Picture of virus under microscope

Research under the microscope...

The Strathprints institutional repository is a digital archive of University of Strathclyde research outputs.

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.

Explore SIPBS research

1st order class separability using EEG-based features for classification of wrist movements with direction selectivity

Meckes, M.P. and Sepulveda, F. and Conway, B.A. (2004) 1st order class separability using EEG-based features for classification of wrist movements with direction selectivity. Engineering in Medicine and Biology Society, 2004. 26th Annual International Conference of the IEEE . IEEE. ISBN 0-7803-8439-3

Full text not available in this repository.

Abstract

28 channel EEG data were recorded while a subject performed wrist movements in four directions. Four feature types were extracted for each channel following optimized filtering of the signals. The potential performance of each feature and channel for use in the classification of the EEG signals was analyzed by estimating the relative class overlap using a first order histogram approach. The best feature/channel configurations contained channels both that were close and far from motor areas. While the scope and depth of the study was very limited, the results do suggest more attention should be paid to non-motor areas when investigating movement related EEG.