Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8797742 | Clinical Biomechanics | 2018 | 9 Pages |
Abstract
The non-invasive Microsoft Kinect sensor and the proposed dynamical toolset comprised of data preprocessing, feature extraction, dimensionality reduction, and machine learning offers a low-cost and general method for performance segregation and can complement existing qualitative clinical assessments.
Keywords
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Authors
Zaki Hasnain, Ming Li, Tanya Dorff, David Quinn, Naoto T. Ueno, Sriram Yennu, Anand Kolatkar, Cyrus Shahabi, Luciano Nocera, Jorge Nieva, Peter Kuhn, Paul K. Newton,