Human Movement Detection using Attitude and Heading Reference System

George K. Fourlas, Ilias Maglogiannis

Abstract:Among different types of human movement, falls are the most important since they related with high social and economic costs. Falls can cause various unintentional injuries such as fractures or in the worst-case scenario even lead to death, elderly citizen. Wearable devices present a growing interest in health care applications since they can detect signals of human activity and continuously monitoring critical parameters, offering a reliable and inexpensive solution. In this paper, an attitude and heading reference system - inertial measurement unit (IMU) is used in order to detect human movement and especially different type of falls.