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Design and development of the MedFit App: a mobile application for cardiovascular disease rehabilitation

Prabhu, Ghanashyama ORCID: 0000-0003-2836-9734, Kuklyte, Jogile, Gualano, Leonardo, Venkataraman, Kaushik, Ahmadi, Amin, Duff, Orlaith, Walsh, Deirdre ORCID: 0000-0003-4255-299X, Woods, Catherine ORCID: 0000-0002-0892-6591, O'Connor, Noel E. ORCID: 0000-0002-4033-9135 and Moran, Kieran ORCID: 0000-0003-2015-8967 (2017) Design and development of the MedFit App: a mobile application for cardiovascular disease rehabilitation. In: MobiHealth 2017 – 7th EAI International Conference on Wireless Mobile Communication and Healthcare, 14-16 Nov 2017, Vienna, Austria. ISBN 978-3-319-98550-3

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Abstract

Rehabilitation from cardiovascular disease (CVD) usually requires lifestyle changes, especially an increase in exercise and physical activity. However, uptake and adherence to exercise is low for community based programmes. We propose a mobile application that allows users to choose the type of exercise and compete it at a convenient time in the comfort of their own home. Grounded in a behaviour change framework, the application provides feedback and encouragement to continue exercising and to improve on previous results. The application also utilizes wearable wireless technologies in order to provide highly personalized feedback. The application can accurately detect if a specic exercise is being done, and count the associated number of repetitions utilizing accelerometer or gyroscope signalsMachine learning models are employed to recognize individual local muscular endurance (LME) exercises, achieving overall accuracy of more than 98%. This technology allows providing a near real-time personalized feedback which mimics the feedback that the user might expect from an instructor. This is provided to motivate users to continue the recovery process.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:Cardiovascular disease; Mobile Application; Support Vector Machine; Wearable Sensors; Repetition Counting
Subjects:Computer Science > Information technology
Computer Science > Machine learning
Engineering > Electronic engineering
Medical Sciences > Sports sciences
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
DCU Faculties and Schools > Faculty of Science and Health > School of Health and Human Performance
Research Initiatives and Centres > INSIGHT Centre for Data Analytics
Published in: Wireless Mobile Communication and Healthcare. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering . Springer. The original publication is available at www.springerlink.com. ISBN 978-3-319-98550-3
Publisher:Springer. The original publication is available at www.springerlink.com
Official URL:https://www.springerprofessional.de/design-and-development-of-the-medfit-app-a-mobile-application-fo/16068514
Copyright Information:© 2017 Springer
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:SFI, Ireland, grant no. SFI/12/RC/2289, AcquisBi
ID Code:22042
Deposited On:20 Nov 2017 13:53 by Ghanashyama Prabhu . Last Modified 25 Nov 2019 16:03

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