Hybrid De-Noising Algorithm Using Bpf And Wavelet For Fp1 Channel Eye Blink Rejection On Brain Eeg Artefact

Authors

  • Ebtesam N. AlShemmary , Mohammed Ali Ahmed , Lu Zhentai

Abstract

This Wavelet Transform (WT) is a mathematical procedure that widely used for the wanted information extraction from different data. Using wavelet transform (WT) in Blind Source Separation (BSS) had shortcomings of not satisfying pure signal. A hybrid algorithm of (WT) and Bandpass Filtering Process (BPF) will overcome the blemishes. In this work, a novel algorithm suggested dismissing eye flickering from Electroencephalogram (EEG) signals based on the mix between Wavelet De-noising Technique (WDT) and the bandpass filtering process (BPF) called Evolutionary Wavelet Transform (EWT) algorithm. The main purpose of the proposed algorithm is for the eye blinking rejection from the FP1 channel on Electroencephalogram (EEG) signals to get a pure EEG signal. The results show that this integration is a more efficient method compared with the conventional wavelet transform (WT) method. The Signal-to-Noise Ratio (SNR) and Power Spectral Density (PSD) are measuring the quality of the removing process.

 

Published

2020-12-01

Issue

Section

Articles