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Smart chair for monitoring of sitting behavior

Huang, Mengjie, Gibson, Ian and Yang, Rui 2017, Smart chair for monitoring of sitting behavior, in DesTech 2016: Proceedings of the International Conference on Design and Technology, Knowledge E, Dubai, U.A.E., pp. 274-280, doi: 10.18502/keg.v2i2.626.

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Title Smart chair for monitoring of sitting behavior
Author(s) Huang, Mengjie
Gibson, IanORCID iD for Gibson, Ian orcid.org/0000-0002-4149-9122
Yang, Rui
Conference name Design and Technology. International Conference (2016 : Geelong, Victoria)
Conference location Geelong, Victoria
Conference dates 2016/12/05 - 2016/12/08
Title of proceedings DesTech 2016: Proceedings of the International Conference on Design and Technology
Editor(s) Collins, PaulORCID iD for Collins, Paul orcid.org/0000-0003-3308-8689
Gibson, IanORCID iD for Gibson, Ian orcid.org/0000-0002-4149-9122
Publication date 2017
Conference series Design and Technology International Conference
Start page 274
End page 280
Total pages 7
Publisher Knowledge E
Place of publication Dubai, U.A.E.
Keyword(s) sitting behavior
smart chair
classification
Summary Sitting is a common behavior of human body in daily life. It is found that poor sitting postures can link to pains and other complications for people in literature. In order to avoid the adverse effects of poor sitting behavior, we have developed a highly practical design of smart chair system in this paper, which is able to monitor the sitting behavior of human body accurately and non-invasively. The pressure patterns of eight standardized sitting postures of human subjects were acquired and transmitted to the computer for the automatic sitting posture recognition with the application of artificial neural network classifier. The experimental results showed that it can recognize eight sitting postures of human subjects with high accuracy. The sitting posture monitoring in the developed smart chair system can help or promote people to achieve and maintain healthy sitting behavior, and prevent or reduce the chronic disease caused by poor sitting behavior. These promising results suggested that the presented system is feasible for sitting behavior monitoring, which can find applications in many areas including healthcare services, human-computer interactions and intelligent environment.
ISSN 2518-6841
Language eng
DOI 10.18502/keg.v2i2.626
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2017, The Authors
Free to Read? Yes
Use Rights Creative Commons Attribution licence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30104744

Document type: Conference Paper
Collections: School of Engineering
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.