Cognitive Load Quantified via Functional Near Infrared Spectroscopy During Immersive Training with VR Based Basic Life Support Learning Modules in Hostile Environment

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Abstract

This study investigates the use of functional near infrared spectroscopy (fNIRS) as a tool for assessing cognitive workload in virtual reality (VR) based medical education. Specifically, the study explores the effect of simulator immersion and distraction on cognitive workload during a Basic Life Support (BLS) training course delivered by a VR-based serious gaming module. Nineteen participants with no prior knowledge of BLS guidelines completed a VR-based serious gaming BLS training module and were randomly assigned to two groups for the BLS examination; the first group had experienced medium distraction while the second group had a high level of distraction. All participants then took a hands-on BLS exam at the end of the study protocol. The results show significant decrease in cognitive workload measured by fNIRS during the training sessions. The oxygenation levels at the prefrontal cortex were significantly higher for the participants who had taken the high distraction VR-exam, suggesting a higher neural involvement compared to the group who had taken the medium distraction VR-exam. However, unlike hands-on exam, no significant difference between two groups was determined for the VR-based exam. The results demonstrate that fNIRS can be used to measure cognitive workload in VR-based medical training and provide further insights for optimizing serious game-based learning tools.

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APA

Polat, M. D., Izzetoglu, K., Aksoy, M. E., Kitapcioglu, D., Usseli, T., & Yoner, S. I. (2023). Cognitive Load Quantified via Functional Near Infrared Spectroscopy During Immersive Training with VR Based Basic Life Support Learning Modules in Hostile Environment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 14019 LNAI, pp. 359–372). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-35017-7_23

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