Please use this identifier to cite or link to this item:
|Title:||Joint spatial-temporal filter design for analysis of motor imagery EEG||Authors:||Li, X.
|Keywords:||brain computer interface
spatial filter design
|Issue Date:||18-Oct-2013||Citation:||Li, X.,Zhang, H.,Guan, C.,Ong, S.H.,Pan, Y.,Ang, K.K. (2013-10-18). Joint spatial-temporal filter design for analysis of motor imagery EEG. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings : 978-982. ScholarBank@NUS Repository. https://doi.org/10.1109/ICASSP.2013.6637795||Abstract:||This paper addresses the key issue of discriminative feature extraction of electroencephalogram (EEG) signals in brain-computer interfaces. Recent advances in neuroscience indicate that multiple brain regions can be activated during motor imagery. The signal propagation among the regions can give rise to spurious effects in identifying event-related desynchronization/synchronization for discriminative motor imagery detection in conventional feature extraction methods. Particularly, we propose that computational models which account for both signal propagation and volume conduction effects of the source neuronal activities can more accurately describe EEG during the specific brain activities and lead to more effective feature extraction. To this end, we devise a unified model for joint learning of signal propagation and spatial patterns. The preliminary results obtained with real-world motor imagery EEG data sets confirm that the new methodology can improve classification accuracy with statistical significance. © 2013 IEEE.||Source Title:||ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings||URI:||http://scholarbank.nus.edu.sg/handle/10635/83876||ISBN:||9781479903566||ISSN:||15206149||DOI:||10.1109/ICASSP.2013.6637795|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Mar 24, 2020
checked on Mar 29, 2020
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.