Authors:
M. Chaari
1
;
2
;
M. Abid
3
;
1
;
Y. Ouakrim
3
;
1
;
M. Lahami
2
and
N. Mezghani
3
;
1
Affiliations:
1
LICEF Research Center, TELUQ, Montreal, Canada
;
2
National School of Engineers of Sfax, Sfax University, Tunisia
;
3
Laboratoire de Recherche en Imagerie et Orthopédie (LIO), CRCHUM, Montreal, Canada
Keyword(s):
mHealth, Mobile Application, Cardiac Rehabilitation, Human Activity Recognition (HAR), Wearable Sensors, Classification.
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 g
ood accuracy for recognizing all the ten daily living activities.
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