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Qi, J, Yang, P, Hanneghan, M, Fan, D, Deng, Z and Dong, F (2016) Ellipse fitting model for improving the effectiveness of life-logging physical activity measures in an Internet of Things environment. IET Networks, 5 (5). ISSN 2047-4954
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Abstract
The popular use of wearable devices and mobile phones makes the effective capture of life-logging physical activity (PA) data in an Internet of Things (IoT) environment possible. The effective collection of measures of PA in the long term is beneficial to interdisciplinary healthcare research and collaboration from clinicians, researchers and patients. However, due to heterogeneity of connected devices and rapid change of diverse life patterns in an IoT environment, life-logging PA information captured by mobile devices usually contains much uncertainty. In this study, the authors project the distribution of irregular uncertainty by defining a walking speed related score named as daily activity in physical space and present an ellipse-fitting model-based validity improvement method for reducing uncertainties of life-logging PA measures in an IoT environment. The experimental results reflect that the proposed method remarkably improves the validity of PA measures in a healthcare platform. © The Institution of Engineering and Technology 2016.
| Item Type: | Article |
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| Subjects: | G Geography. Anthropology. Recreation > GV Recreation Leisure Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Computer Science & Mathematics |
| Publisher: | IET |
| Date Deposited: | 23 Nov 2016 12:35 |
| Last Modified: | 04 Sep 2021 12:15 |
| DOI or ID number: | 10.1049/iet-net.2015.0109 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/4856 |
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