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Please use this identifier to cite or link to this item: https://repositorio.uti.edu.ec//handle/123456789/3154
Title: Movement Detection Algorithm for Patients with Hip Surgery
Authors: Guevara-Maldonado, César
Santos. Matilde
Jadán-Guerrero, Janio
Issue Date: 2019
Publisher: Advances in Intelligent Systems and Computing. Volume 771, Pages 439 – 448. International Joint Conference: 13th International Conference on Soft Computing Models, SOCO 2018, 11th International Conference on Computational Intelligence in Security for Information Systems, CISIS 2018 and 9th International Conference on EUropean Transnational Education, ICEUTE 2018. San Sebastian. 6 June 2018 through 8 June 2018
Abstract: 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
URI: https://link.springer.com/chapter/10.1007/978-3-319-94120-2_42
http://repositorio.uti.edu.ec//handle/123456789/3154
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