Random Body Movement Removal Using Adaptive Motion Artifact Filtering in mmWave Radar-Based Neonatal Heartbeat Sensing

Abstract

In response to the pressing requirement for prompt and precise heart rate acquisition during neonatal resuscitation, an adaptive motion artifact filter (AMF) is proposed in this study, which is based on the continuous wavelet transform (CWT) approach and takes advantage of the gradual, time-based changes in heart rate. This method is intended to alleviate the pronounced interference induced by random body movement (RBM) on radar detection in neonates. The AMF analyzes the frequency components at different time points in the CWT results. It extracts spectral peaks from each time slice of the frequency spectrum and correlates them with neighboring peaks to identify the existing components in the signal, thereby reducing the impact of RBM and ultimately extracting the heartbeat component. The results demonstrate a reliable estimation of heart rates. In practical clinical settings, we performed measurements on multiple neonatal patients within a hospital environment. The results demonstrate that even with limited data, its accuracy in estimating the resting heart rate of newborns surpasses 97%, and during infant movement, its accuracy exceeds 96%.