Non-contact Dual Pulse Doppler System Based Real-time Relative Demodulation and Respiratory & Heart Rates Estimations for Chronic Heart Failure Patients

Abstract

Long-term continuous patient monitoring is required in many health systems for monitoring and analytical diagnosing purposes. Most of monitoring systems have shortcomings related to their functionality and/or patient comfortably. Non-contact monitoring systems have been developed to address some of these shortcomings. One of such systems is non-contact physiological vital signs assessments for chronic heart failure (CHF) patients. This paper presents novel real-time demodulation technique and estimations algorithms for the non-contact physiological vital signs assessments for CHF patients based on a patented novel non-contact bio-motion sensor. A database consists of twenty CHF patients with New York Heart Association (NYHA) Heart Failure Classification Class II & III, whose underwent full Polysomnography (PSG) analysis for the diagnosis of sleep apnea, disordered sleep, or both, were selected for the study. The propose algorithms analyze the non-contact bio-motion signals and estimate the patient's respiratory and heart rates. The outputs of the algorithms are compared with gold-standard PSG recordings. Across all twenty CHF patients’ recordings, the respiratory rate estimation median accuracy achieved 91.52% with median error of ±1.31 breaths per minute. The heart rate estimation median accuracy achieved 91.29% with median error of ±6.16 beats per minute. A potential application would be home continuous sleep and circadian rhythm monitoring.