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- Muñoz, John E., et al.
(författare)
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A Psychophysiological Model of Firearms Training in Police Officers : A Virtual Reality Experiment for Biocybernetic Adaptation
- 2020
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Ingår i: Frontiers in Psychology. - : Frontiers Media SA. - 1664-1078. ; 11
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Tidskriftsartikel (refereegranskat)abstract
- Crucial elements for police firearms training include mastering very specific psychophysiological responses associated with controlled breathing while shooting. Under high-stress situations, the shooter is affected by responses of the sympathetic nervous system that can impact respiration. This research focuses on how frontal oscillatory brainwaves and cardiovascular responses of trained police officers (N = 10) are affected during a virtual reality (VR) firearms training routine. We present data from an experimental study wherein shooters were interacting in a VR-based training simulator designed to elicit psychophysiological changes under easy, moderate and frustrating difficulties. Outcome measures in this experiment include electroencephalographic and heart rate variability (HRV) parameters, as well as performance metrics from the VR simulator. Results revealed that specific frontal areas of the brain elicited different responses during resting states when compared with active shooting in the VR simulator. Moreover, sympathetic signatures were found in the HRV parameters (both time and frequency) reflecting similar differences. Based on the experimental findings, we propose a psychophysiological model to aid the design of a biocybernetic adaptation layer that creates real-time modulations in simulation difficulty based on targeted physiological responses.
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- Muñoz, John E., et al.
(författare)
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Taxonomy of Physiologically Adaptive Systems and Design Framework
- 2021
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Ingår i: International Conference on Human-Computer Interaction. - Cham : Springer Publishing Company. - 9783030778576 - 9783030778569 ; , s. 559-576
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Konferensbidrag (refereegranskat)abstract
- The design of physiologically adaptive systems entails several complex steps from acquiring human body signals to create responsive adaptive behaviors that can be used to enhance conventional communication pathways between human and technological systems. Categorizing and classifying the computing techniques used to create intelligent adaptation via physiological metrics is an important step towards creating a body of knowledge that allows the field to develop and mature accordingly. This paper proposes the creation of a taxonomy that groups several physiologically adaptive (also called biocybernetic) systems that have been previously designed and reported. The taxonomy proposes two subcategories of adaptive techniques: control theoretics and machine learning, which have multiple sub-categories that we illustrate with systems created in the last decades. Based on the proposed taxonomy, we also propose a design framework that considers four fundamental aspects that should be defined when designing physiologically adaptive systems: the medium, the application area, the psychophysiological target state, and the adaptation technique. We conclude the paper by discussing the importance of the proposed taxonomy and design framework as well as suggesting research areas and applications where we envision biocybernetic systems will evolve in the following years.
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