Quantitative Evaluation of the Microsoft Kinect for Use in an Upper Extremity Virtual Rehabilitation Environment

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C23_Nixon_ICVR2013.pdf (235.94 KB)
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Nixon, Mason
Chen, Yu-ping
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http://hdl.handle.net/1853/48212
Abstract
Low cost depth sensors could potentially allow for home-based care and rehabilitation using virtual systems. Currently, no publicly available and peer-reviewed assessment has been made on the accuracy of joint position data determined by the Microsoft KinectTM for assessment of upper extremity movements. We devised and validated clinically-based angle classifications for random arm movements in 3D-space, specifically, the shoulder joint flexion/extension angle, shoulder joint abduction/adduction angle, and 3-dimensional shoulder joint angle of 19 subjects at a distance of 2.0m using an eight camera Vicon Motion Capture system. Results show an average absolute error of these angle measurements not exceeding 10.0%.
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2013
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