A 1-D block processing for non-invasive detection of 2-D cardiac and respiratory rates

Non-invasive measurement of vital signs (circulatory and respiratory physiological movements of the thorax) using Doppler radar is important to rescue missions (e.g., extricating survivors from wreckage, earthquake rubble etc.). A major challenge for biomedical radar systems is detecting the heartbeat of a subject with high accuracy. A novel algorithm based on one-dimensional (1-D) block processing state-space method (SSM) is considered in this paper to extract vital signs from data measured on a human subject using UWB radar. The 1-D block processing SSM produces range/Doppler-dependent system poles uniquely identified in a parametric manner with signal peaks at the cardiac and respiratory frequencies. It is shown that accurate estimates of vital signs can be obtained without producing high harmonics and inter-modulation products that plague signal resolution in 2-D FFT images.