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Proceedings Paper

Wavelet domain analysis of EEG data for emotion recognition: evaluation of recoursing energy efficiency
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Paper Abstract

In this paper, we evaluate the feature extraction technique of Recoursing Energy Efficiency on electroencephalograph data for human emotion recognition. A protocol has been established to elicit five distinct emotions (joy, sadness, disgust, fear, surprise, and neutral). EEG signals are collected using a 256-channel system, preprocessed using band-pass filters and Laplacian Montage, and decomposed into five frequency bands using Discrete Wavelet Transform. The Recoursing Energy Efficiency (REE) is calculated and applied to a Multi-Layer Perceptron network for classification. We compare the performance of REE features with conventional energy based features.

Paper Details

Date Published: 3 June 2011
PDF: 8 pages
Proc. SPIE 8058, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering IX, 805818 (3 June 2011); doi: 10.1117/12.884074
Show Author Affiliations
Theus H. Aspiras, Univ. of Dayton (United States)
Vijayan K. Asari, Univ. of Dayton (United States)


Published in SPIE Proceedings Vol. 8058:
Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering IX
Harold Szu, Editor(s)

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