Mitigation of ocular artifacts for EEG signal using improved earth worm optimization-based neural network and lifting wavelet transform.

Mitigation of ocular artifacts for EEG signal using improved earth worm optimization-based neural network and lifting wavelet transform. Comput Methods Biomech Biomed Engin. 2020 Nov 27;:1-28 Authors: Prasad DS, Chanamallu SR, Prasad KS Abstract An Electroencephalogram (EEG) is often tarnished by various categories of artifacts. Numerous efforts have been taken to improve its quality by eliminating the artifacts. The EEG involves the biological artifacts (ocular artifacts, ECG and EMG artifacts), and technical artifacts (noise from the electric power source, amplitude artifacts, etc.). From these physiological artifacts, ocular activities are one of the most well-known over other noise sources. Reducing the risks of this event and avoid it is practically very difficult, even impossible, as the ocular activities are involuntary tasks. To trim down the effect of ocular artifacts overlapping with EEG signal and overwhelm the subjected flaws, few intelligent approaches have to be developed. This proposal tempts to implement a novel method for detecting and preventing ocular artifacts from the EEG signal. The developed model involves two main phases: (a) Detection of Ocular artifacts and (b) Removal of ocular artifacts. For detecting the ocular artifacts, initially, the EEG is subjected to decomposition process using 5-level Discrete Wavelet Transform (DWT), and Empirical Mean Curve Decomposition (EMCD). Next to the decomposition process,...
Source: Computer Methods in Biomechanics and Biomedical Engineering - Category: Biomedical Engineering Authors: Tags: Comput Methods Biomech Biomed Engin Source Type: research