An Experimental Analysis on EMG Artifact Removal Methods from EEG Signal Records

Abstract

Electromyography is the measurement of the muscle action prospective (MUAP) in many muscle tissue over time and space (EMG). In real time measurements, EMG signals will damage electromyography data, making effective investigation and elucidation of EEG signals difficult. A crucial step is to eliminate distortions of EMG from EEG records. Singular Spectrum Analysis and Multimodal Empirical Mode Decomposition are two new methods for reducing EEG distortions. Using Independent Component Analysis and the Wavelet Method together, for example, some researchers supplied two approaches and then exploited their respective benefits to further eliminate artifacts without hurting the EEG data. New approaches for eliminating muscle artefacts from EEG are studied in this research. Signal transformations, filtering algorithms as well as blind source separation are among the fundamental techniques examined.