Micro-context recognition of sedentary behaviour using smartphone

Muhammad Fahim; Asad Masood Khattak; Thar Baker; Francis Chow; Babar Shah

doi:10.1109/DICTAP.2016.7543996

Micro-context recognition of sedentary behaviour using smartphone

Muhammad Fahim, Asad Masood Khattak, Thar Baker, Francis Chow, Babar Shah

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	2016 6th International Conference on Digital Information and Communication Technology and Its Applications, DICTAP 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	30-34
Number of pages	5
ISBN (Electronic)	9781467396097
DOIs	https://doi.org/10.1109/DICTAP.2016.7543996
Publication status	Published - 18 Aug 2016
Externally published	Yes
Event	6th International Conference on Digital Information and Communication Technology and Its Applications, DICTAP 2016 - Konya, Turkey Duration: 21 Jul 2016 → 23 Jul 2016

Publication series

Name	International Conference on Digital Information and Communication Technology and Its Applications: Proceedings
Publisher	IEEE

Conference

Conference	6th International Conference on Digital Information and Communication Technology and Its Applications, DICTAP 2016
Country/Territory	Turkey
City	Konya
Period	21/07/2016 → 23/07/2016

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.

Keywords

k-NN
Micro-context Recognizer
Sedentary behaviour
Smartphone

ASJC Scopus subject areas

Signal Processing
Information Systems
Computer Science Applications

Access to Document

10.1109/DICTAP.2016.7543996Licence: Unspecified

Cite this

Fahim, M., Khattak, A. M., Baker, T., Chow, F., & Shah, B. (2016). Micro-context recognition of sedentary behaviour using smartphone. In 2016 6th International Conference on Digital Information and Communication Technology and Its Applications, DICTAP 2016 (pp. 30-34). Article 7543996 (International Conference on Digital Information and Communication Technology and Its Applications: Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DICTAP.2016.7543996

Fahim, Muhammad ; Khattak, Asad Masood ; Baker, Thar et al. / Micro-context recognition of sedentary behaviour using smartphone. 2016 6th International Conference on Digital Information and Communication Technology and Its Applications, DICTAP 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 30-34 (International Conference on Digital Information and Communication Technology and Its Applications: Proceedings).

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title = "Micro-context recognition of sedentary behaviour using smartphone",

abstract = "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.",

keywords = "k-NN, Micro-context Recognizer, Sedentary behaviour, Smartphone",

author = "Muhammad Fahim and Khattak, \{Asad Masood\} and Thar Baker and Francis Chow and Babar Shah",

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year = "2016",

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doi = "10.1109/DICTAP.2016.7543996",

language = "English",

series = "International Conference on Digital Information and Communication Technology and Its Applications: Proceedings",

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Fahim, M, Khattak, AM, Baker, T, Chow, F & Shah, B 2016, Micro-context recognition of sedentary behaviour using smartphone. in 2016 6th International Conference on Digital Information and Communication Technology and Its Applications, DICTAP 2016., 7543996, International Conference on Digital Information and Communication Technology and Its Applications: Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 30-34, 6th International Conference on Digital Information and Communication Technology and Its Applications, DICTAP 2016, Konya, Turkey, 21/07/2016. https://doi.org/10.1109/DICTAP.2016.7543996

Micro-context recognition of sedentary behaviour using smartphone. / Fahim, Muhammad; Khattak, Asad Masood; Baker, Thar et al.
2016 6th International Conference on Digital Information and Communication Technology and Its Applications, DICTAP 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 30-34 7543996 (International Conference on Digital Information and Communication Technology and Its Applications: Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - 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.

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Fahim M, Khattak AM, Baker T, Chow F, Shah B. Micro-context recognition of sedentary behaviour using smartphone. In 2016 6th International Conference on Digital Information and Communication Technology and Its Applications, DICTAP 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 30-34. 7543996. (International Conference on Digital Information and Communication Technology and Its Applications: Proceedings). doi: 10.1109/DICTAP.2016.7543996

Micro-context recognition of sedentary behaviour using smartphone

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this