Removal of ballistocardiogram artifact from electroencephalograms exploiting heart rate variability

Authors:
A. Kosma;K. Nazarpour;S. Sanei
Affiliations:
Centre of Digital Signal Processing, Cardiff University, Wales, UK;Centre of Digital Signal Processing, Cardiff University, Wales, UK;Centre of Digital Signal Processing, Cardiff University, Wales, UK
Venue:
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
Year:
2009

Citing 2
Cited 0

Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications

Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
A novel semiblind signal extraction approach for the removal of eye-blink artifact from EEGs

EURASIP Journal on Advances in Signal Processing

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Abstract

An approach for eliminating the cardiac pulsation (ballistocardiogram, BCG) effect from electroencephalograms (EEG) is proposed. The artifact results from functional magnetic resonance imaging (fMRI) scanner during simultaneous EEG-fMRI recordings. The BCG artifact exhibits similar periodic physiological structure. The proposed blind source extraction (BSE) algorithm employs second order statistics to exploit the heart rate variability and focuses on the contaminated EEG segments. This method is compared with some previously developed, well-known algorithms such as FastICA, SOBI and JADE, and a qualitative comparison is given. The methods are examined for both synthetic and real data.