Movement Detection Algorithm for Patients with Hip Surgery

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. © 2019, Springer International Publishing AG, part of Springer Nature.