%0 Conference Paper
%A Javed, E.
%A Faye, I.
%A Malik, A.S.
%A Abdullah, J.M.
%D 2014
%F scholars:4909
%I IEEE Computer Society
%K Magnetic resonance imaging; Principal component analysis; Signal processing, Ballistocardiogram artifact; Brain activity; Composite algorithm; Empirical Mode Decomposition; Event related potentials; Functional magnetic resonance images (fMRI); Neuronal activities; Simultaneous EEG-fMRI, Electroencephalography
%R 10.1109/ICIAS.2014.6869512
%T Reference-free reduction of ballistocardiogram artifact from EEG data using EMD-PCA
%U https://khub.utp.edu.my/scholars/4909/
%X Concurrent electroencephalograph (EEG) and functional magnetic resonance image (fMRI) led researchers to acquire neuronal activities in detail over the past few decades. Regardless of the advantages of combining these modalities, artifacts posed a greater challenge to attain good quality data. One such problematic artifact which contaminates EEG recordings is Ballistocardiogram (BCG) artifact. A reference-free composite algorithm which combines empirical mode decomposition (EMD) and principal component analysis (PCA) named as EMD-PCA has been introduced in this study. The results show that the algorithm can efficiently reduce the BCG artifact by preserving original neuronal signals. The proposed algorithm showed improvement in reducing the BCG artifact as well as in the preservation of brain activities, when compared with two renowned existing methods that are average artifact subtraction (AAS) and optimal basis set (OBS). © 2014 IEEE.
%Z cited By 5; Conference of 2014 5th International Conference on Intelligent and Advanced Systems, ICIAS 2014 ; Conference Date: 3 June 2014 Through 5 June 2014; Conference Code:107042