Guignard Brice, Rouard Annie, Chollet Didier, Seifert Ludovic
Centre d'Etudes des Transformations des Activités Physiques et Sportives (CETAPS EA3832), Faculty of Sport Sciences, University of Rouen Normandy, Mont Saint AignanFrance; Laboratoire Interuniversitaire de Biologie de la Motricité (LIBM), Department Sciences and Mountain (SceM), University Savoie Mont Blanc, Le Bourget-du-LacFrance.
Laboratoire Interuniversitaire de Biologie de la Motricité (LIBM), Department Sciences and Mountain (SceM), University Savoie Mont Blanc, Le Bourget-du-Lac France.
Front Psychol. 2017 Mar 14;8:383. doi: 10.3389/fpsyg.2017.00383. eCollection 2017.
Motor control in swimming can be analyzed using low- and high-order parameters of behavior. Low-order parameters generally refer to the superficial aspects of movement (i.e., position, velocity, acceleration), whereas high-order parameters capture the dynamics of movement coordination. To assess human aquatic behavior, both types have usually been investigated with multi-camera systems, as they offer high three-dimensional spatial accuracy. Research in ecological dynamics has shown that movement system variability can be viewed as a functional property of skilled performers, helping them adapt their movements to the surrounding constraints. Yet to determine the variability of swimming behavior, a large number of stroke cycles (i.e., inter-cyclic variability) has to be analyzed, which is impossible with camera-based systems as they simply record behaviors over restricted volumes of water. Inertial measurement units (IMUs) were designed to explore the parameters and variability of coordination dynamics. These light, transportable and easy-to-use devices offer new perspectives for swimming research because they can record low- to high-order behavioral parameters over long periods. We first review how the low-order behavioral parameters (i.e., speed, stroke length, stroke rate) of human aquatic locomotion and their variability can be assessed using IMUs. We then review the way high-order parameters are assessed and the adaptive role of movement and coordination variability in swimming. We give special focus to the circumstances in which determining the variability between stroke cycles provides insight into how behavior oscillates between stable and flexible states to functionally respond to environmental and task constraints. The last section of the review is dedicated to practical recommendations for coaches on using IMUs to monitor swimming performance. We therefore highlight the need for rigor in dealing with these sensors appropriately in water. We explain the fundamental and mandatory steps to follow for accurate results with IMUs, from data acquisition (e.g., waterproofing procedures) to interpretation (e.g., drift correction).
游泳中的运动控制可以通过行为的低阶和高阶参数进行分析。低阶参数通常指运动的表面方面(即位置、速度、加速度),而高阶参数则捕捉运动协调的动态过程。为了评估人类的水上行为,这两种类型的参数通常都使用多摄像头系统进行研究,因为它们具有较高的三维空间精度。生态动力学研究表明,运动系统的变异性可以被视为熟练执行者的一种功能特性,有助于他们使运动适应周围的限制条件。然而,要确定游泳行为的变异性,必须分析大量的划水周期(即周期间变异性),而基于摄像头的系统无法做到这一点,因为它们只是在有限的水体中记录行为。惯性测量单元(IMU)旨在探索协调动力学的参数和变异性。这些轻便、可携带且易于使用的设备为游泳研究提供了新的视角,因为它们可以长时间记录低阶到高阶的行为参数。我们首先回顾如何使用IMU评估人类水上运动的低阶行为参数(即速度、划水长度、划水频率)及其变异性。然后,我们回顾评估高阶参数的方法以及运动和协调变异性在游泳中的适应性作用。我们特别关注确定划水周期之间变异性的情况,这有助于深入了解行为如何在稳定和灵活状态之间振荡,以功能性地响应环境和任务限制。综述的最后一部分为教练提供了关于使用IMU监测游泳表现的实用建议。因此,我们强调在水中正确使用这些传感器时需要严谨。我们解释了使用IMU获得准确结果必须遵循的基本且必要的步骤,从数据采集(如防水程序)到解释(如漂移校正)。