Motion capture and activity tracking using smartphone-driven body sensor networks

Because of advances in inertial microelectronics and mobile computing technologies, highly accurate sensor hardware has become ubiquitous in modern smartphones. This paper introduces a framework that networks smartphone devices to produce body sensor networks for motion capture and activity tracking application areas. Data is transferred in real-time using the motion cloud, an online gateway and storehouse for inertial data. The goal of this research is to present a modular methodology for amalgamating smartphone sensor data within a centralized repository that is suitable for experimental research. The proposed framework explores solutions for sensor fusion, data synchronization, data streaming and remote control functionality in smartphones. To demonstrate sensing accuracy, three devices are strapped to the motion performer´s arm to record the articulated motion of a hand wave gesture. To demonstrate continuous sensing, two devices are networked for a period of two hours to identify differences between sedentary and active comnortments.