Phase determination during normal running using kinematic data
Phase determination during normal running using kinematic data
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DOI：
10.1007/bf02345744
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发表时间：
2000-09-01
影响因子：
3.2
通讯作者：
Stergiou, N
中科院分区：
文献类型：
--
作者：
Hreljac, A;Stergiou, N
算法来预测heelstrike和脚趾离地时间在正常运行的主题选定的速度，只使用运动学数据，提出。为了评估这些算法的准确性，将结果与来自各进行十次试验的十名受试者的同步力平台记录进行比较。使用单个180 Hz摄像机，定位在矢状面，预测脚跟着地时间的平均RMS误差为4.5 ms，而预测脚趾离地时间的平均RMS误差为6.9 ms。脚跟着地的平均真误差（早期预测为负）为+2.4 ms，脚趾离地为+2.8 ms，表明未发生系统误差。预测接触时间的平均RMS误差为7.5 ms，预测接触时间的平均真实误差为0.5 ms。使用这些简单的算法的事件时间的估计与其他需要专门设备的技术相比毫不逊色。它的结论是，所提出的算法提供了一个简单而可靠的方法，确定事件的时间在正常运行的主题选定的步伐，只使用运动学数据，可以实现与任何运动学数据收集系统。
Algorithms to predict heelstrike and toe-off times during normal running at subject-selected speeds, using only kinematic data, are presented. To assess the accuracy of these algorithms, results are compared with synchronised force platform recordings from ten subjects performing ten trials each. Using a single 180 Hz camera, positioned in the sagittal plane, the average RMS error in predicting heelstrike times is 4.5 ms, whereas the average RMS error in predicting toe-off times is 6.9 ms. Average true errors (negative for an early prediction) are +2.4 ms for heelstrike and +2.8 ms for toe-off, indicating that systematic errors have not occured. The average RMS error in predicting contact time is 7.5 ms, and the average true error in predicting contact time is 0.5 ms. Estimations of event times using these simple algorithms compare favourably with other techniques requiring specialised equipment. It is concluded that the proposed algorithms provide an easy and reliable method of determining event times during normal running at a subject selected pace using only kinematic data and can be implemented with any kinematic data-collection system.