Classify event-related motor potentials of cued motor actions

Authors:
Somnuk Phon-Amnuaisuk
Affiliations:
Special Interest Group, Perception and Simulation of Intelligent Behaviours, Faculty of Information Technology, Multimedia University, Cyberjaya, Selangor Darul Ehsan, Malaysia
Venue:
ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
Year:
2008

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A time-frequency approach to feature extraction for a brain-computer interface with a comparative analysis of performance measures

EURASIP Journal on Applied Signal Processing

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Abstract

Motor related potentials are generated when an individual is engaged in a task involving motor actions. The transient post-synaptical potential could be observed from the recorded electroencephalogram (EEG) signal. Properties derived from time domain and frequency domain such as event-related motor potential and suppression in band power could be useful EEG features. In this report, lateralised motor potential (LMP) and band power ratio (BPR) are used to classify cued left-fingers and right-fingers movements. Two classifiers are employed in this experiment: minimum distance classifier (MDC) and normal density Bayes classifier (NDBC). The results show that the features from LMP has more discriminative power than band power ratio. They also show that NDBC has a perfect performance in this task.