Title :
Removal of blink from EEG by Empirical Mode Decomposition (EMD)
Author :
Shahbakhti, M. ; Khalili, V. ; Kamaee, G.
Author_Institution :
Dept. of Biomed. Eng., Islamic Azad Univ., Dezfoul, Iran
Abstract :
The electroencephalographic signals (EEG) are rather weak and contaminated with different artifacts that have biological and external sources. Among these artifacts, blinks and eye movements are the most common of them. In this paper, we introduce a new method, Empirical Mode Decomposition (EMD), for removal of blink contamination from EEG signal. The proposed method is compared to a fourth order Butterworth high-pass filtering with cutoff frequency at 2 Hz. The performance index of our experiment is mean square error (MSE) between bands of pure EEG and corrected EEG. Results obtained from the analysis of contaminated EEG signal show that EMD method outperforms the high pass filtering for elimination of blink contamination from EEG. However, EMD could not be applied on-line.
Keywords :
Hilbert transforms; electroencephalography; eye; medical signal processing; EEG; EMD; blink contamination removal; electroencephalographic signals; empirical mode decomposition; eye movements; fourth order Butterworth high pass filter comparison; mean square error; Adaptive filters; Contamination; Electroencephalography; Electrooculography; Empirical mode decomposition; Entropy; Filtering; Blink; EEG; Empirical Mode Decomposition (EMD); High pass filter; mean square error (MSE);
Conference_Titel :
Biomedical Engineering International Conference (BMEiCON), 2012
Conference_Location :
Ubon Ratchathani
Print_ISBN :
978-1-4673-4890-4
DOI :
10.1109/BMEiCon.2012.6465451