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

Walls of Identities. Built environment as Social Marker

info:eu-repo/semantics/publishe

Arab settlements: tribal structures and spatial organizations in the Middle East between Hellenistic and Early Islamic periods

info:eu-repo/semantics/publishe

Organizzazione spaziale e strutture sociali nel Medio-Oriente Tardo Bizantino e Primo Islamico (V-VII SEC.)

info:eu-repo/semantics/publishe

Semi-urban or semi-rural settlements: a new definition of urban centres

info:eu-repo/semantics/publishe

The Different Fates of Architectures

This paper aims to problematize the issue of reuse and reoccupation of architectures and building materials in the Near East. So far, the vast majority of research and published work dealing with this topic (not only in the field of Islamic Archaeology and Art History) have focused on the monumental complexes of urban centres. In this framework, the concept of spolia has been at the centre of a long and still heated transdisciplinary debate. Vernacular architecture and rural contexts have, for the most part, been neglected. Frequent episodes of reoccupation of earlier structures, even if thoroughly described in archaeological reports are almost automatically branded as the result of pragmatic behaviour of local communities benefitting from the availability of abundant building materials from ruined structures. However, the vast number of ways in which reuse and reoccupation might have occurred is often overlooked. Even conceding that most of the evidence is likely due to some form or other of “pragmatism,” the different ways in which these appear need to be more fully explained and interpreted. This paper, which builds on existing scholarship of reuse and reoccupation, argues for a rethinking of the methodology. Other experiences, most notably those investigating the late Antique and early Medieval western Mediterranean, provide a useful point of reference for where to start the discussion. This paper will demonstrate how extending the perspective from the single building to the broader context, including the surrounding landscape, is ultimately the only way to fully comprehend the archaeological evidence and possibly better understand and explain the different “fates” of architectures.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

A Machine Learning Approach to Monitor the Emergence of Late Intrauterine Growth Restriction

Late intrauterine growth restriction (IUGR) is a fetal pathological condition characterized by chronic hypoxia secondary to placental insufficiency, resulting in an abnormal rate of fetal growth. This pathology has been associated with increased fetal and neonatal morbidity and mortality. In standard clinical practice, late IUGR diagnosis can only be suspected in the third trimester and ultimately confirmed at birth. This study presents a radial basis function support vector machine (RBF-SVM) classification based on quantitative features extracted from fetal heart rate (FHR) signals acquired using routine cardiotocography (CTG) in a population of 160 healthy and 102 late IUGR fetuses. First, the individual performance of each time, frequency, and nonlinear feature was tested. To improve the unsatisfactory results of univariate analysis we firstly adopted a Recursive Feature Elimination approach to select the best subset of FHR-based parameters contributing to the discrimination of healthy vs. late IUGR fetuses. A fine tuning of the RBF-SVM model parameters resulted in a satisfactory classification performance in the training set (accuracy 0.93, sensitivity 0.93, specificity 0.84). Comparable results were obtained when applying the model on a totally independent testing set. This investigation supports the use of a multivariate approach for the in utero identification of late IUGR condition based on quantitative FHR features encompassing different domains. The proposed model allows describing the relationships among features beyond the traditional linear approaches, thus improving the classification performance. This framework has the potential to be proposed as a screening tool for the identification of late IUGR fetuses

An Efficient Algorithm for the Extraction of Fetal ECG from Standard and Non-Standard Multi Abdominal Maternal Leads

The importance of fetal surveillance during pregnancy is worldwide accepted since its peculiar ability to anticipate fetal distress under a variety of conditions. The novel frontier in the field of remote fetal monitoring relies on a continuous and everyday-monitoring of fetal wellbeing. As a consequence, fECG monitoring systems have seen a net increase in popularity in the recent years. In this paper, we propose a novel algorithm for the detection of fECG and we validated its performances by testing it on an open source collection of 75 annotated fECG traces. Our results show the reliability of the proposed methodology in extracting fECG and deriving an estimate of fHR

Dataset on linear and non-linear indices for discriminating healthy and IUGR fetuses

The presented collection of data comprises of a set of 12 linear and nonlinear indices computed at different time scales and extracted from Fetal Heart Rate (FHR) traces acquired through Hewlett Packard CTG fetal monitors (series 1351A), connected to a PC. The sampling frequency of the recorded FHR signal is equal 2 Hz. The recorded populations consist of two groups of fetuses: 60 healthy and 60 Intra Uterine Growth Restricted (IUGR) fetuses. IUGR condition is a fetal condition defined as the abnormal rate of fetal growth. In clinical practice, diagnosis is confirmed at birth and may only be suspected during pregnancy. The pathology is a documented cause of fetal and neonatal morbidity and mortality. The described database was employed in a set of machine learning approaches for the early detection of the IUGR condition: “Integrating machine learning techniques and physiology based heart rate features for antepartum fetal monitoring” [1]. The added value of the proposed indices is their interpretability and close connection to physiological and pathological aspect of FHR regulation. Additional information on data acquisition, feature extraction and potential relevance in clinical practice are discussed in [1]