Radarcardiograph Signal Modeling and Time-Frequency Analysis

Abstract

In this paper, we delve deeper into recent advancements in radar based biomedical measurements that capture fine movements associated with human heart sounds. We call this measurement the Radarcardiograph (RCG). We analyze the RCG of three subjects to identify distinguishing time and frequency components of the signal. We introduce a parametric signal model as a function of the identified characteristic features. From there, we simultaneously collect and time synchronize the RCG with conventional contact based cardiac interval measurements. We then compare these signals using the Short Time Fourier Transform (STFT), Continuous Wavelet Transform (CWT) and Cochleogram (CLG) for time-frequency analysis. We comment on the similarities and difference of the signals, using the model as reference. Our results improve current understanding of radar based heart sound measurements and provide further validation that radar can be used for non-contact technology heart sound monitoring. We identify limitations in radar based heart sounds measurements. Namely, limited signal quality in the wireless channel, reduced recovered frequency range and weak high frequency components. However, such problem can be addressed via advanced denoising algorithms and system level optimization.