Title: Denoising and Error Removal of EEG Signal using WDT and Smoothing Filters

Year of Publication: May - 2016
Page Numbers: 17-26
Authors: Mahmoud I. Al-Kadi, Mamun Bin Ibne Reaz
Conference Name: 2016 Universal Technology Management Conference (UTMC)
- United States

Abstract:


Electroencephalogram (EEG) signals are significantly distorted in case of any external interference which inevitably affects monitoring the Depth of Anesthesia (DOA). During scoliosis correction surgeries, the error sample rate and noise level are remarkably increased because surgeons use high power electronic equipment and several kinds of electric hand tools. This research investigates the main causes of EEG signal distortion during this kind of operations and discusses the denoising process during different stages of anesthesia. This paper presents and tests a novel EEG denoising technique for scoliosis correction surgeries using a hybrid combination of conventional filters, Wavelet noise removal and smoothing filters. The Savitzky-Golay (SG) smoothing filter removes the residual noise overlapped with EEG signals and also smooth the sharp points resulted from removing high power noise, high speed sampling rate and sudden changes in EEG signals. The parameters of these filters are continuously changed according to the noise level and DOA in order to preserve the signal characteristics. The experimental outcomes present that the resultant EEG data are significantly corrected and fully denoised without any substantial variation in their components.