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SUPAR: Smartphone as a ubiquitous physical activity recognizer for u-healthcare services

Authors
Fahim M.Lee S.Yoon Y.
Issue Date
Aug-2014
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014, pp.3666 - 3669
Journal Title
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
Start Page
3666
End Page
3669
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/5784
DOI
10.1109/EMBC.2014.6944418
ISSN
0000-0000
Abstract
Current generation smartphone can be seen as one of the most ubiquitous device for physical activity recognition. In this paper we proposed a physical activity recognizer to provide u-healthcare services in a cost effective manner by utilizing cloud computing infrastructure. Our model is comprised on embedded triaxial accelerometer of the smartphone to sense the body movements and a cloud server to store and process the sensory data for numerous kind of services. We compute the time and frequency domain features over the raw signals and evaluate different machine learning algorithms to identify an accurate activity recognition model for four kinds of physical activities (i.e., walking, running, cycling and hopping). During our experiments we found Support Vector Machine (SVM) algorithm outperforms for the aforementioned physical activities as compared to its counterparts. Furthermore, we also explain how smartphone application and cloud server communicate with each other. © 2014 IEEE.
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