Eye Blink Artefact Removal of Single Frontal EEG Channel Algorithm using Ensemble Empirical Mode Decomposition and Outlier Detection

Mohd Nurul Al Hafiz Sha'abani; Norfaiza Fuad; Norezmi Jamal

doi:10.11113/mjfas.v17n6.2287

Authors

Mohd Nurul Al Hafiz Sha'abani Universiti Tun Hussein Onn Malaysia
Norfaiza Fuad Universiti Tun Hussein Onn Malaysia
Norezmi Jamal Universiti Tun Hussein Onn Malaysia

DOI:

https://doi.org/10.11113/mjfas.v17n6.2287

Keywords:

electroencephalogram, eye blink removal, single-channel, EEMD

Abstract

Recently, the emergence of various applications to use EEG has evolved the EEG device to become wearable with fewer electrodes. Unfortunately, the process of removing artefact becomes challenging since the conventional method requires an additional artefact reference channel or multichannel recording to be working. By focusing on frontal EEG channel recording, this paper proposed an alternative single-channel eye blink artefact removal method based on the ensemble empirical mode decomposition and outlier detection technique. The method removes the segment of the potential eyeblinks artefact on the residual of a pre-determined level of decomposition. An outlier detection technique is introduced to identify the peak of the eyeblink based on the extreme value of the residual signal. The results showed that the corrected EEG signal achieved high correlation, low RMSE and have small differences in PSD when compared to the reference clean EEG. Comparing with an adaptive Wiener filter technique, the corrected EEG signal by the proposed method had better signal-to-artefact ratio.

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