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Open AccessArticle

Smart Web-Based Platform to Support Physical Rehabilitation

1
Intelligent & Interactive Lab (SI2 Lab), Universidad de Las Américas, Quito 170124, Ecuador
2
Department of Electrical Engineering, CTS/UNINOVA, Nova University of Lisbon, 2829-516 Monte de Caparica, Portugal
3
Faculty of Electrical Engineering, University of Twente, 217 7500 Enschede, The Netherlands
4
Ecole Normale Supérieure de Paris-Saclay, 94235 Cachan, France
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(5), 1344; https://doi.org/10.3390/s18051344
Received: 29 March 2018 / Revised: 21 April 2018 / Accepted: 23 April 2018 / Published: 26 April 2018
The enhancement of ubiquitous and pervasive computing brings new perspectives in medical rehabilitation. In that sense, the present study proposes a smart, web-based platform to promote the reeducation of patients after hip replacement surgery. This project focuses on two fundamental aspects in the development of a suitable tele-rehabilitation application, which are: (i) being based on an affordable technology, and (ii) providing the patients with a real-time assessment of the correctness of their movements. A probabilistic approach based on the development and training of ten Hidden Markov Models (HMMs) is used to discriminate in real time the main faults in the execution of the therapeutic exercises. Two experiments are designed to evaluate the precision of the algorithm for classifying movements performed in the laboratory and clinical settings, respectively. A comparative analysis of the data shows that the models are as reliable as the physiotherapists to discriminate and identify the motion errors. The results are discussed in terms of the required setup for a successful application in the field and further implementations to improve the accuracy and usability of the system. View Full-Text
Keywords: telemedicine; motor rehabilitation; motion assessment; natural user interface; Hidden Markov Model telemedicine; motor rehabilitation; motion assessment; natural user interface; Hidden Markov Model
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Rybarczyk, Y.; Kleine Deters, J.; Cointe, C.; Esparza, D. Smart Web-Based Platform to Support Physical Rehabilitation. Sensors 2018, 18, 1344.

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