Ellipse fitting model for improving the effectiveness of life-logging physical activity measures in an Internet of Things environment
Issue Date
2016-10-13Subjects
Internet of Thingswearable computing
wearable monitoring
life-logging data
physical activity
B800 Medical Technology
Metadata
Show full item recordAbstract
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.Citation
Qi J, Yang P, Hanneghan M, Fan D, Deng Z, 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), pp.107-113.Journal
IET NetworksAdditional Links
https://ieeexplore.ieee.org/document/7587513Type
ArticleLanguage
enISSN
2047-4954EISSN
2047-4962ae974a485f413a2113503eed53cd6c53
10.1049/iet-net.2015.0109