Designing for Rehabilitation Movement Recognition and Measurement in Virtual Reality
Latif, Ummi Khaira; Gong, Zhengya; Nanjappan, Vijayakumar; Georgiev, Georgi V.
Type:
Year:
2023
Editor:
Kevin Otto, Boris Eisenbart, Claudia Eckert, Benoit Eynard, Dieter Krause, Josef Oehmen, Nad
Author:
Series:
ICED
Institution:
Center for Ubiquitous Computing, University of Oulu, Finland
Section:
Design Methods
Page(s):
1387-1396
DOI number:
Abstract:
Virtual reality (VR)-based rehabilitation has been widely implemented to maintain and increase patient motivation during therapy sessions. Researchers nowadays design VR-based rehabilitation by leveraging off-the-shelf VR devices for easy access and application. However, researchers need to implement additional custom hardware or incorporate a specific algorithm to perform a real-time evaluation of each therapeutic movement. This study aims to design and develop a system with features for recognizing and measuring the upper limb rehabilitation movement in VR using off-the-shelf VR devices such as VR headsets, controllers, and trackers. This system is bundled and distributed as a single toolkit to accommodate other researchers in providing the evaluation feature for their VR-based rehabilitation system. The user experiment was conducted to verify the usability of this proposed design system. The experiment results show that the system can recognize 16 upper limb movements and provide several measurement data that researchers can use in providing the evaluation feature based on their design requirements.
Keywords:
