Title
A hybrid ICA-Hermite transform for removal of Ballistocardiogram from EEG.
Abstract
In this paper the problem of removing Ballistocardiogram (BCG) artifact from EEG signal is addressed. BCG removal is an important task in analysis of simultaneous EEG-fMRI data. We propose a new method by combining independent component analysis (ICA) and discrete Hermite transform (DHT) for this purpose. Discrete Hermite transform is a powerful technique which is able to model a signal with no assumption about its shape. This feature makes DHT an appropriate tool to be combined with ICA for removing the BCG artifact. We show that the proposed hybrid ICA-Hermite transform can compensate for the existing drawbacks of the two methods, when applied separately. A significant improvement over conventional methods is demonstrated with synthetic data, and supported by preliminary work with real EEG.
Year
Venue
Keywords
2012
European Signal Processing Conference
Artifact removal,Ballistocardiogram,Independent component analysis,Discrete Hermite transform
Field
DocType
ISSN
Computer vision,Hermite transform,Computer science,Synthetic data,Independent component analysis,Artificial intelligence,Electroencephalography
Conference
2076-1465
Citations 
PageRank 
References 
0
0.34
10
Authors
5
Name
Order
Citations
PageRank
Saideh Ferdowsi114710.85
Saeid Sanei253072.63
Judith Nottage300.34
Owen O'Daly400.68
Vahid Abolghasemi527422.58