Title: Imagined wrist movement classification in single trial EEG for brain computer interface using wavelet packet

Authors: Yusuf U. Khan

Addresses: Department of Computing and Electronic Systems, MIEEE, FIETE, University of Essex, UK

Abstract: In kinaesthetic imagery, healthy subjects simulate the disability of muscle inactivity by imagining movements. EEG recordings from five healthy subjects were studied to classify the imagined left and right wrist movements performed in four directions (extension, pronation, flexion and supination). Wavelet Packet Transform (WPT) was used to extract features based on normalised energy and average amplitude for the best basis (selected by using local discriminant method). Radial Basis Function classifier was used and a four-fold cross validation was performed. The overall classification accuracy of 83% was achieved by using a vector set comprising of 10 best discriminatory features.

Keywords: WPT; wavelet packet transforms; best basis; EEG; wrist movement; kinaesthetic imagery; muscle disability; muscle inactivity; imagined movements; RBF network classifier; electroencephalography; extension; pronation; flexion; supination; feature extraction; radial basis function; neural networks.

DOI: 10.1504/IJBET.2010.034522

International Journal of Biomedical Engineering and Technology, 2010 Vol.4 No.2, pp.169 - 180

Published online: 07 Aug 2010 *

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