Keisuke Osawa, Yu You, Yi Sun, Tai-Qi Wang, Shun Zhang, M. Shimodozono, Eiichirou Tanaka
{"title":"Telerehabilitation System Based on OpenPose and 3D Reconstruction with Monocular Camera","authors":"Keisuke Osawa, Yu You, Yi Sun, Tai-Qi Wang, Shun Zhang, M. Shimodozono, Eiichirou Tanaka","doi":"10.20965/jrm.2023.p0586","DOIUrl":null,"url":null,"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.","PeriodicalId":178614,"journal":{"name":"J. Robotics Mechatronics","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Robotics Mechatronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20965/jrm.2023.p0586","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.