A Remote Rehabilitation and Evaluation System Based on Azure Kinect

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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 pro-vides an automatic evaluation function of rehabilitation training, including evaluation of motion angles and trajectories. After acquiring the user’s 3D mo-tions, 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, con-venience, and high accuracy of the system, finally con-cluding that the system can be used in practical rehabilitation applications.

Original languageEnglish
Pages (from-to)1371-1382
Number of pages12
JournalJournal of Robotics and Mechatronics
Volume34
Issue number6
DOIs
Publication statusPublished - 2022 Dec

Keywords

  • 3D motion acquisition and evaluation
  • Azure Kinect
  • remote rehabilitation

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering

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