Application of cloud computing in physical activity research

I. Te Hsieh, Chun Yu Chen, Yu Cheng Lin, Jia Yi Li, Chun Ting Lai, Terry B J Kuo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)


Accelerometers-based devices provide a convenient and efficient way to measure the physical activity, but they are not convenient enough for general users. To improve the ease of use, we developed a novel accelerometer-based cloud-computing system that can automatically upload the recorded acceleration data by telemetry to a cloud end server for further analysis. This automatic cloud computing actimeter system is composed of a miniature wireless actimeter (KY9), a router and a cloud server. The KY9, taped on the body of the users, senses the bodily tri-axis acceleration signals. The acquired acceleration signals are automatically and wirelessly transmitted to the router, which in turn are automatically uploaded to the cloud server. Finally the data are stored and analyzed in the cloud server. The cloud server contains several linear and non-linear analyses for the acceleration signals and further provides quantitative information for exercise and sleep. The users or the investigators can view the analysis results through a standard web browser without installing additional application programs. The system is characteristic of miniature terminal, automatic wireless transmission, long-term recording and on-line analysis. The cloud platform enables accelerometers to be applied in the field of healthcare, and the automatic wireless transmission greatly improves convenience for both the users and the investigators.

Original languageEnglish
Title of host publicationIEEE SENSORS 2012 - Proceedings
Publication statusPublished - 2012
Externally publishedYes
Event11th IEEE SENSORS 2012 Conference - Taipei, Taiwan
Duration: Oct 28 2012Oct 31 2012


Conference11th IEEE SENSORS 2012 Conference

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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