Adaptive Emotional Information Retrieval From EEG Signals in the Time-Frequency Domain

作者：Petrantonakis Panagiotis C^*; Hadjileontiadis Leontios J

来源：IEEE Transactions on Signal Processing, 2012, 60(5): 2604-2616.

DOI：10.1109/TSP.2012.2187647

• Electroencephalogram (EEG)
• emotion recognition (ER)
• empirical mode decomposition
• frontal brain asymmetry
• multidimensional directed information

This paper aims at developing adaptive methods for electroencephalogram (EEG) signal segmentation in the time-frequency domain, in order to effectively retrieve the emotion-related information within the EEG recordings. Using the multidimensional directed information analysis supported by the frontal brain asymmetry in the case of emotional reaction, a criterion, namely asymmetry index (AsI), is used to realize the proposed segmentation processes that take into account both the time and frequency (in the empirical mode decomposition domain) emotionally related EEG components. The efficiency of the AsI-based %26quot;emotional%26quot; filters was justified through an extensive classification process, using higher-order crossings and cross-correlation as feature-vector extraction techniques and a support vector machine classifier for six different classification scenarios in the valence/arousal space. This resulted in mean classification rates from 64.17% up to 82.91% in a user-independent base, revealing the potential of establishing such a filtering for reliable EEG-based emotion recognition systems.

• 出版日期2012-5