This work proposes a model of movement detection in patients with hip surgery rehabilitation. Using the Microsoft Xbox One Kinect motion capture device, information is acquired from 25 body points -with their respective coordinate axes- of patients while doing rehabilitation exercises. Bayesian networks and sUpervised Classification System (UCS) techniques have been jointly applied to identify correct and incorrect movements. The proposed system generates a multivalent logical model, which allows the simultaneous representation of the exercises performed by patients with good precision. It can be a helpful tool to guide rehabilitation.
CITATION STYLE
Guevara, C., Santos, M., & Jadán, J. (2019). Movement Detection Algorithm for Patients with Hip Surgery. In Advances in Intelligent Systems and Computing (Vol. 771, pp. 439–448). Springer Verlag. https://doi.org/10.1007/978-3-319-94120-2_42
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