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Temporal-spatial gait parameter models of very slow walking

机译:颞空间步态步进参数模型非常缓慢行走

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摘要

This study assessed the relationship between walking speed and common temporal-spatial stride-parameters to determine if a change in gait strategy occurs at extremely slow walking speeds. Stride-parameter models that represent slow walking can act as a reference for lower extremity exoskeleton and powered orthosis controls since these devices typically operate at walking speeds less than 0.4 m/s. Full-body motion capture data were collected from 30 health adults while walking on a self-paced treadmill, within a CAREN-Extended virtual reality environment. Kinematic data were collected for 0.2-0.8 m/s, and self-selected walking speed. Eight temporal stride-parameters were determined and their relationship to walking speed was assessed using linear and quadratic regression. Stride-length, step-length, and step-frequency were linearly related to walking speed, even at speeds below 0.4 m/s. An inflection point at 0.5 m/s was found for stride-time, step-time, stance-time, and double support time. Equations were defined for each stride-parameter, with equation outputs producing correlations greater than 0.91 with the test data. This inflection point suggests a change in gait strategy at very slow walking speeds favouring greater ground contact time.
机译:本研究评估了步行速度和常见时间空间步伐 - 参数之间的关系,以确定步态策略的变化是否发生在极其慢的步行速度。代表慢速行走的跨度参数模型可以作为下肢外骨骼和动力矫形器控制的参考,因为这些装置通常在小于0.4 m / s的步行速度下操作。全身运动捕获数据从30个健康成年人收集,同时在一个自定节奏的跑步机上行走,在康复的虚拟现实环境中。收集运动数据0.2-0.8米/秒,自选择的步行速度。确定八个时间升级参数,并使用线性和二次回归评估它们与步行速度的关系。步幅长度,步长和跨频率与步行速度线性相关,即使在0.4米/秒以下的速度下也是如此。发现了0.5m / s的拐点,用于步进时间,步进时间,姿势时间和双支撑时间。对于每个跨度参数定义了方程,具有在测试数据中产生大于0.91的相关性的等式输出。这种拐点表明步态策略的变化在非常缓慢的行走速度,倾向于更大的地面接触时间。

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