Key result
Various artifact removal techniques, including Blind Source Separation and Empirical Mode Decomposition, are effective in removing physiological artifacts from EEG signals.
This technical review outlines the strengths and weaknesses of different mathematical and signal processing techniques used to filter physiological artifacts (like eye blinks and muscle movements) from EEG recordings.
Electroencephalograms are the neurological signals which help in the study of various diseases. These are often contaminated with various artifacts. It is difficult to study and analysis of brain signals in the existence of these artifacts. EOG, ECG, motion and EMG are the common artifacts which cause disturbance to neurological signal. This review paper focuses on the artifact removal techniques with their features. Important parameters were taken into consideration while the study of various published papers. Strength and weakness of each paper are mentioned. This review of various papers is best of my knowledge.
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Prakash et al. (2016) conducted a review in EEG artifacts. Artifact removal techniques (BSS, EMD, Wavelet Transform) was evaluated. Various artifact removal techniques, including Blind Source Separation and Empirical Mode Decomposition, are effective in removing physiological artifacts from EEG signals.
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