Study on non-contact vital-sign extraction and applications using 60-GHz FMCW radar

Abstract

In this dissertation, the methods of extracting vital-signs from the FMCW radar are proposed, and its applications are described. The FMCW radar can detect not only distance of a target, but also the micro-displacement in the target. Furthermore, owing to the small-size packaging and low power-consumption, the FMCW radar has been used for vital-sign monitoring. The vital-sign extraction from the FMCW radar signal mainly consists of spectral decomposition and range-bin selection. After the demodulation process, the intermediate frequency (IF) signal is calculated. The frequency of the IF signal corresponds to the range of a target. Discrete Fourier transform is used to decompose the IF signal. The magnitude and phase of each range-bin (or spectral-bin) are linearly proportionate to the micro-displacement. In measuring the vital-signs, the body movement occurred by the respiration and heartbeat is the micro-displacement, and the movement is reflected in the magnitude and phase. To extract vital-signs, selecting the range-bin containing the vital-signs is necessary. I proposed three indices for the range-bin selection : magnitude-phase coherency (MPC), spatial phase coherency (SPC), and temporal phase coherency (TPC). The MPC index quantified the coherency between the magnitude and phase. The SPC index evaluated the coherency between the phase over the various range-bins. The TPC index measured the coherency between the phase, and the phase shifted by its average-period, which can quantify the repetitive and regular beats of heart, sinus rhythm. The vital-sign rates extracted by the proposed methods were more accurate than those extracted by conventional methods. By utilizing the proposed methods of vital-sign extraction, various user-monitoring applications were devised. Human-target is differentiated by the objects in that body movement is occurred by the vital-signs. The property was used to detect human-target in vehicle and hospital situations. Moreover, the proposed methods were applied to extract respiratory signal from the subjects during sleep and infants. The respiratory signal extracted from the subjects during sleep were accurate compared with the contact-type respiration-sensor, and the unique characteristics of respiration in the infants were observed.