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 language | English |
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Pages (from-to) | 1371-1382 |
Number of pages | 12 |
Journal | Journal of Robotics and Mechatronics |
Volume | 34 |
Issue number | 6 |
DOIs | |
Publication status | Published - Dec 2022 |
Externally published | Yes |
All Science Journal Classification (ASJC) codes
- General Computer Science
- Electrical and Electronic Engineering