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Removal of ballistocardiogram artifacts exploiting second order cyclostationarity

Ghaderi, Foad, Nazarpour, Kianoush, McWhirter, John and Sanei, Saeid 2010. Removal of ballistocardiogram artifacts exploiting second order cyclostationarity. Presented at: 20th IEEE International Workshop on Machine Learning for Signal Processing, Kittilä, Finland, 29 August-1 September 2010. Published in: Kaski, S., Miller, D. J., Oja, E. and Honkela, A. eds. Proceedings of the 2010 IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2010). Los Alamitos, CA: IEEE, pp. 71-76. 10.1109/MLSP.2010.5589220

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Abstract

Simultaneous recording of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is increasingly used to monitor the brain activity. The interactions between the scanner magnetic field, the patient's body, and the EEG electrodes generate a pulsation artifact called ballistocardiogram (BCG) which is synchronized with the patient's heart beat. The BCG artifact is considered here as the sum of a number of independent cyclostationary components having the same cycle frequency. Cyclostationary source extraction (CSE) is used here to remove BCG artifact. The results are compared with the results of benchmark BCG removal techniques. It is shown that visual evoked potentials (VEPs) recorded inside the scanner and processed using the proposed method are more correlated with the VEPs recorded outside the scanner. Moreover, the presence of electrocardiogram (ECG) data is not necessary in this method as the cycle frequency of the BCG is directly computed from the contaminated EEG signals.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Engineering
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Additional Information: Twentieth in a Series of Workshops Organised by the IEEE Signal Processing Society Machine Learning for Signal Processing Technical Committee; August 29 – September 1, 2010, Kittilä, Finland
Publisher: IEEE
ISBN: 9781424478750
Last Modified: 04 Jun 2017 02:57
URI: http://orca-mwe.cf.ac.uk/id/eprint/14353

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