Next Article in Journal
Appdaptivity: An Internet of Things Device-Decoupled System for Portable Applications in Changing Contexts
Next Article in Special Issue
Designing Interactive Experiences for Children with Cochlear Implant
Previous Article in Journal
Electrochemical Biosensor for Nitrite Based on Polyacrylic-Graphene Composite Film with Covalently Immobilized Hemoglobin
Article Menu
Issue 5 (May) cover image

Export Article

Open AccessArticle
Sensors 2018, 18(5), 1344; https://doi.org/10.3390/s18051344

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.
Received: 29 March 2018 / Revised: 21 April 2018 / Accepted: 23 April 2018 / Published: 26 April 2018
Full-Text   |   PDF [4416 KB, uploaded 3 May 2018]   |  

Abstract

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
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Rybarczyk, Y.; Kleine Deters, J.; Cointe, C.; Esparza, D. Smart Web-Based Platform to Support Physical Rehabilitation. Sensors 2018, 18, 1344.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top