Extracting Cardiac Information From Medical Radar Using Locally Projective Adaptive Signal Separation - Yao, Yu; Sun, Guanghao; Kirimoto, Tetsuo; Schiek, Michael (Frontiers in Physiology, 2019)
Electrocardiography is the gold standard for electrical heartbeat activity, but offers no direct measurement of mechanical activity. Mechanical cardiac activity can be assessed non-invasively using e.g. ballistocardiography and recently, medical radar has emerged as a contactless alternative modality. However, all modalities for measuring the mechanical cardiac activity are affected by respiratory movements, requiring a signal separation step before higher level analysis can be performed. This paper adapts a nonlinear filter for separating the respiratory and cardiac signal components of radar recordings. In addition, we present an adaptive algorithm for estimating the parameters for the nonlinear filter. Using the two example analysis tasks of cardiac template extraction from radar and peak timing analysis, we demonstrate that the nonlinear filter combined with adaptive parameter estimation delivers superior results compared to linear filtering. Our analysis suggests that the improvement is due to better preservation of the cardiac signal morphology by the nonlinear signal separation method. Hence, we expect that the nonlinear signal separation method introduced in this paper will mostly benefit analysis task investigating the cardiac radar signal morphology on a beat-to-beat basis.