TY - GEN
T1 - Improving the validity of lifelogging physical activity measures in an internet of things environment
AU - Yang, Po
AU - Hanneghan, Martin
AU - Qi, Jun
AU - Deng, Zhikun
AU - Dong, Feng
AU - Fan, Dina
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/12/22
Y1 - 2015/12/22
N2 - Recently, the popular use of wearable devices and mobile apps makes the effectively capture of lifelogging physical activity data in an Internet of Things (IoT) environment possible. The effective collection of measures of physical activity in the long term is beneficial to interdisciplinary healthcare research and collaboration from clinicians, researchers to patients. However, due to heterogeneity of connected devices and rapid change of diverse life patterns in an IoT environment, lifelogging physical activity information captured by mobile devices usually contains much uncertainty. In this paper, we provide a comprehensive review of existing life-logging physical activity measurement devices, and identify regular and irregular uncertainties of these activity measures in an IoT environment. We then project the distribution of irregular uncertainty by defining a walking speed related score named as Daily Activity in Physical Space (DAPS). Finally, we present an ellipse fitting model based validity improvement method for reducing uncertainties of life-logging physical activity measures in an IoT environment. The experimental results reflect that the proposed method effectively improves the validity of physical activity measures in a healthcare platform.
AB - Recently, the popular use of wearable devices and mobile apps makes the effectively capture of lifelogging physical activity data in an Internet of Things (IoT) environment possible. The effective collection of measures of physical activity in the long term is beneficial to interdisciplinary healthcare research and collaboration from clinicians, researchers to patients. However, due to heterogeneity of connected devices and rapid change of diverse life patterns in an IoT environment, lifelogging physical activity information captured by mobile devices usually contains much uncertainty. In this paper, we provide a comprehensive review of existing life-logging physical activity measurement devices, and identify regular and irregular uncertainties of these activity measures in an IoT environment. We then project the distribution of irregular uncertainty by defining a walking speed related score named as Daily Activity in Physical Space (DAPS). Finally, we present an ellipse fitting model based validity improvement method for reducing uncertainties of life-logging physical activity measures in an IoT environment. The experimental results reflect that the proposed method effectively improves the validity of physical activity measures in a healthcare platform.
KW - Internet of things
KW - Life-logging
KW - Physical activity
UR - http://www.scopus.com/inward/record.url?scp=84964267366&partnerID=8YFLogxK
U2 - 10.1109/CIT/IUCC/DASC/PICOM.2015.341
DO - 10.1109/CIT/IUCC/DASC/PICOM.2015.341
M3 - Conference Proceeding
AN - SCOPUS:84964267366
T3 - Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015
SP - 2309
EP - 2314
BT - Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015
A2 - Atzori, Luigi
A2 - Jin, Xiaolong
A2 - Jarvis, Stephen
A2 - Liu, Lei
A2 - Calvo, Ramon Aguero
A2 - Hu, Jia
A2 - Min, Geyong
A2 - Georgalas, Nektarios
A2 - Wu, Yulei
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015
Y2 - 26 October 2015 through 28 October 2015
ER -