Classification of human head motion patterns using creeping wave propagations.

Wearable electronics are continually being developed for a multitude of applications like remote health monitoring, personal activity tracking, and gaming. To design efficient wireless communication between multiple on-body devices, propagation models of the human body must be considered. Due to the creeping wave effect of radio waves near a curved surface, the human body itself acts as a channel capable of supporting and affecting wireless signals. The around-head creeping wave propagation behavior of three different frequencies has been investigated. Since these continuous frequency signals are affected by the movements of the human body, their altered signatures are also classifiable as effects of distinct daily activities like eating, drinking, breathing, and speaking. To improve the measurement system for practical operation in the field, the network analyzer is replaced with smaller, cheaper sensor alternatives including narrowband and wideband candidates.