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1、A WAVELET BASED DE-NOISING TECHNIQUE FOROCULAR ARTIFACT CORRECTION OF THE ELECTROENCEPHALOGRAMTatjana Zikov, Stphane Bibian, Guy A. Dumont, Mihai HuzmezanDepartment of Electrical and Computer Engineering, the University of British Columbia, BC, CANADA.Abstract This paper investigates a wavelet based
2、 denoising of the electroencephalogram (EEG) signal to correct for the presence of the ocular artifact (OA).The proposed technique is based on an over-complete wavelet expansion of the EEG as follows: i) a stationary wavelet transform (SWT) is applied to the corrupted EEG; ii) the thresholding of th
3、e coefficients in the lower frequency bandsis performed; iii) the de-noised signal is reconstructed. This paper demonstrates the potential of the proposed technique for successful OA correction. The advantage over conventional methods is that there is no need for the recording of the electrooculogra
4、m (EOG) signal itself. The approach works both for eye blinks and eye movements. Hence, there is no need to discriminate between different artifacts. To allow for a proper comparison, the contaminated EEG signals as well as the corrected signals are presented together with their corresponding power
5、spectra.Keywords-stationary wavelet transform (SWT), electroencephalogram (EEG), electrooculogram (EOG), ocular artifact (OA).I. INTRODUCTIONThe electroencephalogram (EEG) gives researchers a non-invasive insight into the intricacy of the human brain. It is a valuable tool for clinicians in numerous
6、 applications, from the diagnosis of neurological disorders, to the clinical monitoring of depth of anesthesia. For awake healthy subject, normal EEG amplitude is in the order of 20-50V.The EEG is very susceptible to various artifacts, causing problems for analysis and interpretation. In current dat
7、a acquisition, eye movement and blink related artifacts are often dominant over other electrophysiological contaminating signals (e.g. heart and muscle activity, head and body movements), as well as external interferences due to power sources. Eye movements and blinks produce a large electrical sign
8、al around the eyes (in the order of mV), known as electrooculogram (EOG), which spreads across the scalp and contaminates the EEG. These contaminating potentials are commonly referred to as ocular artifact (OA).The rejection of epochs contaminated with OA usually leads to a substantial loss of data.
9、 Asking subjects not to blink or move their eyes or to keep their eyes shut and still, is often unrealistic or inadequate. The fact that the subject is concentrating on fulfilling these requirements might itself influence his EEG. Hence, devising a method for successful removal of ocular artifacts (
10、OA) from EEG recordings has been and still is a major challenge. Widely used time-domain regression methods involve the subtraction of some portion of the recorded EOG from the EEG 1, 2. They assume that the propagation of ocular potentials is volume conducted, frequency independent and without any
11、time delay. However, Gasser et al. in 3 argued that the scalp is not a perfect volume conductor, and thus, attenuates some frequencies more than others. Consequently, frequency domain regression was proposed. In addition, no significant time delay was found, which was in consistency with the EOG bei
12、ng volume conducted.In 4 it was reported that, in reality, the frequency dependence does not seem to be very pronounced, while the assumption of no measurable delay was confirmed. Thus, while some researchers support the frequency domain approach for EOG correction 3, 5, others disputed its advantag
13、es 4, 6, 7. However, neither time nor frequency regression techniques take into account the propagation of the brain signals into the recorded EOG. Thus a portion of relevant EEG signal is always cancelled out along with the artifact. Further, these techniques mainly use different correction coeffic
14、ients for eye blinks versus eye movements. They also heavily depend on the regressing EOG channel.In addition, Croft and Barry 7 demonstrated that the propagation of the EOG across the scalp is constant with respect to ocular artifact types and frequencies. They proposed a more sophisticated regress
15、ion method (the aligned-artifact average solution) that corrects blinks and eye movement artifacts together, and made possible the adequate correction for posterior sites 6. They claim that the influence of the EEG-to-EOG propagation has been minimized in their method.In an attempt to overcome the p
16、roblem of the EEG-to-EOG propagation, a multiple source eye correction method has been proposed by Berg and Scherg 8. In this method, the OA was estimated based on the source eye activity rather than the EOG signal. The method involves obtaining an accurate estimate of the spatial distribution of the eye activity from calibration data, which is a rather difficult task.Due to its decorrelation efficiency, the principal component analysis (PCA) has
