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Steering a wheelchair by thought

Lakany, H. and , Lakany, H. (2005) Steering a wheelchair by thought. The IEE International Workshop on Intelligent Environments. pp. 199-202. ISSN 0537-9989

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Abstract

In this paper, we report on preliminary results of research whose aim is to classify EEG signals recorded from a subject whilst controlling a joystick and moving it io different directions. We develop a method 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 inputs to a neural network based classifier. The classification results show that we are able to discriminate between different directions using the selected features. This shows that this approach could be potentially useful in building braincomputer interfaces (BCIs) where a paralysed person could communicate with a wheelchair and steer it to the desired direction using only EEG signals.

Item type: Article
ID code: 8269
Keywords: EEG signals, salient spatio-temporal features, continuous wavelet transform, neural network based classifier, braincomputer, Bioengineering, Medicine (General)
Subjects: Technology > Engineering (General). Civil engineering (General) > Bioengineering
Medicine > Medicine (General)
Department: Faculty of Engineering > Bioengineering
Related URLs:
Depositing user: Strathprints Administrator
Date Deposited: 04 Sep 2009 14:23
Last modified: 04 Oct 2012 12:32
URI: http://strathprints.strath.ac.uk/id/eprint/8269

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