Machine Learning and Data Analytics Lab, Department of Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Carl-Thiersch-Straße 2b, 91052 Erlangen, Germany.
Adidas AG, Adi-Dassler-Straße 1, 91074 Herzogenaurach, Germany.
Sensors (Basel). 2021 May 27;21(11):3728. doi: 10.3390/s21113728.
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.
在体育运动中,取得优异表现的关键在于持续的学习和适应过程。除了生理、技术和情感表现因素外,先前的研究还关注了感知技能,揭示了它们在决策中的重要性。这包括通过眼睛、头部和身体运动的相互作用来获取相关的环境信息。然而,为了评估视觉探索活动(VEA),通常使用的实验室设置存在限制,这些限制忽略了评估环境的代表性,或者将连贯的认知和运动任务分离开来。然而,体内研究成本高昂且难以复制。此外,像眼动追踪这样复杂方法的应用实施起来很麻烦,并且需要专家知识才能正确解释结果。在本文中,我们引入了一种基于虚拟现实的可重现评估方法,用于评估 VEA。为了深入了解感知认知过程,我们研究了一种基于头部运动的易于解释的度量标准,该标准可以量化运动员的 VEA。我们的结果与类似的体内实验相吻合,因此通过展示所实施方法的有效性以及虚拟现实在确定不同技能水平之间特征方面的应用,对其进行了扩展。研究结果表明,所开发的方法可以提供准确的评估,同时提高控制、有效性和可解释性,从而为未来的研究和发展提供信息。