Sparse Non-Contact Multiple People Localization and Vital Signs Monitoring Via FMCW Radar
Yonathan Eder (Weizmann Institute of Science); Zhuoyang Liu (Weizmann Institute of Science); Yonina Eldar ()
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Non-contact vital signs monitoring (NCVSM) of multiple people is becoming a necessity in healthcare due to increasing morbidity and manpower shortage. In meeting these requirements, frequency modulated continuous wave (FMCW) radars have shown great potential. However, current techniques present difficulties in locating and monitoring humans in noisy environments containing multiple objects. In this work, we first develop a model for NCVSM of multiple people via FMCW radar, based on a single-input-multiple-output setup. By considering the sparse nature of the modeled signals along with human-typical cardiopulmonary characteristics, we provide a joint-sparse recovery mechanism to accurately localize targets in a clutter-rich scenario where existing techniques struggle. Then, we present a robust method for NCVSM of the found individuals, with improved performance results when compared to current NCVSM techniques using several statistical metrics. Our approach offers excellent performance in a medical application where high accuracy is required.