Abstract:
We explore a quantitative assessment for a Microsoft Kinect-based stroke rehabilitation virtual reality (VR) video game, Mystic Isle, by evaluating three assessment metri...Show MoreMetadata
Abstract:
We explore a quantitative assessment for a Microsoft Kinect-based stroke rehabilitation virtual reality (VR) video game, Mystic Isle, by evaluating three assessment metrics of player hand movement- maximum range (extension), peak velocity and mean velocity. We also analyze the left-right hand symmetry by visualizing trajectories of both hands throughout the game. Assessment metrics obtained by the Kinect-based game have been validated using a Vicon motion capture system. The percentage errors of maximum range and mean velocity are less than 10%. The peak velocity metric is more sensitive to noise and sampling rate with a percentage error up to 18%.
Published in: 2017 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)
Date of Conference: 17-19 July 2017
Date Added to IEEE Xplore: 17 August 2017
ISBN Information:
Departrnent of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA
Department of Occupational Therapy, University of Missouri, Columbia, MO, USA
Departrnent of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA
Departrnent of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA
Department of Occupational Therapy, University of Missouri, Columbia, MO, USA
Departrnent of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA