Robust Cardiac Rate Detection of an Individual

Radar devices can be used to monitor vital signs, such as respiratory and cardiac rates. For this purpose, the phase of an echo signal received from the chest or back of a human is usually used; subsequently, respiratory rate detection (RRD) and cardiac rate detection (CRD) can be achieved by estimating two fundamental frequencies corresponding to the respiratory and cardiac rates, respectively. However, the interference caused by undesirable terms would inevitably be induced in an echo signal; thus, the cardiac rate information contained in the phase of the received signal is often smeared and destroyed. Among several sources of interference such as high-order harmonics of respiratory rate, random body movement of an individual, and system noise, the body movement of an individual is the most critical for reliable CRD, making it a very challenging task. To address this problem, we herein propose a new framework comprising four steps: 1) RRD via differentiation and spectrum analysis for an unwrapped phase of received signal, 2) coarse detection of cardiac rate candidates, 3) selection of three promising candidates for the desired cardiac rate based on a histogram of several candidates, and 4) determination of the desired cardiac rate via a fuzzy logic rule-based method. In experiments using 7.29 GHz impulse-radio ultrawideband radar hardware, we observed that our proposed framework is capable of performing accurate and robust real-time CRD even in the presence of body movement.