Why the study?
Do specific psychophysiological signals correlate with distinct affective states (relaxation, engagement, stress) in healthy students?
Do specific psychophysiological signals correlate with distinct affective states (relaxation, engagement, stress) in healthy students?
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Quantitative measures from non-invasive physiological sensors may help characterize specific affective states during human-computer interactions.
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 respiration, galvanic skin response, blood volume pulse, electrocardiogram and electroencephalogram. Forty-three healthy students were exposed to computer-mediated stimuli, while wearable non-invasive sensors were applied in order to collect the physiological data. The stimuli were designed to elicit three distinct affective states: relaxation, engagement and stress. In this work we report how our quantitative analysis has helped in redefining important aspects of the protocol, and we show preliminary findings related to the specific psychophysiological patterns correlating with the three target affective states. Results further suggest that some of the quantitative measures might be useful in characterizing specific affective states.
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Mauri et al. (2010) studied this question.
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