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无标记与基于标记运动捕捉技术在地面行走中三维运动学的比较。

A comparison of three-dimensional kinematics between markerless and marker-based motion capture in overground gait.

机构信息

Department of Kinesiology and Sport Sciences, University of Miami, Miami, FL, United States; Sports Medicine Institute, University of Miami Miller School of Medicine, Miami, FL, United States.

Department of Kinesiology and Sport Sciences, University of Miami, Miami, FL, United States.

出版信息

J Biomech. 2023 Oct;159:111793. doi: 10.1016/j.jbiomech.2023.111793. Epub 2023 Sep 7.

Abstract

Vision-based methods using RGB inputs for human pose estimation have grown in recent years but have undergone limited testing in clinical and biomechanics research areas like gait analysis. The purpose of the present study was to compare lower extremity kinematics during overground gait between a traditional marker-based approach and a commercial multi-view markerless system in a sample of subjects including young adults, older adults, and adults diagnosed with Parkinson's disease. A convenience sample of 35 adults between the age of 18-85 years were included in this study, yielding a total of 114 trials and 228 gait cycles that were compared between systems. A total of 30 time normalized waveforms, including three-dimensional joint centers, segment angles, and joint angles were compared between systems using root mean-squared error (RMSE), range of motion difference (ΔROM), Pearson correlation coefficients (r), and interclass correlation coefficients (ICC). RMSEs for joint center positions were less than 28 mm in all joints with correlations indicating good to excellent agreement. RMSEs for segment and joint angles were in range of previous results, with highest agreement between systems in the sagittal plane. ΔROM differences were within reference values that characterize clinical groups like Parkinson's disease, stroke, or knee osteoarthritis. Further improvements in pelvis tracking, markerless keypoint model definitions, and standardization of comparison study protocols are needed. Nevertheless, markerless solutions seem promising toward unrestricted motion analysis in biomechanics research and clinical settings.

摘要

近年来,基于视觉的 RGB 输入人体姿势估计方法发展迅速,但在临床和生物力学研究领域(如步态分析)的测试有限。本研究的目的是在年轻人、老年人和帕金森病患者的样本中,比较传统基于标记的方法和商业多视图无标记系统在地面行走时下肢运动学的差异。本研究纳入了 35 名年龄在 18-85 岁之间的成年人的便利样本,共进行了 114 次试验和 228 个步态周期,在两个系统之间进行了比较。使用均方根误差(RMSE)、运动范围差异(ΔROM)、Pearson 相关系数(r)和组内相关系数(ICC)比较了两个系统之间的 30 个时间归一化波形,包括三维关节中心、节段角度和关节角度。所有关节的关节中心位置 RMSE 均小于 28mm,相关系数表明具有良好到极好的一致性。节段和关节角度的 RMSE 在先前结果的范围内,系统之间在矢状面的一致性最高。ΔROM 差异在临床组(如帕金森病、中风或膝骨关节炎)的参考值范围内。需要进一步改进骨盆跟踪、无标记关键点模型定义以及比较研究协议的标准化。然而,无标记解决方案似乎很有前途,可以用于生物力学研究和临床环境中的无限制运动分析。

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