부산대학교 도서관

Quite a few physiological measures have been shown to correlate with psychological stress, and used to design some stress detection algorithms. As most of them are also known to react to non-affective mental states as well, physiology-driven stress models based on these features may lack from specificity. This article tackles this issue by looking for physiological features that are both responsive to affective stress load and minimally sensitive to cognitive activity. A laboratory experiment was designed in such a way that activity-related variations in physiological measures can be isolated during exposure to common tasks. A pressure component was defined and extracted from our data. Its relevance as a predictor of features' ability to distinguish between the stressful and control conditions was shown from descriptive statistics. A feature selection procedure was applied on usual heart rate, heart rate variability and skin conductance-based features, to identify the most pressure-specific ones in a between-subjects perspective. Finally, a simple model built from the selected features succeeded in detecting 87.5% of stress examples among instances of stressless task performance.