Title:
Validation of Accuracy of the Super Pop VR™ Kinematic Assessment Methodology Using Markerless Versus Marker-Based Motion Capture Systems
Validation of Accuracy of the Super Pop VR™ Kinematic Assessment Methodology Using Markerless Versus Marker-Based Motion Capture Systems
| dc.contributor.author | García-Vergara, Sergio | |
| dc.contributor.author | Robinette, Paul | |
| dc.contributor.author | Chen, Yu-Ping | |
| dc.contributor.author | Howard, Ayanna M. | |
| dc.contributor.corporatename | Georgia Institute of Technology. Institute for Robotics and Intelligent Machines | en_US |
| dc.contributor.corporatename | Georgia Institute of Technology. School of Electrical and Computer Engineering | en_US |
| dc.contributor.corporatename | Georgia State University. College of Health and Human Sciences | en_US |
| dc.date.accessioned | 2016-04-13T16:16:41Z | |
| dc.date.available | 2016-04-13T16:16:41Z | |
| dc.date.issued | 2016 | |
| dc.description.abstract | Therapists and clinicians have been combining virtual reality (VR) systems for rehabilitation purposes with motion capture systems to accurately keep track of the users' movements and better analyze their kinematic performance. The current state-of-the-art motion capture technology is limited to the clinical setting due to its cost, the necessity for a controlled environment, requirement of additional equipment, among others. Given the benefits of home-based rehabilitation protocols, more portable and cost-effective technology is being coupled with the VR systems. In this work, we focus on validating the accuracy of the Kinect™ camera from Microsoft. We compare its performance to a current state-of-the-art motion capture system. Namely, we 1) analyze the difference between the outcome metrics computed with data collected with the Kinect™ camera and the outcome metrics computed with data collected with the motion capture system, and 2) compare the spatial trajectories generated by both systems for the hand, elbow, and shoulder joints. Data were collected from ten able-bodied adults to quantify these comparisons. In general, results from both analyzes support the validity and feasibility of using the Kinect™ camera for home-based rehabilitation purposes. | en_US |
| dc.embargo.terms | null | en_US |
| dc.identifier.citation | García-Vergara, S., Robinette, P., Chen, Y-P., & Howard, A. M. (2016). Validation of Accuracy of the Super Pop VR™ Kinematic Assessment Methodology Using Markerless Versus Marker-Based Motion Capture Systems (in publication). | en_US |
| dc.identifier.uri | http://hdl.handle.net/1853/54727 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Georgia Institute of Technology | en_US |
| dc.subject | Home-based rehabilitation | en_US |
| dc.subject | Kinect™ vs. OptiTrack | en_US |
| dc.subject | Physical therapy | en_US |
| dc.subject | Super Pop VR™ | en_US |
| dc.subject | Technological rehabilitation | en_US |
| dc.title | Validation of Accuracy of the Super Pop VR™ Kinematic Assessment Methodology Using Markerless Versus Marker-Based Motion Capture Systems | en_US |
| dc.type | Text | |
| dc.type.genre | Post-print | |
| dspace.entity.type | Publication | |
| local.contributor.author | Howard, Ayanna M. | |
| local.contributor.corporatename | School of Civil and Environmental Engineering | |
| local.contributor.corporatename | Institute for Robotics and Intelligent Machines (IRIM) | |
| relation.isAuthorOfPublication | 6d77e175-105c-4b0b-9548-31f20e60e20a | |
| relation.isOrgUnitOfPublication | 88639fad-d3ae-4867-9e7a-7c9e6d2ecc7c | |
| relation.isOrgUnitOfPublication | 66259949-abfd-45c2-9dcc-5a6f2c013bcf |