4.6 Article

Assessing Visual Exploratory Activity of Athletes in Virtual Reality Using Head Motion Characteristics

Journal

SENSORS
Volume 21, Issue 11, Pages -

Publisher

MDPI
DOI: 10.3390/s21113728

Keywords

virtual reality; visual exploratory activity; perceptual-cognitive skills; head turn activity

Funding

  1. Bavarian Ministry of Economic Affairs, Regional Development and Energy
  2. German Research Foundation (DFG) [ES 434/8-1]

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Maximizing performance success in sports involves continuous learning and adaptation processes, with the evaluation of visual exploratory activity (VEA) playing a key role. This study introduces a virtual reality-based reproducible assessment method for quantifying athletes' VEA using head movement, improving assessment accuracy and providing insights into perceptual-cognitive processes.
Maximizing performance success in sports is about continuous learning and adaptation processes. Aside from physiological, technical and emotional performance factors, previous research focused on perceptual skills, revealing their importance for decision-making. This includes deriving relevant environmental information as a result of eye, head and body movement interaction. However, to evaluate visual exploratory activity (VEA), generally utilized laboratory settings have restrictions that disregard the representativeness of assessment environments and/or decouple coherent cognitive and motor tasks. In vivo studies, however, are costly and hard to reproduce. Furthermore, the application of elaborate methods like eye tracking are cumbersome to implement and necessitate expert knowledge to interpret results correctly. In this paper, we introduce a virtual reality-based reproducible assessment method allowing the evaluation of VEA. To give insights into perceptual-cognitive processes, an easily interpretable head movement-based metric, quantifying VEA of athletes, is investigated. Our results align with comparable in vivo experiments and consequently extend them by showing the validity of the implemented approach as well as the use of virtual reality to determine characteristics among different skill levels. The findings imply that the developed method could provide accurate assessments while improving the control, validity and interpretability, which in turn informs future research and developments.

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