Kuklyte, Jogile, Gualano, Leonardo, Prabhu, Ghanashyama ORCID: 0000-0003-2836-9734, Venkataraman, Kaushik, Walsh, Deirdre ORCID: 0000-0003-4255-299X, Woods, Catherine ORCID: 0000-0002-0892-6591, Moran, Kieran ORCID: 0000-0003-2015-8967 and O'Connor, Noel E. ORCID: 0000-0002-4033-9135 (2017) MedFit: a mobile application for patients in CVD recovery. In: MMHealth Workshop 2017 at ACM Multimedia, October 23 - 27 2017, Mountain View, CA, USA. ISBN 978-1-4503-5504-9
Abstract
The third phase of the recovery from cardiovascular disease (CVD) is an exercise-based rehabilitation programme. However, adherence to an exercise regime is typically not maintained by the patient for a variety of reasons such as lack of time, financial constraints, etc. In order to facilitate patients to perform their exercises from the comfort of their home and at their own convenience, we have developed a mobile application, termed MedFit. It provides access to a tailored suite of exercises along with easy to understand guidance from audio and video instructions. Two types of wearable sensors are utilized to provide motivational feedback. Fitbit, a commercially available activity and fitness tracker, is used to provide in-depth feedback for self-monitoring over longer periods of time (e.g. day, week, month), whereas the Shimmer wireless sensing platform provides the data for near real-time feedback on the quality of the exercises performed. MedFit is a simple and intuitive mobile application designed to provide the motivation and tools for patients to help ensure faster recovery from the trauma caused by CVD. In this paper we describe features available in the MedFit application and the overall motivation behind the project.
Metadata
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Event Type: | Conference |
Refereed: | Yes |
Uncontrolled Keywords: | Cardiovascular disease; Mobile Application; Wearable Sensors; Activity Recognition; Repetition Counting; Health care information systems; |
Subjects: | Engineering > Imaging systems Medical Sciences > Exercise Engineering > Signal processing Medical Sciences > Health Medical Sciences > Sports sciences |
DCU Faculties and Centres: | UNSPECIFIED |
Published in: | MMHealth Workshop 2017 at ACM Multimedia, Proceedings. . ACM. ISBN 978-1-4503-5504-9 |
Publisher: | ACM |
Official URL: | https://doi.org/10.1145/3132635.3132651 |
Copyright Information: | © 2017 ACM. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. https://doi.org/10.1145/3132635.3132651 |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
Funders: | Science Foundation Ireland. Grant No. SFI/12/RC/2289 |
ID Code: | 22011 |
Deposited On: | 23 Oct 2017 08:49 by Jogile Kuklyte . Last Modified 25 Nov 2019 16:04 |
Documents
Full text available as:
Preview |
PDF
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
896kB |
Downloads
Downloads
Downloads per month over past year
Archive Staff Only: edit this record