Abstract
Most of the current methods to identify sedentary take time as a major parameter, this methods are too simple and cannot make people intuitively understand their sedentary situation. A number of studies have shown that standing up and doing some activity can have a good effect on relieving the sedentary condition, and changing sitting postures also do the same work, and even mildly movement can be beneficial for relieving sedentary condition. This paper propose a quantitative system of sedentary condition based on wireless body area network. In the process of identifying the sedentary condition, we consider not only the sedentary time, but also the time they are not on chairs, the number of times they leave chairs and the change amount of sitting postures. Then we also grade the sedentary level by the above parameters. Finally we display the data of the sedentary time, the time they are not on chairs, the number of times they leave chairs, the change amount of sitting postures and the sedentary level. So it can make people intuitively understand of their sedentary condition. Experiment results show that the algorithm is reasonable and it can identify people’s sedentary condition effectively.
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Acknowledgment
At first, i want to take this chance to thanks to my tutor Wenfeng Li. In the process of composing this paper, he gives me much academic and constructive advice, and helps me to correct my paper. My great gratitude also goes to some of my friends and classmates who have selfless and generously helped me with my paper.
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Li, X., Ge, Y., Li, W., Ma, C. (2018). A Quantitative System of Sedentary Condition Based on Wireless Body Area Network. In: Fortino, G., Ali, A., Pathan, M., Guerrieri, A., Di Fatta, G. (eds) Internet and Distributed Computing Systems. IDCS 2017. Lecture Notes in Computer Science(), vol 10794. Springer, Cham. https://doi.org/10.1007/978-3-319-97795-9_11
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DOI: https://doi.org/10.1007/978-3-319-97795-9_11
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