Quantified-self for obesity: physical activity behaviour sensing to improve health outcomes

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Title: Quantified-self for obesity: physical activity behaviour sensing to improve health outcomes
Authors: Taylor, D
Murphy, J
Ahmad, M
Purkayastha, S
Scholtz, S
Ramezani, R
Vlaev, I
Blakemore, AI
Darzi, A
Item Type: Journal Article
Abstract: © 2016 The authors and IOS Press. All rights reserved.Physical activity levels in bariatric patients have not been well documented, despite their importance in maintaining weight loss following surgery. This study investigated the feasibility of tracking physical activity using a smartphone app with minimal user interaction. Thus far, we have obtained good quality data from 255 patients at various points in their weight loss journey. Preliminary analyses indicate little change in physical activity levels following surgery with pre-surgery patients reaching an average of 16 minutes per day and post-surgery patients achieving a daily average of 21 minutes. Further analyses using machine-learning techniques will be conducted to determine whether physical activity is a critical factor in distinguishing between successful and unsuccessful weight loss outcomes and in the resolution of comorbid conditions in patients with similar clinical profiles.
Issue Date: 7-Apr-2016
Date of Acceptance: 25-Nov-2015
URI: http://hdl.handle.net/10044/1/36943
DOI: https://dx.doi.org/10.3233/978-1-61499-625-5-414
ISSN: 1879-8365
Publisher: IOS Press
Start Page: 414
End Page: 416
Journal / Book Title: Studies in Health Technology and Informatics
Volume: 220
Copyright Statement: ©2015 IOP Publishing Ltd.
Keywords: Medical Informatics
1117 Public Health And Health Services
0807 Library And Information Studies
Publication Status: Published
Appears in Collections:Division of Surgery
Department of Medicine
Faculty of Medicine



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