Telerehabilitation System Based on OpenPose and 3D Reconstruction with Monocular Camera

Keisuke Osawa, Yu You, Yi Sun, Tai-Qi Wang, Shun Zhang, M. Shimodozono, Eiichirou Tanaka
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Abstract

Owing to aging populations, the number of elderly people with limb dysfunction affecting their daily lives will continue to increase. These populations have a great need for rehabilitation training to restore limb functions. However, the current numbers of rehabilitation hospitals and doctors are limited. Moreover, people often cannot go to a hospital owing to external conditions (e.g., the impacts of COVID-19). Thus, an urgent need exists for telerehabilitation system for allowing patients to have training at home. The purpose of this study is to develop an easy-to-use system for allowing target users to experience rehabilitation training at home and to remotely receive real-time guidance from doctors. The proposed system only needs a monocular camera to capture 3D motions. First, the 2D key joints of the human body are detected; then, a simple baseline network is used to reconstruct 3D key joints from the 2D key joints. The 2D detection only has an average angle error of 1.7% compared to that of a professional motion capture system. In addition, the 3D reconstruction has a mean per-joint position error of only 67.9 mm compared to the real coordinates. After acquiring the user’s 3D motions, the system synchronizes the 3D motions to a virtual human model in Unity, providing the user with a more intuitive and interactive experience. Generally, many telerehabilitation systems require professional motion capture cameras and wearable equipment, and the training target is a single body part. In contrast, the proposed system is low-cost and easier to use and only requires a monocular camera and computer to achieve real-time and intuitive telerehabilitation (even though the training target is the entire body). Furthermore, the system provides a similarity evaluation of the motions based on the dynamic time warping; this can provide more accurate and direct feedback to users. In addition, a series of evaluation experiments verify the system’s usability, convenience, feasibility, and accuracy, with the ultimate conclusion that the system can be used in practical rehabilitation applications.
基于OpenPose和单目相机三维重建的远程康复系统
由于人口老龄化,肢体功能障碍影响老年人日常生活的人数将继续增加。这些人群非常需要康复训练来恢复肢体功能。然而,目前康复医院和医生的数量有限。此外,由于外部条件(例如COVID-19的影响),人们往往无法去医院。因此,迫切需要远程康复系统,使患者能够在家中进行训练。本研究的目的是开发一个易于使用的系统,使目标用户能够在家中体验康复训练,并远程接受医生的实时指导。所提出的系统只需要一个单目摄像机来捕捉3D运动。首先对人体的二维关键关节进行检测;然后,利用简单的基线网络,从二维关键节点重构三维关键节点。与专业动作捕捉系统相比,2D检测的平均角度误差仅为1.7%。此外,与真实坐标相比,三维重建的平均每个关节位置误差仅为67.9 mm。在获取用户的3D动作后,系统将3D动作同步到Unity中的虚拟人体模型中,为用户提供更加直观和互动的体验。一般来说,许多远程康复系统需要专业的运动捕捉摄像机和可穿戴设备,训练目标是单个身体部位。相比之下,所提出的系统成本低,易于使用,只需要一个单目摄像机和计算机就可以实现实时和直观的远程康复(即使训练目标是整个身体)。此外,该系统还提供了基于动态时间规整的运动相似度评估;这可以为用户提供更准确和直接的反馈。此外,通过一系列的评估实验,验证了系统的可用性、便捷性、可行性和准确性,最终得出该系统可用于实际康复应用的结论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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