogram signal is within the window, the higher order cumulative magnitude is smaller; if there is an electro-oculogram signal in the window, the high order cumulative magnitude becomes large, and when the electro-oculogram peak value enters the window, the high order cumulative magnitude reaches a local maximum. The time at which the higher order cumulative local maxima are located may be defined as the initial and final endpoints of the preliminarily identified eye charge.
After the preliminary identification of the eye electricity is completed, as the real eye electricity interval is changed, when the difference between the real eye electricity interval and 0.4 xFs is larger, the error of the eye electricity interval in the preliminary identification is larger, as shown in fig. 3, the accuracy of the identification eye electricity result is poorer as shown in the figure, which is the preliminary identification eye electricity interval obtained after the sliding window high-order accumulation processing is performed on the brain electricity with the real eye electricity interval of 200 ms.
In order to further optimize the identification effect, the application provides a section further adjustment method combining the electrooculogram peak value. Specifically, as shown in fig. 4, the point O is the position of the peak P of the true eye electricity, and the point P is obtained by smoothing the preliminary identification eye electricity interval (D-D1) and then taking the maximum value (the denoising method may be various methods, such as wavelet denoising, smoothing filtering, low-pass filtering, etc.). T-T1 is a real eye electric interval, D-D1 is a preliminary identification eye electric interval, and the adjustment direction of D-D1 is that two endpoints approach to T-T1 respectively. The specific method for further adjusting the preliminary identification eye electric interval is as follows: taking the O point location reference point, DO is the left half section of the preliminary identification electrooculogram, and D 1 O is the right half section of the preliminary identification electrooculogram. Finding the center point position of the left half interval DO, obtaining the corresponding amplitude of the real eye electricity, calculating the Ratio of the amplitude to the eye electricity peak value, and if the Ratio is between 0.4 and 0.6, considering that the preliminary identification eye electricity interval adjustment is completed. Specifically, if Ratio is less than 0.4, D moves one sampling point to the right, and then Ratio is calculated until Ratio is between 0.4 and 0.6, and adjustment is completed; if Ratio >0.6, the D point is moved leftwards by one sampling point, and Ratio is calculated again until the Ratio is between 0.4 and 0.6, and the adjustment is completed. Wherein, the ratio value interval of 0.4-0.6 is an empirical value obtained according to the characteristics of the electrooculogram curve.
The above is to identify the adjustment of the left half interval of the electrooculogram, and the right half is the same as the left half. Finally, accurate detection and identification of the single-channel eye electric interval are realized, as shown in fig. 5, (b) the solid line in the figure corresponds to the initial identification eye electric interval end point, the dotted line corresponds to the adjusted identification eye electric interval end point, and further adjustment can be seen on the basis of the initial identification eye electric interval, so that the identification eye electric interval is closer to the real eye electric interval, and the eye electric detection is more accurate.
According to the application, the electro-oculogram generation interval is initially positioned based on calculation of the high-order accumulation amount of the sliding window, and then the electro-oculogram generation interval is further adjusted by combining with the electro-oculogram peak value, so that the electro-oculogram generation position is accurately identified. The accurate identification of the electro-oculogram artifacts can ensure that the effective electroencephalogram signals are reserved to the greatest extent on the basis of removing the electro-oculogram artifacts, and the removal effect of the electroencephalogram signals is improved as a whole.
Unless defined otherwise, all technical and/or scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application relates. The materials, methods, and examples mentioned herein are illustrative only and not intended to be limiting.
Although the present application has been described in connection with specific embodiments thereof, those skilled in the art will appreciate that various substitutions, modifications and changes may be made without departing from the spirit of the application.
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