Remote Sensing For Vital Signs Monitoring Using Advanced Radar Signal Processing Techniques

In the past half century, low-power wireless signals from portable radar sensors, initially continuous-wave (CW) radars and more recently ultra-wideband (UWB) radar systems, have been successfully used to detect physiological movements of stationary human beings.

The thesis starts with a careful review of existing signal processing techniques and state of the art methods possible for vital signs monitoring using UWB impulse systems. Then an in-depth analysis of various approaches is presented.

Robust heart-rate monitoring methods are proposed based on a novel result: spectrally the fundamental heartbeat frequency is respiration-interference-limited while its higher-order harmonics are noise-limited. The higher-order statistics related to heartbeat can be a robust indication when the fundamental heartbeat is masked by the strong lower-order harmonics of respiration or when phase calibration is not accurate if phase-based method is used. Analytical spectral analysis is performed to validate that the higher-order harmonics of heartbeat is almost respiration-interference free. Extensive experiments have been conducted to justify an adaptive heart-rate monitoring algorithm. The scenarios of interest are, 1) single subject, 2) multiple subjects at different ranges, 3) multiple subjects at same range, and 4) through wall monitoring.

A remote sensing radar system implemented using the proposed adaptive heart-rate estimation algorithm is compared to the competing remote sensing technology, a remote imaging photoplethysmography system, showing promising results.

State of the art methods for vital signs monitoring are fundamentally related to process the phase variation due to vital signs motions. Their performance are determined by a phase calibration procedure. Existing methods fail to consider the time-varying nature of phase noise. There is no prior knowledge about which of the corrupted complex signals, in-phase component (I) and quadrature component (Q), need to be corrected. A precise phase calibration routine is proposed based on the respiration pattern. The I/Q samples from every breath are more likely to experience similar motion noise and therefore they should be corrected independently. High slow-time sampling rate is used to ensure phase calibration accuracy. Occasionally, a 180-degree phase shift error occurs after the initial calibration step and should be corrected as well. All phase trajectories in the I/Q plot are only allowed in certain angular spaces. This precise phase calibration routine is validated through computer simulations incorporating a time-varying phase noise model, controlled mechanic system, and human subject experiment.