A Statistical Approach for Ocular Artifact Removal in Brain Signals

Brain signal analysis is a complex task. Many cases artifacts are generated at the time of signal acquisition. In this paper authors have taken an approach using statistical technique to remove the artifacts from the signal. For such attempt a new-multiscale sample entropy (new-MSE) along with the statistical method kurtosis are used for identification of artifact. Considering the automated threshold, the application of wavelet transform is performed to evaluate the exact co-efficient. Further the inverse of the transform helps to construct the artifact free signal. Proposed method proves its efficacy and is shown in the result section. Also, the signals are visually inspected in form of waveform.