Name
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%. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/CHASE.2017.90 | 2017 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) |
Keywords | Field | DocType |
stroke rehabilitation game,assessment,validation | Motion capture,Rehabilitation,Computer vision,Virtual reality,Computer science,Simulation,Sampling (signal processing),Stroke,Artificial intelligence,Quantitative assessment,Trajectory | Conference |
ISBN | Citations | PageRank |
978-1-5090-4723-9 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mengxuan Ma | 1 | 1 | 1.76 |
| Rachel Proffitt | 2 | 25 | 4.17 |
| Marjorie Skubic | 3 | 1045 | 105.36 |