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We present a preliminary quantitative study aimed at developing an optimal standard protocol for automatic classification of specific affective states as related to human- computer interactions. This goal is mainly achieved by comparing standard psychological test-reports to quantitative measures derived from simultaneous non-invasive acquisition of psychophysiological signals of interest, namely...
The long term goal of our research is to develop a tool for recognizing human emotions during e-learning processes. This could be accomplished by combining quantitative indexes extracted from non-invasive recordings of four physiological signals: namely skin conductance, blood volume pulse, electrocardiogram and electroencephalogram. Wearable, non-invasive sensors, communicating with a PC, were applied...
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