QT and RR interval analysis in genetic cardiac diseases using the AccuQT and advanced heart rate variability methods.

The QT interval is a key indicator in assessing arrhythmia risk, evaluating drug safety, and supporting clinical diagnosis in cardiology. The QT interval is significantly influenced by heart rate so it must be accurately corrected to ensure reliable clinical interpretation. Conventional correction formulas, such as Bazett's formula, are widely utilized but often criticized for inaccuracies, either under- or overcorrecting QT intervals in different physiological conditions.

Threshold estimation in running using dynamical correlations of RR intervals.

We study the estimation of aerobic threshold (AeT) and anaerobic threshold (AnT) using dynamical detrended fluctuation analysis (DDFA). Conventionally, the thresholds are estimated in laboratory settings, where the subject performs an incremental exercise test on a cycloergometer or treadmill. We compared DDFA-based thresholds (DDFAT and DDFAT) with lactate thresholds (LT and LT) and examined thresholds derived from theoretical and measured maximal heart rates (HR).

Detection of congestive heart failure from RR intervals during long-term electrocardiographic recordings.

Background: Timely detection is crucial for managing cardiovascular diseases. Recently developed computational tools to analyze RR interval (RRI) sequences offer cost-effective means for early cardiac screening and monitoring with consumer-grade heart rate devices.

Objective: The purpose of this study was to demonstrate detection of congestive heart failure (CHF) from RRIs by discriminating CHF from both healthy controls and patients with present atrial fibrillation (AF).

Relevance of accurate QT correction in the assessment of long QT syndrome.

Background: Long QT syndrome (LQTS) is a genetic cardiac disease, where the corrected QT (QTc) interval is prolonged. It can cause arrhythmias and lead to a sudden cardiac death. Duration of the QT interval depends on the heart rate and this dependency is treated with QT correction.

Estimation of physiological exercise thresholds based on dynamical correlation properties of heart rate variability.

Aerobic and anaerobic thresholds of the three-zone exercise model are often used to evaluate the exercise intensity and optimize the training load. Conventionally, these thresholds are derived from the respiratory gas exchange or blood lactate concentration measurements. Here, we introduce and validate a computational method based on the RR interval (RRI) dynamics of the heart rate (HR) measurement, which enables a simple, yet reasonably accurate estimation of both metabolic thresholds.

Accurate QT correction method from transfer entropy.

Background: The QT interval in the electrocardiogram (ECG) is a fundamental risk measure for arrhythmic adverse cardiac events. However, the QT interval depends on the heart rate and must be corrected accordingly. The present QT correction (QTc) methods are either simple models leading to under- or overcorrection, or impractical in requiring long-term empirical data.