Physiological measures of arousal during soldier- relevant tasks performed in a simulated environment

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Abstract

Deployed United States Army Soldiers operate in dynamic situations, yet there is little known about how to most effectively train Soldier combat skills in a stress-inducing environment prior to deployment. In order to best simulate the experiences of Soldiers in theater, a training environment must be immersive, creating the illusion of “being there, ” thus providing a heightened level of arousal and encouraging the desire to perform well within the training. A 300-degree immersive simulator was used to examine the potential effectiveness of such a training environment. Participants performed a Shoot-Don’t-Shoot task with two types of performance feedback, shock and lifebar loss Levels of arousal were continuously measured through heart rate variability (HRV); psychophysiological measures have been linked to psychological stress and cognitive function. HRV was measured through interbeat interval (IBI), or the peak-to-peak interval of heartbeats, which is linked to cognitive arousal. Higher levels of arousal were seen in the Shock condition compared to the Life Bar condition. IBI was additionally examined in a Baseline session as well as Post-Shock and Post-Life Bar sessions, and results showed that IBI returned to near Baseline levels after both conditions, indicating a recovery from arousal induced during the scenarios. These results show the value of objectively measuring physiology to assess heightened arousal during Soldier-relevant tasks in a simulated environment. Examining the extent to which Soldiers experience arousal, which can often be a proxy for stress, can indicate how immersive or stressful an environment is, and therefore its potential effectiveness as a realistic pre-deployment training environment.

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Patton, D., & Gamble, K. (2016). Physiological measures of arousal during soldier- relevant tasks performed in a simulated environment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9743, pp. 372–382). Springer Verlag. https://doi.org/10.1007/978-3-319-39955-3_35

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