Firefighter virtual reality simulation for personalized stress detection

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Abstract

Classifying stress in firefighters poses challenges, such as accurate personalized labeling, unobtrusive recording, and training of adequate models. Acquisition of labeled data and verification in cage mazes or during hot trainings is time consuming. Virtual Reality (VR) and Internet of Things (IoT) wearables provide new opportunities to create better stressors for firefighter missions through an immersive simulation. In this demo, we present a VR-based setup that enables to simulate firefighter missions to trigger and more easily record specific stress levels. The goal is to create labeled datasets for personalized multilevel stress detection models that include multiple biosignals, such as heart rate variability from electrocardiographic RR intervals. The multi-level stress setups can be configured, consisting of different levels of mental stressors. The demo shows how we established the recording of a baseline and virtual missions with varying challenge levels to create a personalized stress calibration.

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Klingner, S., Han, Z., Liu, Y., Fan, F., Altakrouri, B., Michel, B., … Chau, S. M. (2020). Firefighter virtual reality simulation for personalized stress detection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12325 LNAI, pp. 343–347). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-58285-2_32

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