Engineering approaches for ECG artefact removal from EEG: a review

Abstract

Electroencephalograms (EEGs) signal, obtained by recording the brain waves are used to analyse health problems related to neurology and clinical neurophysiology. This signal is often contaminated by a range of physiological and non-physiological artefacts, which leads to a misinterpretation in EEG signal analysis. Hence, artefact removal is one of the pre-processing step required for clinical usefulness of the EEG signal. One of the physiological artefact, i.e., electrocardiogram (ECG) contaminated EEG can affect the clinical analysis and diagnosis of brain health in various ways. This paper presents a review of engineering approaches adopted till date for ECG artefact identification and removal from contaminated EEG signal. In addition, the technical approach, computational extensiveness, input requirement and the results achieved with every method is discussed. Along with that, the feasibility study for real time implementation of the algorithms is discussed. Also, an analysis of these methods has been reported based on their performance.