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From the field of play to the laboratory: Recreating the demands of competition with augmented reality simulated sport
Authors:Kahlee Adams  Adam Kiefer  Derek Panchuk  Adam Hunter  Ryan MacPherson  Wayne Spratford
Institution:1. University of Canberra Research Institute for Sport and Exercise (UCRISE), University of Canberra, Canberra, Australiakahlee.adams@canberra.edu.auORCID Iconhttps://orcid.org/0000-0001-9263-3929;3. Department of Exercise and Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA;4. College of Sport &5. Exercise Science, Victoria University, Melbourne, Australia;6. Movement Science, Australian Institute of Sport, Canberra, Australia;7. Department of Exercise and Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USAORCID Iconhttps://orcid.org/0000-0003-4821-5580;8. University of Canberra Research Institute for Sport and Exercise (UCRISE), University of Canberra, Canberra, Australia;9. Discipline of Sport and Exercise Science, Faculty of Health, University of Canberra, Canberra, AustraliaORCID Iconhttps://orcid.org/0000-0002-6207-8829
Abstract:ABSTRACT

Biomechanical analysis has typically been confined to a laboratory setting. While attempts have been made to take laboratory testing into the field, this study was designed to assess whether augmented reality (AR) could be used to bring the field into the laboratory. This study aimed to measure knee load in volleyball players through a jump task incorporating AR while maintaining the perception-action couplings by replicating the visual features of a volleyball court. Twelve male volleyball athletes completed four tasks: drop landing, hop jump, spike jump, and spike jump while wearing AR smart glasses. Biomechanical variables included patellar tendon force, knee moment and kinematics of the ankle, knee, hip, pelvis and thorax. The drop landing showed differences in patellar tendon force and knee moment when compared to the other conditions. The hop jump did not present differences in kinetics when compared to the spike conditions, instead of displaying the greatest kinematic differences. As a measure of patellar tendon loading the AR condition showed a close approximation to the spike jump, with no differences present when comparing landing forces and mechanics. Thus, AR may be used in a clinical assessment to better replicate information from the competitive environment.
Keywords:Representative Learning Design  Perception-Action Coupling  Motor Control Learning  Knee Loading  Volleyball  Biomechanics
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