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Classification of wrist movements using EEG-based wavelets features

Lakany, H. and Conway, B.A. (2006) Classification of wrist movements using EEG-based wavelets features. 27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005 . IEEE, Shanghai, China, pp. 5404-5407. ISBN 0-7803-8741-4

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Abstract

Our aim is to assess and evaluate signal processing and classification methods for extracting features from EEG signals that are useful in developing brain-computer interfaces. In this paper, we report on results of developing a method to classify wrist movements using EEG signals recorded from a subject whilst controlling a joystick and moving it in different directions. Such method could be potentially useful in building brain-computer interfaces (BCIs) where a paralysed person could communicate with a wheelchair and steer it to the desired direction using only EEG signals. Our method is based on extracting salient spatio-temporal features from the EEG signals using continuous wavelet transform. We perform principal component analysis on these features as means to assess their usefulness for classification and to reduce the dimensionality of the problem. We use the results from the PCA as means to represent the different directions. We use a simple technique based on Euclidean distance to classify the data. The classification results show that we are able to discriminate between different directions using the selected features.

Item type: Book
ID code: 8374
Keywords: biomechanics, electroencephalography, feature extraction, handicapped aids, medical signal processing, principal component analysis, signal classification, spatiotemporal phenomena, wavelet transforms, Bioengineering
Subjects: Technology > Engineering (General). Civil engineering (General) > Bioengineering
Department: Faculty of Engineering > Bioengineering
Related URLs:
    Depositing user: Strathprints Administrator
    Date Deposited: 03 Sep 2009 14:59
    Last modified: 04 Oct 2012 16:47
    URI: http://strathprints.strath.ac.uk/id/eprint/8374

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