Next Article in Journal / Special Issue
Application of Computational Intelligence to Improve Education in Smart Cities
Previous Article in Journal
Smartphone-Based Cooperative Indoor Localization with RFID Technology
Previous Article in Special Issue
Using Markov Chains and Multi-Objective Optimization for Energy-Efficient Context Recognition
Article Menu
Issue 1 (January) cover image

Export Article

Open AccessArticle
Sensors 2018, 18(1), 268;

A More Efficient Transportable and Scalable System for Real-Time Activities and Exercises Recognition

LIARA Laboratory, Université du Québec à Chicoutimi, Chicoutimi, QC G7H 2B1, Canada
Authors to whom correspondence should be addressed.
Received: 15 December 2017 / Revised: 11 January 2018 / Accepted: 12 January 2018 / Published: 18 January 2018
(This article belongs to the Special Issue Sensing, Data Analysis and Platforms for Ubiquitous Intelligence)
Full-Text   |   PDF [9177 KB, uploaded 19 January 2018]   |  


Many people in the world are affected by muscle wasting, especially the population hits by myotonic dystrophy type 1 (DM1). Those people are usually given a program of multiple physical exercises to do. While DM1 and many other people have difficulties attending commercial centers to realize their program, a solution is to develop such a program completable at home. To this end, we developed a portable system that patients could bring home. This prototype is an improved version of the previous one using Wi-Fi, as this new prototype runs on BLE technology. This new prototype conceptualized induces great results. View Full-Text
Keywords: activity recognition; wearable; power efficiency; machine learning activity recognition; wearable; power efficiency; machine learning

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).

Share & Cite This Article

MDPI and ACS Style

Chapron, K.; Plantevin, V.; Thullier, F.; Bouchard, K.; Duchesne, E.; Gaboury, S. A More Efficient Transportable and Scalable System for Real-Time Activities and Exercises Recognition. Sensors 2018, 18, 268.

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



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