A Mobile Application for Physical Activity Recognition using Acceleration Data from Wearable Sensors for Cardiac Rehabilitation

M. Chaari, M. Chaari, M. Abid, M. Abid, Y. Ouakrim, Y. Ouakrim, M. Lahami, N. Mezghani, N. Mezghani

2020

Abstract

mHealth applications are an ever-expanding frontier in today’s use of technology. They allow a user to record health data and contact their doctor from the convenience of a smartphone. This paper presents a first version release of a mobile application that aims to assess compliance of cardiovascular diseased patients with home-based cardiac rehabilitation, by monitoring physical activities using wearable sensors. The application generates reports for both the patient and the doctor through an interactive dashboard, as initial proposal, that provides feedback of physical activities of daily living undertaken by the patient. The application integrates a human activity recognition system, which learns a support vector machine algorithm to identify 10 different daily activities, such as walking, going upstairs, sitting and lying, from accelerometer data using a connected textile including movement sensors. Our early deployment and execution results are promising since they are showing good accuracy for recognizing all the ten daily living activities.

Paper Citation

in Harvard Style

Chaari M., Abid M., Ouakrim Y., Lahami M. and Mezghani N. (2020). A Mobile Application for Physical Activity Recognition using Acceleration Data from Wearable Sensors for Cardiac Rehabilitation. In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 5: HEALTHINF; ISBN 978-989-758-398-8, SciTePress, pages 625-632. DOI: 10.5220/0009118706250632

in Bibtex Style

@conference{healthinf20,
author={M. Chaari and M. Abid and Y. Ouakrim and M. Lahami and N. Mezghani},
title={A Mobile Application for Physical Activity Recognition using Acceleration Data from Wearable Sensors for Cardiac Rehabilitation},
booktitle={Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 5: HEALTHINF},
year={2020},
pages={625-632},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009118706250632},
isbn={978-989-758-398-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 5: HEALTHINF
TI - A Mobile Application for Physical Activity Recognition using Acceleration Data from Wearable Sensors for Cardiac Rehabilitation
SN - 978-989-758-398-8
AU - Chaari M.
AU - Abid M.
AU - Ouakrim Y.
AU - Lahami M.
AU - Mezghani N.
PY - 2020
SP - 625
EP - 632
DO - 10.5220/0009118706250632
PB - SciTePress