Division of Physical and Occupational Therapy, Department of Integrated Health Science, Graduate School of Medicine, Nagoya University Daiko-minami, Higashi-ku, Nagoya, Japan.
Biomedical and Health Informatics Unit, Department of Integrated Health Science, Graduate School of Medicine, Nagoya University Daiko-minami, Higashi-ku, Nagoya, Japan.
PLoS Comput Biol. 2023 Jan 19;19(1):e1009989. doi: 10.1371/journal.pcbi.1009989. eCollection 2023 Jan.
Two-dimensional video-based pose estimation is a technique that can be used to estimate human skeletal coordinates from video data alone. It is also being applied to gait analysis and in particularly, due to its simplicity of measurement, it has the potential to be applied to gait analysis of large populations. However, it is considered difficult to completely homogenize the environment and settings during the measurement of large populations. Therefore, it is necessary to appropriately deal with technical errors that are not related to the biological factors of interest. In this study, by analyzing a large cohort database, we have identified four major types of anomalies that occur during gait analysis using OpenPose in uncontrolled environments: anatomical, biomechanical, and physical anomalies and errors due to estimation. We have also developed a workflow for identifying and correcting these anomalies and confirmed that this workflow is reproducible through simulation experiments. Our results will help obtain a comprehensive understanding of the anomalies to be addressed during pre-processing for 2D video-based gait analysis of large populations.
基于二维视频的姿态估计是一种仅从视频数据中估计人体骨骼坐标的技术。它也被应用于步态分析，特别是由于其测量的简单性，它有可能被应用于大人群的步态分析。然而，在大人群的测量过程中，要完全使环境和设置同质化是被认为是困难的。因此，有必要适当地处理与感兴趣的生物因素无关的技术误差。在这项研究中，我们通过分析一个大型队列数据库，确定了在非受控环境中使用 OpenPose 进行步态分析时出现的四种主要异常类型：解剖学、生物力学和物理异常，以及由于估计而产生的误差。我们还开发了一种用于识别和纠正这些异常的工作流程，并通过模拟实验确认了该工作流程的可重复性。我们的研究结果将有助于全面了解在大人群的基于二维视频的步态分析的预处理过程中需要解决的异常。
