Feature Extraction on Brain Computer Interfaces using Discrete Dyadic Wavelet Transform: Preliminary Results

The purpose of this work is to evaluate different feature extraction alternatives to detect the event related evoked potential signal on brain computer interfaces, trying to minimize the time employed and the classification error, in terms of sensibility and specificity of the method, looking for al...

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Bibliographic Details
Published in:Journal of physics. Conference series 2011-01, Vol.313 (1), p.012011-7
Main Authors: Gareis, I, Gentiletti, G, Acevedo, R, Rufiner, L
Format: Article
Language:English
Subjects:
Classification
Dyadics
Feature extraction
Human-computer interface
Mathematical analysis
Physics
Sensitivity
Wavelet
Wavelet transforms
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Summary:The purpose of this work is to evaluate different feature extraction alternatives to detect the event related evoked potential signal on brain computer interfaces, trying to minimize the time employed and the classification error, in terms of sensibility and specificity of the method, looking for alternatives to coherent averaging. In this context the results obtained performing the feature extraction using discrete dyadic wavelet transform using different mother wavelets are presented. For the classification a single layer perception was used. The results obtained with and without the wavelet decomposition were compared; showing an improvement on the classification rate, the specificity and the sensibility for the feature vectors obtained using some mother wavelets.
ISSN:1742-6596
1742-6588
1742-6596
DOI:10.1088/1742-6596/313/1/012011