Design and Validation of a Mental and Social Stress Induction Protocol Towards Load-Invariant Physiology-Based Detection

Camille Jeunet 1 Christian Mühl 1 Fabien Lotte 1, 2
1 Potioc - Popular interaction with 3d content
LaBRI - Laboratoire Bordelais de Recherche en Informatique, Inria Bordeaux - Sud-Ouest
Abstract : Stress is a major societal issue with negative impacts on health and economy. Physiological computing offers a continuous, direct, and unobtrusive method for stress level assessment and computer-assisted stress management. However, stress is a complex construct and its physiology can vary depending on its source: cognitive workload or social evaluation. To study the feasibility of physiology-based load-invariant psychosocial stress-detection, we designed a stress-induction protocol able to independently vary the relevant types of psychophysiological activity: mental and psychosocial stress. Here, we validate the efficacy of our protocol to induce psychosocial and mental stress. Our participants (N=24) had to perform a cognitive task associated with two workload conditions (low/high mental stress), in two contexts (low/high psychosocial stress), during which we recorded subjects' self-reports, behaviour, physiology and neurophysiology. Questionnaires showed that the subjectively perceived level of stress varied with the psychosocial stress induction, while perceived arousal and mental effort levels vary with mental stress induction. Behaviour and physiology further corroborated the validity of our protocol. Heart rate and skin conductance globally increased after psychosocial stress induction relative to the non-stressful condition. Moreover, we demonstrated that higher workload tasks (mental stress) led to decrease in performance and a marked increase of heart rate.
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Communication dans un congrès
International Conference on Physiological Computing Systems, Jan 2014, Lisbonne, Portugal. 2014
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Camille Jeunet, Christian Mühl, Fabien Lotte. Design and Validation of a Mental and Social Stress Induction Protocol Towards Load-Invariant Physiology-Based Detection. International Conference on Physiological Computing Systems, Jan 2014, Lisbonne, Portugal. 2014. 〈hal-00879966〉

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