Sleep Stage Classification Through HRV, Complexity Measures, and Heart Rate Asymmetry Using Generalized Estimating Equations Models.

This study investigates whether heart rate asymmetry (HRA) parameters offer insights into sleep stages beyond those provided by conventional heart rate variability (HRV) and complexity measures. Utilizing 31 polysomnographic recordings, we focused exclusively on electrocardiogram (ECG) data, specifically the RR interval time series, to explore heart rate dynamics associated with different sleep stages. Employing both statistical techniques and machine learning models, with the Generalized Estimating Equation model as the foundational approach, we assessed the effectiveness of HRA in identifying and differentiating sleep stages and transitions.

pRR30, pRR3.25% and Asymmetrical Entropy Descriptors in Atrial Fibrillation Detection.

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 than or equal to 30 ms or 3.25% of the previous RR interval (pRR30 and pRR3.

Obesity in Hypertensive Patients Is Characterized by a Dawn Phenomenon in Systolic Blood Pressure Values and Variability.

One of the causes of hypertension is excess weight gain, which can also affect the course of this disease. Both the diagnosis and management of hypertension commonly use ambulatory blood pressure monitoring; the results of which correlate more strongly with cardiovascular diseases and cardiovascular death than office blood pressure monitoring. We evaluated blood pressure values and their variability from hour to hour to see if and when they differed between hypertensive patients with and without obesity.

Relative Consistency of Sample Entropy Is Not Preserved in MIX Processes.

Relative consistency is a notion related to entropic parameters, most notably to Approximate Entropy and Sample Entropy. It is a central characteristic assumed for e.g.

Assessing sample entropy of physiological signals by the norm component matrix algorithm: application on muscular signals during isometric contraction.

Sample Entropy (SampEn) is a popular method for assessing the unpredictability of biological signals. Its calculation requires to preliminarily set the tolerance threshold r and the embedding dimension m. Even if most studies select m=2 and r=0.