Assessing visual exploratory activity of athletes in virtual reality using head motion characteristics

Wirth M, Kohl S, Gradl S, Farlock R, Roth D, Eskofier B (2021)

Publication Type: Journal article

Publication year: 2021

Journal

Sensors MDPI

Book Volume: 21

Article Number: 3728

Journal Issue: 11

DOI: 10.3390/s21113728

Abstract

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 deriv-ing 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 con-sequently 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.

Authors with CRIS profile

Markus Wirth Lehrstuhl für Informatik 14 (Machine Learning and Data Analytics) Sebastian Kohl Lehrstuhl für Informatik 14 (Machine Learning and Data Analytics) Stefan Gradl-Trautvetter Lehrstuhl für Informatik 14 (Machine Learning and Data Analytics) Daniel Roth Juniorprofessur für Human-Centered Computing and Extended Reality Björn Eskofier Machine Learning and Data Analytics Lab

Involved external institutions

Adidas AG DE Germany (DE)

How to cite

APA:

Wirth, M., Kohl, S., Gradl, S., Farlock, R., Roth, D., & Eskofier, B. (2021). Assessing visual exploratory activity of athletes in virtual reality using head motion characteristics. Sensors, 21(11). https://dx.doi.org/10.3390/s21113728

MLA:

Wirth, Markus, et al. "Assessing visual exploratory activity of athletes in virtual reality using head motion characteristics." Sensors 21.11 (2021).

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