NDLI: Combination of amplitude and phase features under a uniform framework with EMD in EEG-based Brain-Computer Interface

Content Provider	IEEE Xplore Digital Library
Author	Wei He Pengfei Wei Yi Zhou Liping Wang
Copyright Year	2012
Description	Author affiliation: Shenzhen Key Lab. of Neuropsychiatric Modulation, Shenzhen Inst. of Adv. Technol., Shenzhen, China (Wei He; Pengfei Wei; Yi Zhou; Liping Wang)
Abstract	In a Brain-Computer Interface (BCI) system, the variations of the amplitude and the phase in EEG signal convey subjects' movement intention and underpin the differentiation of the various mental tasks. Combining these two kinds of information under a uniform feature extraction framework can better reflect the brain states and potentially contribute to BCI classification. Here the Common Spatial Pattern (CSP) and the Phase Locking Value (PLV) were used to capture the amplitude and the phase information. To integrate these two feature extraction procedures, the Empirical Mode Decomposition (EMD) is introduced in preprocessing which behaved as filter bank to optimize bands selection automatically for CSP and exactly calculate the instantaneous phase for PLV. The most discriminative features were selected from the feature pool by the sequential floating forward feature selection method (SFFS). The proposed method was applied to both public and recorded datasets (each n=4). Compared with the traditional CSP, the average increment of classification accuracy is 5.4% (2.0% for public and 8.7% for recorded datasets), which both manifests statistically significances (p<;0.05). Moreover, we preliminarily investigate the possibility of the online realization of this method and it shows a comparable result with the offline result.
Sponsorship	IEEE Eng. Medicine Biol. Soc.
Starting Page	1687
Ending Page	1690
File Size	965727
Page Count	4
File Format	PDF
ISBN	9781424441198
ISSN	1557170X
e-ISBN	9781457717871
DOI	10.1109/EMBC.2012.6346272
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electroencephalography Feature extraction Accuracy Electrodes Filter banks
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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