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Adaptive extraction of emotion-related EEG segments using multidimensional directed information in time-frequency domain

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2 Author(s)
Petrantonakis, P.C. ; Dept. of Electr. & Comput. Eng., Aristotle Univ. of Thessaloniki, Thessaloniki, Greece ; Hadjileontiadis, L.J.

Emotion discrimination from electroencephalogram (EEG) has gained attention the last decade as a user-friendly and effective approach to EEG-based emotion recognition (EEG-ER) systems. Nevertheless, challenging issues regarding the emotion elicitation procedure, especially its effectiveness, raise. In this work, a novel method, which not only evaluates the degree of emotion elicitation but localizes the emotion information in the time-frequency domain, as well, is proposed. The latter, incorporates multidimensional directed information at the time-frequency EEG representation, extracted using empirical mode decomposition, and introduces an asymmetry index for adaptive emotion-related EEG segment selection. Experimental results derived from 16 subjects visually stimulated with pictures from the valence/arousal space drawn from the International Affective Picture System database, justify the effectiveness of the proposed approach and its potential contribution to the enhancement of EEG-ER systems.

Published in:

Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE

Date of Conference:

Aug. 31 2010-Sept. 4 2010