Dynamic stress profile generation for crisis situations training

Luca Pelissero-Witoslawski (1) , Domitile Lourdeaux (1) , Dominique Lenne (1)

1 Heudiasyc - Heuristique et Diagnostic des Systèmes Complexes [Compiègne]

Our work focuses on improving the management of stressful situations using virtual environments. We hypothesise that learners can improve how they deal with these situations by being confronted with a wide variety of scenarios. We want to create customised situations using different stressors, which is why we are interested in the representation and diagnosis of the learner ability to cope with said stressors. The diagnosis of a stress profile is carried out using stress sensors which provide measurements. However, these measurements are not quite spotless and uncertainties are present. Moreover, the situations we generate are complex and involve stressors that can impact each learner differently. Hence, many uncertainties also impact the diagnosis. In order to take these uncertainties into account, we rely on the transferable belief model, and we come up with stressors depicted in the form of a taxonomy that can be configured by the instructor. This will allow them to explore different levels of granularity.

Mots clés: Training; Solid modeling; Uncertainty; Protocols; Taxonomy; Virtual environments; Physiology

Domaines: Intelligence artificielle [cs.AI]

Luca Pelissero-Witoslawski, Domitile Lourdeaux, Dominique Lenne. Dynamic stress profile generation for crisis situations training. IEEE International Conference on Systems, Man, and Cybernetics (SMC 2021), Oct 2021, Melbourne, Australia. pp.1823-1828, ⟨10.1109/smc52423.2021.9659295⟩. ⟨hal-03545192⟩