Overview of vital sign detection-simulation and measurements

Commercial EM software packages are not suitable to detect cardiac and respiratory motion of the chest cavity, crucial to vital sign detection, in the study of electromagnetic (EM) wave interaction with tissues using utilized phantom models. The tissue constitutive parameters are time dependent, and are strong function of the volume and physical composition of the tissue layers near the surface due to the associated physiological motion. In this paper, we consider a human body phantom model that includes physiological motion, and a state-space method to extract cardiac and respiration rates. The method is applied to simulated data as well as 3 GHz UWB radar measurements on a sedentary subject. It is shown that the state-space method accurately estimates vital signs without producing harmonics and inter-modulation products that plague signal resolution in commonly used auto-correlated FFT spectrograms relying on peak detection with errors less than 2%.