Identifying typical physical activity on smartphone with varying positions and orientations

	Identifying typical physical activity on smartphone with varying positions and orientations
	Fen Miao; Yi He; Jinlei Liu; Ye Li; Idowu Ayoola
刊名	Biomedical Engineering Online
	2015
英文摘要	Background: Traditional activity recognition solutions are not widely applicable due to a high cost and inconvenience to use with numerous sensors. This paper aims to automatically recognize physical activity with the help of the built-in sensors of the widespread smartphone without any limitation of firm attachment to the human body. Methods: By introducing a method to judge whether the phone is in a pocket, we investigated the data collected from six positions of seven subjects, chose five signals that are insensitive to orientation for activity classification. Decision trees (J48), Naive Bayes and Sequential minimal optimization (SMO) were employed to recognize five activities: static, walking, running, walking upstairs and walking downstairs. Results: The experimental results based on 8,097 activity data demonstrated that the J48 classifier produced the best performance with an average recognition accuracy of 89.6% during the three classifiers, and thus would serve as the optimal online classifier. Conclusions: The utilization of the built-in sensors of the smartphone to recognize typical physical activities without any limitation of firm attachment is feasible.
收录类别	SCI
原文出处	http://www.biomedcentral.com/content/pdf/s12938-015-0026-4.pdf
语种	英语
内容类型	期刊论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/7043]
专题	深圳先进技术研究院_医工所
作者单位	Biomedical Engineering Online
推荐引用方式 GB/T 7714	Fen Miao,Yi He,Jinlei Liu,et al. Identifying typical physical activity on smartphone with varying positions and orientations[J]. Biomedical Engineering Online,2015.
APA	Fen Miao,Yi He,Jinlei Liu,Ye Li,&Idowu Ayoola.(2015).Identifying typical physical activity on smartphone with varying positions and orientations.Biomedical Engineering Online.
MLA	Fen Miao,et al."Identifying typical physical activity on smartphone with varying positions and orientations".Biomedical Engineering Online (2015).