STATIONARY WAVELET BASED STATISTICAL APPROACH FOR OCULAR ARTIFACTS REMOVAL IN THE EEG SIGNAL
Electroencephalogram (EEG) is a bioelectric signal, related to brain activity used as an important tool by physicians for studying the functional state of the brain and for diagnosing certain neurophysiologic states and disorders. Whether obtained from the scalp, cortex, or depths of the brain, the potentials recorded represent the activity of numerous neurons. This may include the activity of surrounding organs also, which forms the artifacts. Artifacts in EEG signals are caused by various factors, like line interference, Eye blinks, Eye ball movements and ECG (electrocardiogram). The presence of physiological artifacts such as eye blinks, in EEG recordings obscures the underlying processes and makes analysis problematic. We have used wavelet based approach for correcting the artifacts generated by eye blink and eye ball movements in EEG. Various methods such as Eye fixation method, Regression methods, PCA, ICA, adaptive and non adaptive thresholding methods are studied and an appropriate threshold limit and a thresholding function is found which shows its potential in removing the ocular artifacts, while preserving the necessary background activity. The removal of ocular artifact from scalp EEGs is of considerable importance for both the automated and visual analysis of underlying brainwave activity. Stationary Wavelet Transform (SWT) is used to decompose the recorded EEG. Depending on the choice of mother wavelet function, larger coefficients will be generated corresponding to the noise affected areas. The larger coefficients will now be an estimate of noise. Appropriate threshold limit is found which separates the noise coefficients and the signal coefficients.
Stationary Wavelet Transform (SWT) Electroencephalogram (EEG) and Wavelet Thresholding
Sanjanna.V Dabbu.Suman M.Venkateswara Rao
National Productivity Council, Govt.of India Hyderabad India Department of Biomedical Engineering University College of Engineering Osmania University, Hyderabad
国际会议
成都
英文
214-218
2011-01-14（万方平台首次上网日期，不代表论文的发表时间）