Accurate Detection of Doppler Cardiograms With a Parameterized Respiratory Filter Technique Using a K-Band Radar Sensor

Cardiogram is one of the most important factors for health assessment. As a new expression of cardiograms, the Doppler cardiograms (DCGs) detected remotely via Doppler radar sensor (DRS) provide rich details of the heart motion. However, the existing techniques for measurement of DCG requires that the subject holds his/her breath to avoid the disturbance caused by respiration. To realize the accurate detection of DCGs in the presence of respiration, a high-linearity $K$ -band dc-coupled continuous-wave (CW) DRS with digital dc-tuning function was custom-designed and a novel parameterized respiratory filter (PRF) algorithm was proposed to precisely remove the respiratory signal. Both simulation and experimental results show that the proposed PRF algorithm has better DCG extraction performance than the conventional methods. Furthermore, the experimental results in normal and clinical environments show that the grained differential DCG (D-DCG) has promising potential in professional heart rate variability (HRV) analysis and heart diseases diagnosis, which means the proposed DCGs detection has the potential to be a convenient, comfortable, and reliable way for daily and clinical heart health assessment.