A skewed-Gaussian model for pulse decomposition analysis of photoplethysmography signals.

Pulse decomposition analysis (PDA) has been proposed to extract reliable information from photoplethysmography (PPG) morphology by decomposing the signal in its physiological sub-waves. The Gaussian model has been widely used in the literature, even though it often underperforms because it is limited to symmetric morphologies. More advanced asymmetric models, such as the Gamma model, have been proposed to achieve improved accuracy.

Ethics of Wearable-Based Out-of-Hospital Cardiac Arrest Detection.

Out-of-hospital cardiac arrest is a major health problem, and immediate treatment is essential for improving the chances of survival. The development of technological solutions to detect out-of-hospital cardiac arrest and alert emergency responders is gaining momentum; multiple research consortia are currently developing wearable technology for this purpose. For the responsible design and implementation of this technology, it is necessary to attend to the ethical implications.

Quantitative validation of the suprasternal pressure signal to assess respiratory effort during sleep.

Intra-esophageal pressure (Pes) measurement is the recommended gold standard to quantify respiratory effort during sleep, but used to limited extent in clinical practice due to multiple practical drawbacks. Respiratory inductance plethysmography belts (RIP) in conjunction with oronasal airflow are the accepted substitute in polysomnographic systems (PSG) thanks to a better usability, although they are partial views on tidal volume and flow rather than true respiratory effort and are often used without calibration. In their place, the pressure variations measured non-invasively at the suprasternal notch (SSP) may provide a better measure of effort.

Changes in Maternal Heart Rate Variability and Photoplethysmography Morphology after Corticosteroid Administration: A Prospective, Observational Study.

: Owing to the association between dysfunctional maternal autonomic regulation and pregnancy complications, assessing non-invasive features reflecting autonomic activity-e.g., heart rate variability (HRV) and the morphology of the photoplethysmography (PPG) pulse wave-may aid in tracking maternal health.

Increasing accuracy of pulse arrival time estimation in low frequency recordings.

Wearable devices that measure vital signals using photoplethysmography are becoming more commonplace. To reduce battery consumption, computational complexity, memory footprint or transmission bandwidth, companies of commercial wearable technologies are often looking to minimize the sampling frequency of the measured vital signals. One such vital signal of interest is the pulse arrival time (PAT), which is an indicator of blood pressure.

Rationale and design of the BECA project: Smartwatch-based activation of the chain of survival for out-of-hospital cardiac arrest.

Aim: Out-of-hospital cardiac arrest is a major health problem, and the overall survival rate is low (4.6%-16.4%).

Artificial intelligence based cardiotocogram assessment during labor.

Objective: To assess whether artificial intelligence, inspired by clinical decision-making procedures in delivery rooms, can correctly interpret cardiotocographic tracings and distinguish between normal and pathological events.

Study Design: A method based on artificial intelligence was developed to determine whether a cardiotocogram shows a normal response of the fetal heart rate to uterine activity (UA). For a given fetus and given the UA and previous FHR, the method predicts a fetal heart rate response, under the assumption that the fetus is still in good condition and based on how that specific fetus has responded so far.

A Review on Atrial Fibrillation Detection From Ambulatory ECG.

Atrial fibrillation (AF) is a prevalent clinical arrhythmia disease and is an important cause of stroke, heart failure, and sudden death. Due to the insidious onset and no obvious clinical symptoms of AF, the status of AF diagnosis and treatment is not optimal. Early AF screening or detection is essential.

Maternal cardiorespiratory coupling: differences between pregnant and nonpregnant women are further amplified by sleep-stage stratification.

Pregnancy complications are associated with abnormal maternal autonomic regulation. Subsequently, thoroughly understanding maternal autonomic regulation during healthy pregnancy may enable the earlier detection of complications, in turn allowing for the improved management thereof. Under healthy autonomic regulation, reciprocal interactions occur between the cardiac and respiratory systems, i.

A sleep stage estimation algorithm based on cardiorespiratory signals derived from a suprasternal pressure sensor.

Automatic estimation of sleep structure is an important aspect in moving sleep monitoring from clinical laboratories to people's homes. However, the transition to more portable systems should not happen at the expense of important physiological signals, such as respiration. Here, we propose the use of cardiorespiratory signals obtained by a suprasternal pressure (SSP) sensor to estimate sleep stages.

Fetal electrocardiography and artificial intelligence for prenatal detection of congenital heart disease.

Introduction: This study aims to investigate non-invasive electrocardiography as a method for the detection of congenital heart disease (CHD) with the help of artificial intelligence.

Material And Methods: An artificial neural network was trained for the identification of CHD using non-invasively obtained fetal electrocardiograms. With the help of a Bayesian updating rule, multiple electrocardiographs were used to increase the algorithm's performance.

Evidence and clinical relevance of maternal-fetal cardiac coupling: A scoping review.

Background: Researchers have long suspected a mutual interaction between maternal and fetal heart rhythms, referred to as maternal-fetal cardiac coupling (MFCC). While several studies have been published on this phenomenon, they vary in terms of methodologies, populations assessed, and definitions of coupling. Moreover, a clear discussion of the potential clinical implications is often lacking.

Implementation of the combined use of non-invasive fetal electrocardiography and electrohysterography during labor: A prospective clinical study.

Introduction: Fetal electrocardiography (NI-fECG) and electrohysterography (EHG) have been proven more accurate and reliable than conventional non-invasive methods (doppler ultrasound and tocodynamometry) and are less affected by maternal obesity. It is still unknown whether NI-fECG and EHG will eliminate the need for invasive methods, such as the intrauterine pressure catheter and fetal scalp electrode. We studied whether NI-fECG and EHG can be successfully used during labor.

Automatic signal quality assessment of raw trans-abdominal biopotential recordings for non-invasive fetal electrocardiography.

Wearable monitoring systems for non-invasive multi-channel fetal electrocardiography (fECG) can support fetal surveillance and diagnosis during pregnancy, thus enabling prompt treatment. In these embedded systems, power saving is the key to long-term monitoring. In this regard, the computational burden of signal processing methods implemented for the fECG extraction from the multi-channel trans-abdominal recordings plays a non-negligible role.

Changes in Maternal Heart Rate and Autonomic Regulation following the Antenatal Administration of Corticosteroids: A Secondary Analysis.

While the effect of antenatally administered corticosteroids on fetal heart rate (HR) and heart rate variability (HRV) is well established, little information is available on how these drugs affect maternal physiology. In this secondary analysis of a prospective, observational cohort study, we quantify how corticosteroids affect maternal HR and HRV, which serve as a proxy measure for autonomic regulation. Abdominal ECG measurements were recorded before and in the five days following the administration of betamethasone—a corticosteroid commonly used for fetal maturation—in 46 women with singleton pregnancies.

Extraction of cardiac-related signals from a suprasternal pressure sensor during sleep.

The accurate detection of respiratory effort during polysomnography is a critical element in the diagnosis of sleep-disordered breathing conditions such as sleep apnea. Unfortunately, the sensors currently used to estimate respiratory effort are either indirect and ignore upper airway dynamics or are too obtrusive for patients. One promising alternative is the suprasternal notch pressure (SSP) sensor: a small element placed on the skin in the notch above the sternum within an airtight capsule that detects pressure swings in the trachea.

An Overview of the Sensors for Heart Rate Monitoring Used in Extramural Applications.

This work presents an overview of the main strategies that have been proposed for non-invasive monitoring of heart rate (HR) in extramural and home settings. We discuss three categories of sensing according to what physiological effect is used to measure the pulsatile activity of the heart, and we focus on an illustrative sensing modality for each of them. Therefore, electrocardiography, photoplethysmography, and mechanocardiography are presented as illustrative modalities to sense electrical activity, mechanical activity, and the peripheral effect of heart activity.

Pharmacological cardioversion of supraventricular tachycardia in pregnancy during continuous electrophysiological foetal monitoring: a case report.

Background: Maternal tachycardia is the most frequently occurring cardiac complication during pregnancy. Often administration of drugs is required as a treatment. The drug of choice is intravenously administered adenosine because it is considered safe, though there are limited studies regarding safety for the foetus with the use of adenosine.

Longitudinally Tracking Maternal Autonomic Modulation During Normal Pregnancy With Comprehensive Heart Rate Variability Analyses.

Changes in the maternal autonomic nervous system are essential in facilitating the physiological changes that pregnancy necessitates. Insufficient autonomic adaptation is linked to complications such as hypertensive diseases of pregnancy. Consequently, tracking autonomic modulation during progressing pregnancy could allow for the early detection of emerging deteriorations in maternal health.

Novel Multichannel Entropy Features and Machine Learning for Early Assessment of Pregnancy Progression Using Electrohysterography.

Objective: Preterm birth is the leading cause of morbidity and mortality involving over 10% of infants. Tools for timely diagnosis of preterm birth are lacking and the underlying physiological mechanisms are unclear. The aim of the present study is to improve early assessment of pregnancy progression by combining and optimizing a large number of electrohysterography (EHG) features with a dedicated machine learning framework.

The electrical heart axis of the fetus between 18 and 24 weeks of gestation: A cohort study.

Introduction: A fetal anomaly scan in mid-pregnancy is performed, to check for the presence of congenital anomalies, including congenital heart disease (CHD). Unfortunately, 40% of CHD is still missed. The combined use of ultrasound and electrocardiography might boost detection rates.

Adapted ST analysis during labor: relative versus absolute ST events, a case-control study.

Background: The value of ST analysis of the fetal electrocardiogram during labor to lower asphyxia and cesarean section rates is uncertain. Physiological variation of the electrical heart axis between fetuses may explain false alarms in conventional ST analysis (absolute ST analysis). ST events (alarms) based on relative T/QRS rises (relative ST analysis) correct for this variation and may improve diagnostic accuracy of ST analysis.

Dedicated Algorithm for Unobtrusive Fetal Heart Rate Monitoring Using Multiple Dry Electrodes.

Multi-channel measurements from the maternal abdomen acquired by means of dry electrodes can be employed to promote long-term monitoring of fetal heart rate (fHR). The signals acquired with this type of electrode have a lower signal-to-noise ratio and different artifacts compared to signals acquired with conventional wet electrodes. Therefore, starting from the benchmark algorithm with the best performance for fHR estimation proposed by Varanini et al.

Changes in Maternal Heart Rate Variability in Response to the Administration of Routine Obstetric Medication in Hospitalized Patients: Study Protocol for a Cohort Study (MAMA-Heart Study).

Pregnancy is a period of continuous change in the maternal cardiovascular system, partly mediated by the autonomic nervous system. Insufficient autonomic adaptation to increasing gestation is associated with pregnancy complications, such as hypertensive disorders of pregnancy and preterm birth (both major causes of perinatal morbidity and mortality). Consequently, maternal heart rate variability (mHRV), which is a proxy measure for autonomic activity, is increasingly assessed in these cohorts to investigate the pathophysiology of their complications.

Non-invasive Fetal Electrocardiography for Intrapartum Cardiotocography.

Fetal monitoring is important to diagnose complications that can occur during pregnancy. If detected timely, these complications might be resolved before they lead to irreversible damage. Current fetal monitoring mainly relies on cardiotocography, the simultaneous registration of fetal heart rate and uterine activity.