Camera-Based Heart Rate Variability for Estimating the Maturity of Neonatal Autonomic Nervous System

Heart rate variability (HRV) can be used as an effective indicator for the maturity of the neonatal autonomic nervous system (ANS) and some acute neonatal diseases (e.g. respiratory distress syndrome, late-onset sepsis). Advances in contactless sensing technology have led to the rapid development of camera-based physiological monitoring, but few studies have focused on HRV measurement in the Neonatal Intensive Care Unit. This study aims to evaluate the performance of camera-based neonatal HRV monitoring (camera-HRV) using camera–photoplethysmography, and to further investigate the feasibility of applying camera-HRV for tracking ANS maturation through quantitative analysis of 12 HRV indices on quiet infants with limited motions. The clinical experimental results show that as the ANS of newborns matures, the trends of camera-HRV indices are consistent with those obtained by electrocardiogram (ECG) and photoplethysmography (PPG). Furthermore, the performance of camera-HRV in predicting the postmenstrual age of newborns is comparable to that obtained by ECG and PPG, which can predict 63.89% of infants with an accuracy of less than ± 2 weeks. In particular, camera-HRV shows excellent performance in the classification of preterm/term infants, with an optimal accuracy of 0.90 and an F1 score of 0.88. The pilot clinical study suggests that camera-HRV can be a feasible tool for tracking the development of neonatal ANS.