Smartphone is most ubiquitous device and provides unique opportunity of continuous and automated tracking of sedentary lifestyle with the help of embedded sensors. In this paper, we present the evaluation of our pilot study results to track the sedentary lifestyle. The proposed model works well in real-time and inside the smartphone environment to process the sensory data. We compute the time and frequency domain features over the acceleration signals and classify the context with non-parametric nearest neighbor algorithm. To analyze the lifestyle patterns, information is transferred to the cloud server for archiving, further computation and its availability anywhere, anytime for visualization. It facilitates users to maintain and monitor their everyday lifestyle patterns and assists them to change their unhealthy sedentary behaviour identified by the proposed research. Furthermore, achieved results demonstrate the applicability of the proposed research in real-world scenarios.
|Title of host publication
|18th International Conference on Advanced Communications Technology
|Subtitle of host publication
|"Information and Communications for Safe and Secure Life!", ICACT 2016: Proceedings
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|Published - 03 Mar 2016
|18th International Conference on Advanced Communications Technology, ICACT 2016 - Pyeongchang, Korea, Republic of
Duration: 31 Jan 2016 → 03 Feb 2016
|International Conference on Advanced Communication Technology, ICACT
|18th International Conference on Advanced Communications Technology, ICACT 2016
|Korea, Republic of
|31/01/2016 → 03/02/2016
Bibliographical notePublisher Copyright:
© 2016 Global IT Research Institute (GiRI).
Copyright 2017 Elsevier B.V., All rights reserved.
- Sedentary behaviour
ASJC Scopus subject areas
- Electrical and Electronic Engineering