Abnormal heart rhythms, also known as arrhythmias, can be life-threatening. AFIB and AFL are examples of arrhythmia that affect a growing number of patients. This paper describes a method that can support clinicians during arrhythmia diagnosis. We pr...
A diagnostic system for sleep apnea based on oxygen saturation and RR intervals obtained from the EKG (electrocardiogram) is proposed with the goal to detect and quantify minute long segments of sleep with breathing pauses. We measured the discrimina...
Background: The ratio of the difference between neighboring RR intervals to the length of the preceding RR interval (x%) represents the relative change in the duration between two cardiac cycles. We investigated the diagnostic properties of the perce...
Congestive heart failure (CHF) refers to the inadequate blood filling function of the ventricular pump and it may cause an insufficient heart discharge volume that fails to meet the needs of body metabolism. Heart rate variability (HRV) based on the...
Congestive heart failure (CHF), a progressive and complex syndrome caused by ventricular dysfunction, is difficult to detect at an early stage. Heart rate variability (HRV) was proposed as a prognostic indicator for CHF. Inspired by the success of 2-...
Autonomic cardiac regulation is affected by advancing age and can be observed by variations in R-peak to R-peak intervals (RRIs). Heart rate variability (HRV) has been investigated as a physiological marker for predicting age using machine learning....
Atrial Fibrillation (AFib) is a heart condition that occurs when electrophysiological malformations within heart tissues cause the atria to lose coordination with the ventricles, resulting in “irregularly irregular” heartbeats. Because sy...
As heart rate variability (HRV) studies become more and more prevalent in clinical practice, one of the most common and significant causes of errors is associated with distorted RR interval (RRI) data acquisition. The nature of such artifacts can be...
Cardiac signals have complex structures representing a combination of simpler structures. In this paper, we develop a new data analytic tool that can extract the complex structures of cardiac signals using the framework of multi-chaotic analysis, whi...
The present study aimed at testing the hypothesis that application of multiscale cross-approximate entropy (MCAE) analysis in the study of nonlinear coupling behavior of two synchronized time series of different natures [i.e., R-R interval (RRI) and...
Wearable physiological monitors have become increasingly popular, often worn during people’s daily life, collecting data 24 hours a day, 7 days a week. In the last decade, these devices have attracted the attention of the scientific community a...
The dynamics of the collapse of complexity observable in the performance of the cardiovascular system during the stress test is investigated in this paper. For this purpose, the interplay between the RR and JT cardiac intervals is measured and assess...
In many applications, recognizing the depth of sleep (e.g., light, deep, REM sleep) while the subject is sleeping enables innovative features. For instance, in SAE Level 4 autonomous driving, a driver may need to takeover the vehicle control in case...
The complexity and the disorder of a 1/
Recent advances in wearable technologies integrating multi-modal sensors have enabled the in-field monitoring of several physiological metrics. In sport applications, wearable devices have been widely used to improve performance while minimizing the...
Atrial fibrillation (AF) is an abnormal rhythm of the heart, which can increase heart-related complications. Paroxysmal AF episodes occur intermittently with varying duration. Human-based diagnosis of paroxysmal AF with a longer-term electrocardiogra...
COVID-19 causes severe illness that results in morbidity and mortality. Electrocardiographic features, including QT prolongation, have been associated with poor acute outcomes; data on the medium-term outcomes remain scarce. This study evaluated the...
Early detection of atrial fibrillation from electrocardiography (ECG) plays a vital role in the timely prevention and diagnosis of cardiovascular diseases. Various algorithms have been proposed; however, they are lacking in considering varied-length...
Although many studies have reported factors associated with reduced heart rate variability (HRV) in Western populations, evidence is limited among Asian populations. Therefore, we investigated the factors associated with reduced HRV values in a gener...
Heart rate variability (HRV) is frequently applied in sport-specific settings. The rising use of freely accessible applications for its recording requires validation processes to ensure accurate data. It is the aim of this study to compare the HRV da...
This study investigates the use of atrioventricular (AV) synchronization as an important diagnostic criterion for atrial fibrillation and flutter (AF) using one to twelve ECG leads. Heart rate, lead-specific AV conduction time, and P-/f-wave amplitud...
Classification of normal sinus rhythm (NSR), paroxysmal atrial fibrillation (PAF), and persistent atrial fibrillation (AF) is crucial in order to diagnose and effectively plan treatment for patients. Current classification models were primarily devel...
Patients with neurodegenerative disorders lose body weight as their diseases progress. In Parkinson’s disease (PD), however, autonomic dysfunction is associated with increased body mass index (BMI). We investigated the correlation between BMI, clinic...
Sleep disorders can have harmful consequences in both the short and long term. They can lead to attention deficits, as well as cardiac, neurological and behavioral repercussions. One of the most widely used methods for assessing sleep disorders is po...
Background: Wearable technologies for monitoring cardiovascular parameters, including electrocardiography (ECG) and impedance cardiography (ICG), propose a challenging research subject. The expectancy for wearable devices to be unobtrusive and miniat...
The purpose of the current study was to determine the concurrent validity of the Elite HRV smartphone application when calculating heart rate variability (HRV) metrics in reference to an independent software criterion. A total of 5 minutes of R&ndash...
Cardiovascular diseases are the leading cause of death around the world. As a result, low-cost biomedical sensors have been gaining importance in business and research over the last few decades. Their main benefits include their small size, light wei...
This paper presents a study undertaken to evaluate the sensor systems that were shortlisted to be used in the development of a portable respiratory-gated transcutaneous auricular vagus nerve stimulation (taVNS) system. To date, all published studies...
Cardiovascular systems essentially have multiscale control mechanisms. Multiscale entropy (MSE) analysis permits the dynamic characterization of the cardiovascular time series for both short-term and long-term processes, and thus can be more illumina...
Autonomic activity affects beat-to-beat variability of heart rate and QT interval. The aim of this study was to explore whether entropy measures are suitable to detect changes in neural outflow to the heart elicited by two different stress paradigms....
Background and Objectives: Atrial fibrillation (AF) results in systemic hemodynamic perturbations which impact cerebral circulation, possibly contributing to the development of dementia. However, evidence documenting effects in cerebral perfusion is...
In this paper, interpersonal coordination is studied by analyzing physiological synchronization between individuals. To this end, a four-phase protocol is proposed to collect biosignals from the participants in each dyad. Then, the time evolution of...
Early diagnosis of paroxysmal atrial fibrillation (PAF) could prompt patients to receive timely interventions in clinical practice. Various PAF onset prediction algorithms might benefit from accurate heart rate variability (HRV) analysis and machine...
Heart rate variability (HRV) features support several clinical applications, including sleep staging, and ballistocardiograms (BCGs) can be used to unobtrusively estimate these features. Electrocardiography is the traditional clinical standard for HR...
Electrocardiogram (ECG) signal has been commonly used to analyze the complexity of heart rate variability (HRV). For this, various entropy methods have been considerably of interest. The multiscale entropy (MSE) method, which makes use of the sample...
The short-term scaling exponent alpha1 of detrended fluctuation analysis (DFA-a1) of heart rate variability (HRV) has been shown to be a sensitive marker for assessing global organismic demands. The wide dynamic range within the exercise intensity sp...
The value of heart rate variability (HRV) in the fields of health, disease, and exercise science has been established through numerous investigations. The typical mobile-based HRV device simply records interbeat intervals, without differentiation bet...
12 March 2020
It is well recognized that regular physical activity may improve cardiac autonomic regulation preventing chronic non-communicable diseases. Accordingly, the assessment of cardiac autonomic regulation (CAR) with non-invasive techniques, such as RR int...
22 February 2022
Patients tend to feel stress in association with dental treatment due to uneasiness and fear. We investigated the effects of providing advance notice and stress-coping traits on the physiological stress of patients during dental treatment. Sixty non-...
In this paper, a new method for the detection of apnea/hypopnea periods in physiological data is presented. The method is based on the intelligent combination of an integrated sensor system for long-time cardiorespiratory signal monitoring and dedica...
Despite the growing interest in physiological stress monitoring, an objective measure of stress is currently lacking, especially in clinical and rehabilitation contexts. With the emerging integration of artificial intelligence (AI) in data analytics,...
Here, we propose a signal processing based approach for the extraction of the fetal heart rate (FHR) from Maternal Abdominal ECG (MAECG) in a non-invasive way. Datasets from a Physionet database has been used in this study for evaluating the performa...
11 January 2023
Heart rate variability (HRV) is a psychophysiological variable that is often used in applied analysis techniques to indicate health status because it provides a window into the intrinsic regulation of the autonomic nervous system. However, HRV data a...
Age is an important determinant of heart rate variability (HRV) in healthy individuals. The incidence of arrhythmia is high in patients with mitral valve prolapse (MVP). However, the correlation of HRV in patients with MVP in different age groups is...
We propose for the first time a method for extracting the instantaneous phases of respiration from the signal of a photoplethysmogram (PPG). In addition to the instantaneous phases of respiration, this method allows for more accurately extracting the...
Heart rate variability (HRV) is used as an index reflecting the adaptability of the autonomic nervous system to external stimuli and can be used to detect various heart diseases. Since HRVs are the time series signal with nonlinear property, entropy...
Respiratory Sinus Arrhythmia (RSA) manifests as cyclic fluctuations in heart rate in synchrony with breathing. Gaining insights into the dynamics of RSA within the cardiac muscle functioning is crucial for comprehending its physiological and clinical...
Cardiac autonomic neuropathy (CAN) is a common complication of diabetes mellitus, and can be assessed using heart rate variability (HRV) and the correlations between systolic blood pressure (SBP) and ECG R-R intervals (RRIs), namely baroreflex sensit...
Obstructive sleep apnea (OSA) is highly associated with cardiovascular diseases, but most patients remain undiagnosed. Cyclic variation of heart rate (CVHR) occurs during the night, and R-R interval (RRI) analysis using a Holter electrocardiogram has...
Background: Early detection of atrial fibrillation (AF) is essential to prevent stroke and other cardiac and embolic complications. We compared the diagnostic properties for AF detection of the percentage of successive RR interval differences greater...
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