Movement Detection of Human Body Segments: Passive radio-frequency identification and machine-learning technologies

Abstract

Movement detection of human body segments is a fertile research topic in human-computer interaction, as well as in medical and entertainment applications. In spite of the fact that most of the current methods to track motion are based on optoelectronic systems and wearable inertial sensors, promising solutions could spring from the application of passive radio-frequency identification (RFID) technology. When the human body's limbs move within an electromagnetic field radiated by an interrogating antenna, a movement-dependent modulation of the backscattered field is sensed by the remote receiver. The collected signals, properly conditioned by wearable electromagnetic markers (tags), may therefore carry intrinsic information about human motion.