Visscher Rosa M S, Freslier Marie, Moissenet Florent, Sansgiri Sailee, Singh Navrag B, Viehweger Elke, Taylor William R, Brunner Reinald
Laboratory for Movement Biomechanics, Department of Health Science and Technology, Institute for Biomechanics, ETH Zürich, Zurich, Switzerland.
Biomechanics of Movement Group, Department of Biomedical Engineering, University of Basel, Basel, Switzerland.
Front Hum Neurosci. 2021 Sep 13;15:720699. doi: 10.3389/fnhum.2021.720699. eCollection 2021.
For interpreting outcomes of clinical gait analysis, an accurate estimation of gait events, such as initial contact (IC) and toe-off (TO), is essential. Numerous algorithms to automatically identify timing of gait events have been developed based on various marker set configurations as input. However, a systematic overview of the effect of the marker selection on the accuracy of estimating gait event timing is lacking. Therefore, we aim to evaluate (1) if the marker selection influences the accuracy of kinematic algorithms for estimating gait event timings and (2) what the best marker location is to ensure the highest event timing accuracy across various gait patterns. 104 individuals with cerebral palsy (16.0 ± 8.6 years) and 31 typically developing controls (age 20.6 ± 7.8) performed clinical gait analysis, and were divided into two out of eight groups based on the orientation of their foot, in sagittal and frontal plane at mid-stance. 3D marker trajectories of 11 foot/ankle markers were used to estimate the gait event timings (IC, TO) using five commonly used kinematic algorithms. Heatmaps, for IC and TO timing per group were created showing the median detection error, compared to detection using vertical ground reaction forces, for each marker. Our findings indicate that median detection errors can be kept within 7 ms for IC and 13 ms for TO when optimizing the choice of marker and detection algorithm toward foot orientation in midstance. Our results highlight that the use of markers located on the midfoot is robust for detecting gait events across different gait patterns.
为了解释临床步态分析的结果，准确估计步态事件，如初始接触（IC）和足趾离地（TO）至关重要。基于各种标记集配置作为输入，已经开发了许多自动识别步态事件时间的算法。然而，缺乏对标记选择对步态事件时间估计准确性影响的系统概述。因此，我们旨在评估：（1）标记选择是否会影响用于估计步态事件时间的运动学算法的准确性；（2）在各种步态模式下，确保最高事件时间准确性的最佳标记位置是什么。104名脑瘫患者（16.0±8.6岁）和31名发育正常的对照者（年龄20.6±7.8岁）进行了临床步态分析，并根据他们在站立中期矢状面和额状面的足部方向，被分为八组中的两组。使用11个足/踝标记的三维标记轨迹，通过五种常用的运动学算法来估计步态事件时间（IC、TO）。针对每组的IC和TO时间创建了热图，显示了与使用垂直地面反作用力进行检测相比，每个标记的中位检测误差。我们的研究结果表明，当根据站立中期的足部方向优化标记选择和检测算法时，IC的中位检测误差可保持在7毫秒以内，TO的中位检测误差可保持在13毫秒以内。我们的结果强调，使用位于中足的标记对于检测不同步态模式下的步态事件具有鲁棒性。
