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Rider motion identification during normal bicycling by means of principal component analysis

机译:通过主成分分析识别正常骑行过程中的车手运动

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摘要

Recent observations of a bicyclist riding through town and on a treadmill show that the rider uses the upper body very little when performing normal maneuvers and that the bicyclist may, in fact, primarily use steering input for control. The observations also revealed that other motions such as lateral movement of the knees were used in low speed stabilization. In order to validate the hypothesis that there is little upper body motion during casual cycling, an in-depth motion capture analysis was performed on the bicycle and rider system. We used motion capture technology to record the motion of three similar young adult male riders riding two different city bicycles on a treadmill. Each rider rode each bicycle while performing stability trials at speeds ranging from 2 km/h to 30 km/h: stabilizing while pedaling normally, stabilizing without pedaling, line tracking while pedaling, and stabilizing with no-hands. These tasks were chosen with the intent of examining differences in the kinematics at various speeds, the effects of pedaling on the system, upper body control motions and the differences in tracking and stabilization. Principal component analysis was used to transform the data into a manageable set organized by the variance associated with the principal components. In this paper, these principal components were used to characterize various distinct kinematic motions that occur during stabilization with and without pedaling. These motions were grouped on the basis of correlation and conclusions were drawn about which motions are candidates for stabilization-related control actions.
机译:最近对骑自行车的人穿过城镇和跑步机骑行的观察表明,骑手在进行常规操作时几乎不使用上身,而骑自行车的人实际上可能主要使用转向输入进行控制。观察结果还表明,其他运动(如膝盖的横向运动)用于低速稳定。为了验证在休闲骑行期间上半身运动很少的假设,对自行车和骑手系统进行了深入的运动捕捉分析。我们使用运动捕捉技术记录了三个相似的年轻成年男性骑手在跑步机上骑着两个不同的城市自行车的运动。在以2 km / h至30 km / h的速度进行稳定性试验时,每个骑手都骑着每辆自行车:正常踩踏板时稳定,不踩踏板时稳定,踩踏板时线跟踪和不用手时稳定。选择这些任务的目的是检查各种速度下的运动学差异,踏板对系统的影响,上身控制动作以及跟踪和稳定方面的差异。主成分分析用于将数据转换为由与主成分相关的方差组织的可管理集合。在本文中,这些主要组成部分用于表征在稳定状态下有无踏板运动时发生的各种运动运动。这些运动是根据相关性进行分组的,并得出结论,哪些运动是稳定相关控制动作的候选者。

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