Application of cloud computing in physical activity research

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.