Micro-context recognition of sedentary behaviour using smartphone
Document Type
Conference Proceeding
Source of Publication
2016 6th International Conference on Digital Information and Communication Technology and Its Applications, DICTAP 2016
Publication Date
8-15-2016
Abstract
© 2016 IEEE. embedded sensors of smartphone provides a unique opportunity to recognize the micro-context of sedentary behaviour. In this paper, we present our research findings on how to recognize micro-contexts by utilizing on board sensors of smartphone. Our proposed approach consists of two stages process. First, we recognize the situation of a person to be either stationery or moving. If stationary, then high probability to be sedentary, in which we can then find micro details about the current context. Second, we process environmental sound and recognize the person's micro-context such as watching television, working on computers or relaxing. Furthermore, we also provide the lifestyle analytics over cloud computing infrastructure to make it available anywhere and anytime for self-management purpose. We developed an initial working prototype to evaluate the applicability of our approach in a real-world scenario.
DOI Link
ISBN
9781467396097
Publisher
Institute of Electrical and Electronics Engineers Inc.
First Page
30
Last Page
34
Disciplines
Computer Sciences
Keywords
k-NN, Micro-context Recognizer, Sedentary behaviour, Smartphone
Scopus ID
Recommended Citation
Fahim, Muhammad; Khattak, Asad Masood; Baker, Thar; Chow, Francis; and Shah, Babar, "Micro-context recognition of sedentary behaviour using smartphone" (2016). All Works. 2391.
https://zuscholars.zu.ac.ae/works/2391
Indexed in Scopus
yes
Open Access
no