Human action classification for a small size physical condition monitoring system

In order to maintain our healthcare, daily monitoring our physical condition is very important. A multiple microelectromechanical system (MEMS) based monitoring system has been developed. The MEMS based monitoring system is developed for aiming noninvasive and unconstrained monitoring to our physical condition. From a viewpoint of the hardware, the smaller size of such monitoring system is better for us. Additionally, the smaller size is better for power consumption. Therefore, we need to design and develop a very small size of monitoring software. Two-step abstraction method for estimating human behavior had been proposed. In this paper, we propose an extended method of the two-step abstraction for ultra-small hardwares.