Andrés, J, Bailador, G, Gibbons, CH et al. (1 more author) (2016) Designing and Testing HealthTracker for Activity Recognition and Energy Expenditure Estimation within the DAPHNE Platform. Procedia Computer Science, 98. pp. 348-355. ISSN 1877-0509
Abstract
This paper describes the design and evaluation of a mobile software library, HealthTracker, which aims to produce activity and energy expenditure estimations in real-time from accelerometer and gyroscope data provided by wearable sensors. Using feature extraction together with a classifier trained using machine learning, the system will automatically and periodically send all the produced estimations to a cloud-based platform that will allow later evaluation by both the user and a physician or caretaker. The system is presented within the DAPHNE platform, an ICT ecosystem designed to provide a means for remote health and lifestyle monitoring and guidance between physicians and their patients.
Metadata
Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Wearable devices; activity detection; energy expenditure; feature extraction; machine learning; signal processing |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Psychology (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 14 Oct 2016 10:48 |
Last Modified: | 05 Oct 2017 16:22 |
Published Version: | http://dx.doi.org/10.1016/j.procs.2016.09.052 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | https://doi.org/10.1016/j.procs.2016.09.052 |