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A Performance Analysis of a Wireless Body-Area Network Monitoring System for Professional Cycling

机译:专业自行车无线体域网监控系统的性能分析

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摘要

It is essential for any highly trained cyclist to optimize his pedalling movement in order to maximize the performance and minimize the risk of injuries. Current techniques rely on bicycle fitting and off-line laboratory measurements. These techniques do not allow the assessment of the kinematics of the cyclist during training and competition, when fatigue may alter the ability of the cyclist to apply forces to the pedals and thus induce maladaptive joint loading. We propose a radically different approach that focuses on determining the actual status of the cyclist's lower limb segments in real-time and real-life conditions. Our solution is based on body area wireless motion sensor nodes that can collaboratively process the sensory information and provide the cyclists with immediate feedback about their pedalling movement. In this paper, we present a thorough study of the accuracy of our system with respect to the gold standard motion capture system. We measure the knee and ankle angles, which influence the performance as well as the risk of overuse injuries during cycling. The results obtained from a series of experiments with nine subjects show that the motion sensors are within 2.2° to 6.4° from the reference given by the motion capture system, with a correlation coefficient above 0.9. The wireless characteristics of our system, the energy expenditure, possible improvements and usability aspects are further analysed and discussed.
机译:对于任何训练有素的骑自行车者来说,最重要的是要优化其蹬踏运动,以最大化性能并最大程度地减少受伤的风险。当前的技术依赖于自行车装配和离线实验室测量。这些技术不允许在训练和比赛期间评估骑车人的运动学,此时疲劳可能会改变骑车人向踏板施加力的能力,从而导致关节适应不良。我们提出了一种截然不同的方法,该方法着眼于在实时和现实情况下确定骑车人下肢的实际状态。我们的解决方案基于人体区域无线运动传感器节点,该节点可以协同处理感官信息,并为骑车人提供有关其踏板运动的即时反馈。在本文中,我们针对金标准运动捕获系统对系统的准确性进行了全面的研究。我们测量膝盖和脚踝的角度,这些角度会影响性能以及骑车过程中过度使用受伤的风险。通过对九个对象的一系列实验获得的结果表明,运动传感器与运动捕获系统给出的参考之间的距离在2.2°至6.4°之内,相关系数高于0.9。我们的系统的无线特性,能耗,可能的改进和可用性方面都将得到进一步分析和讨论。

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