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Strathprints serves world leading Open Access research by the University of Strathclyde, including research by the Strathclyde Institute of Pharmacy and Biomedical Sciences (SIPBS), where research centres such as the Industrial Biotechnology Innovation Centre (IBioIC), the Cancer Research UK Formulation Unit, SeaBioTech and the Centre for Biophotonics are based.

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Comparing EEG patterns of actual and imaginary wrist movements - a machine learning approach

Lakany, H. and Conway, B.A. (2005) Comparing EEG patterns of actual and imaginary wrist movements - a machine learning approach. Proceedings of the first ICGST International Conference on Artificial Intelligence and Machine Learning AIML 05 . ICGST. ISBN 21968/2005

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Abstract

Our goal is to develop an algorithm for feature extraction and classification to be used in building brain-computer interfaces. In this paper, we present preliminary results for classifying EEG data of imaginary wrist movements. We have developed an algorithm based on the spatio-temporal features of the recorded EEG signals. We discuss the differences between the feature vectors selected for both actual and imaginary wrist movements and compare classification results.