Entropy Information of Cardiorespiratory Dynamics in Neonates during Sleep

Abstract: Sleep is a central activity in human adults and characterizes most of the newborn infant life. During sleep, autonomic control acts to modulate heart rate variability (HRV) and respiration. Mechanisms underlying cardiorespiratory interactions in different sleep states have been studied but are not yet fully understood. Signal processing approaches have focused on cardiorespiratory analysis to elucidate this co-regulation. This manuscript proposes to analyze heart rate (HR), respiratory variability and their interrelationship in newborn infants to characterize cardiorespiratory interactions in different sleep states (active vs. quiet). We are searching for indices that could detect regulation alteration or malfunction, potentially leading to infant distress. We have analyzed inter-beat (RR) interval series and respiration in a population of 151 newborns, and followed up with 33 at 1 month of age. RR interval series were obtained by recognizing peaks of the QRS complex in the electrocardiogram (ECG), corresponding to the ventricles depolarization. Univariate time domain, frequency domain and entropy measures were applied. In addition, Transfer Entropy was considered as a bivariate approach able to quantify the bidirectional information flow from one signal (respiration) to another (RR series). Results confirm the validity of the proposed approach. Overall, HRV is higher in active sleep, while high frequency (HF) power characterizes more quiet sleep. Entropy analysis provides higher indices for SampEn and Quadratic Sample entropy (QSE) in quiet sleep. Transfer Entropy values were higher in quiet sleep and point to a major influence of respiration on the RR series. At 1 month of age, time domain parameters show an increase in HR and a decrease in variability. No entropy differences were found across ages. The parameters employed in this study help to quantify the potential for infants to adapt their cardiorespiratory responses as they mature. Thus, they could be useful as early markers of risk for infant cardiorespiratory vulnerabilities

Characterization of cardiorespiratory phase synchronization and directionality in late premature and full term infants

Objective: Though the mutual influence of cardiovascular and respiratory rhythms in healthy newborns has been documented, its full characterization is still pending. In general, the activity of many physiological subsystems has a well-expressed rhythmic character, and often an interdependency between physiological rhythms emerges early in development. Traditional methods of data analysis only address the quantification of the strength of subsystem interactions. In this work, we will investigate system interrelationships in terms of the possible presence of causal or directional interplays. Approach: In this paper, we propose a methodological application that quantifies phase coupling and its directionality in a population of newborn infants born between 35 and 40 weeks of gestational age (GA). The aim is to assess whether GA at birth significantly influences the development of phase synchronization and the directionality of the coupling between the cardiovascular and respiratory system activity. Several studies indicating irregular cardiorespiratory coupling as a leading cause of several pathologies underscore the need to investigate this phenomenon in this at-risk population. Main results: Results from our investigation show a different directionality profile as a function of GA and sleep state. Significance: These findings are a contribution to the understanding of higher risk for the documented negative outcomes in the late preterm population. Moreover, these parameters could provide a tool for the development of early markers of cardiorespiratory dysregulation in infants

Multi-parametric cardiorespiratory analysis in late-preterm, early-term, and full-term infants at birth

Infants born at 35–37 weeks’ gestational age (GA) are at higher risk for a range of pathological conditions and poorer neurodevelopmental outcomes. However, mechanisms responsible are not fully understood. The purpose of this paper is to use traditional and novel techniques to assess newborn autonomic development as a function of GA at birth, focusing on cardiorespiratory regulation. ECG and respiration were acquired during sleep on 329 healthy newborns. Infants were divided into GA groups: 35–36 weeks (late preterm (LPT)), 37–38 weeks (early term (ET)), and 39–40 weeks (full term (FT)). Time domain, frequency domain, and non-linear measures were calculated. Increased heart rate short-term variability and complexity as a function of GA were observed in time domain and non-linear measures. Decreasing inter-breath interval variability was found as a function of GA, with increasing linear cardiorespiratory coupling. A complexity parameter (quadratic sample entropy) was less affected by arrhythmias and artifacts when compared to traditional measures. Results suggest lower maturation in LPT, with less developed cardiorespiratory regulation. This may confer risk for altered outcome, convergent with epidemiological findings. Reported examples show that a combination of methodological approaches can be beneficial to characterize autonomic maturation. [Figure not available: see fulltext.

Cardio-respiratory phase locking in newborn and one month infants as a function of sleep state

Respiratory and cardiac rhythms of newborn infants have been extensively investigated, in order to highlight pathological conditions. Nonetheless, given their tight dependency, methods observing their interactions could provide further insight. This study investigates the phase synchronization of heart rate (HR) and respiration in a group of healthy newborn and one month infants. Synchronous epochs of different n:m orders are identified (n cardiac : m respiratory cycles). Synchrograms provide their graphical representation while λ is an index of circular variance. Differences between epochs of quiet and active sleep and between newborn and one month infants are observed. Results show that the percentage of time spent in synchronization and the average length of periods of synchronization significantly increase during quiet sleep, both for the newborn and the one month infants. In Sudden Infant Death Syndrome (SIDS) the occurrence of infant distress generated by uncoupled cardio-respiratory response has been hypothesized. This confirms the relevance of the proposed analysis and results

Transfer Entropy Modeling of Newborn Cardiorespiratory Regulation

3Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano, Milan, Italy This study investigates the complex interplay between the cardiac and respiratory systems in 268 healthy neonates born between 35 and 40 weeks of gestation. The aim is to provide a comprehensive description of the developing cardiorespiratory information transfer mechanisms as a function of gestational age (GA). This report proposes an extension of the traditional Transfer Entropy measure (TE), which employs multiple lagged versions of the time series of the intervals between two successive R waves of the QRS signal on the electrocardiogram (RR series) and respiration time series (RESP). The method aims to quantify the instantaneous and delayed effects between the two processes within a fine-grained time scale. Firstly, lagged TE was validated on a simulated dataset. Subsequently, lagged TE was employed on newborn cardiorespiratory data. Results indicate a progressive increase in information transfer as a function of gestational age, as well as significant differences in terms of instantaneous and delayed interactions between the cardiac and the respiratory system when comparing the two TE directionalities (RR→RESP vs. RESP→RR). The proposed investigation addresses the role of the different autonomic nervous system (ANS) branches involved in the cardiorespiratory system, since the sympathetic and parasympathetic branches operate at different time scales. Our results allow to infer that the two TE directionalities are uniquely and differently modulated by both branches of the ANS. TE adds an original quantitative tool to understanding cardiorespiratory imbalance in early infanc