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A two-dimensional clinical gait analysis protocol based on markerless recordings from a single RGB-Depth camera

机译:基于单个RGB深度相机的无标记记录的二维临床步态分析协议

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This work presents a two-dimensional markerless clinical gait analysis protocol to estimate the sagittal lower limb joint kinematics from the markerless recordings of a single RGB-Depth camera. The proposed method includes a subject separation from the background, the definition of a multi-segmental model of the lower limb and the estimation of the relevant joint kinematics. The segmentation algorithm performance was assessed by measuring the similarity between the computer-obtained segmentations and manual tracings (ground-truth). The estimated joint angles were compared to those obtained using a reference optoelectronic marker-based clinical protocol. The offset between the mean waveforms and the RMS value of the waveforms difference after removing their offset were computed. The segmentation accuracy resulted to be higher than 0.92 and very repeatable (STD of JI about 0.01). The RMSD values of the ankle kinematics (3.4° on average) are lower than those of other joints (4.9° for the hip joint and 6.2° for the knee joint, on average). Overall, given the good agreement between our results and those of marker-based method, we propose to use it to develop a new generation of low-cost movement analysis systems.
机译:这项工作提出了一个二维无标记临床步态分析协议,以从单个RGB深度相机的无标记记录中估计矢状下肢关节运动学。所提出的方法包括主题与背景的分离,下肢的多段模型的定义以及相关关节运动学的估计。分割算法的性能通过测量计算机获取的分割与手动跟踪(真相)之间的相似性进行评估。将估计的关节角与使用基于参考光电标记的临床协议获得的关节角进行比较。计算出平均波形之间的偏移和去除后的波形差的RMS值。分割精度高于0.92,并且非常可重复(JI的STD约为0.01)。踝关节运动学的RMSD值(平均3.4°)低于其他关节的运动(髋关节的4.9°和膝关节的6.2°)。总体而言,鉴于我们的结果与基于标记的方法之间的良好一致性,我们建议使用它来开发新一代的低成本运动分析系统。

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