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JRM Vol.34 No.6 pp. 1371-1382
doi: 10.20965/jrm.2022.p1371
(2022)

Paper:

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A Remote Rehabilitation and Evaluation System Based on Azure Kinect

Tai-Qi Wang*, Yu You*, Keisuke Osawa*, Megumi Shimodozono**, and Eiichiro Tanaka***

*Graduate School of Information, Production and Systems, Waseda University
2-7 Hibikino, Wakamatsu-ku, Kitakyushu, Fukuoka 808-0135, Japan

**Graduate School of Medical and Dental Sciences, Kagoshima University
8-35-1 Sakuragaoka, Kagoshima, Kagoshima 890-8544, Japan

***Faculty of Science and Engineering, Waseda University
2-7 Hibikino, Wakamatsu-ku, Kitakyushu, Fukuoka 808-0135, Japan

Received:
May 20, 2022
Accepted:
September 2, 2022
Published:
December 20, 2022
Creative Commons License
Keywords:
Azure Kinect, remote rehabilitation, 3D motion acquisition and evaluation
Abstract

In response to the shortage, uneven distribution, and high cost of rehabilitation resources in the context of the COVID-19 pandemic, we developed a low-cost, easy-to-use remote rehabilitation system that allows patients to perform rehabilitation training and receive real-time guidance from doctors at home. The proposed system uses Azure Kinect to capture motions with an error of just 3% compared to professional motion capture systems. In addition, the system provides an automatic evaluation function of rehabilitation training, including evaluation of motion angles and trajectories. After acquiring the user’s 3D motions, the system synchronizes the 3D motions to the virtual human body model in Unity with an average error of less than 1%, which gives the user a more intuitive and interactive experience. After a series of evaluation experiments, we verified the usability, convenience, and high accuracy of the system, finally concluding that the system can be used in practical rehabilitation applications.

Schematic of remote rehabilitation and evaluation system

Schematic of remote rehabilitation and evaluation system

Cite this article as:
T. Wang, Y. You, K. Osawa, M. Shimodozono, and E. Tanaka, “A Remote Rehabilitation and Evaluation System Based on Azure Kinect,” J. Robot. Mechatron., Vol.34 No.6, pp. 1371-1382, 2022.
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