Evaluation and optimization of novel extraction algorithms for the automatic detection of atrial activations recorded within the pulmonary veins during atrial fibrillation.

Background And Objective: The automated detection of atrial activations (AAs) recorded from intracardiac electrograms (IEGMs) during atrial fibrillation (AF) is challenging considering their various amplitudes, morphologies and cycle length. Activation time estimation is further complicated by the constant changes in the IEGM active zones in complex and/or fractionated signals. We propose a new method which provides reliable automatic extraction of intracardiac AAs recorded within the pulmonary veins during AF and an accurate estimation of their local activation times.

Stochastic pacing reveals the propensity to cardiac action potential alternans and uncovers its underlying dynamics.

Key Points: Beat-to-beat alternation (alternans) of the cardiac action potential duration is known to precipitate life-threatening arrhythmias and can be driven by the kinetics of voltage-gated membrane currents or by instabilities in intracellular calcium fluxes. To prevent alternans and associated arrhythmias, suitable markers must be developed to quantify the susceptibility to alternans; previous theoretical studies showed that the eigenvalue of the alternating eigenmode represents an ideal marker of alternans. Using rabbit ventricular myocytes, we show that this eigenvalue can be estimated in practice by pacing these cells at intervals varying stochastically.

Slow conduction in mixed cultured strands of primary ventricular cells and stem cell-derived cardiomyocytes.

Modern concepts for the treatment of myocardial diseases focus on novel cell therapeutic strategies involving stem cell-derived cardiomyocytes (SCMs). However, functional integration of SCMs requires similar electrophysiological properties as primary cardiomyocytes (PCMs) and the ability to establish intercellular connections with host myocytes in order to contribute to the electrical and mechanical activity of the heart. The aim of this project was to investigate the properties of cardiac conduction in a co-culture approach using SCMs and PCMs in cultured cell strands.

Nonlinear behaviour of conduction and block in cardiac tissue with heterogeneous expression of connexin 43.

Altered gap junctional coupling potentiates slow conduction and arrhythmias. To better understand how heterogeneous connexin expression affects conduction at the cellular scale, we investigated conduction in tissue consisting of two cardiomyocyte populations expressing different connexin levels. Conduction was mapped using microelectrode arrays in cultured strands of foetal murine ventricular myocytes with predefined contents of connexin 43 knockout (Cx43KO) cells.

Measures of spatiotemporal organization differentiate persistent from long-standing atrial fibrillation.

Aims: This study presents an automatic diagnostic method for the discrimination between persistent and long-standing atrial fibrillation (AF) based on the surface electrocardiogram (ECG).

Methods And Results: Standard 12-lead ECG recordings were acquired in 53 patients with either persistent (N= 20) or long-standing AF (N= 33), the latter including both long-standing persistent and permanent AF. A combined frequency analysis of multiple ECG leads followed by the computation of standard complexity measures provided a method for the quantification of spatiotemporal AF organization.

Adaptive tracking of EEG oscillations.

Neuronal oscillations are an important aspect of EEG recordings. These oscillations are supposed to be involved in several cognitive mechanisms. For instance, oscillatory activity is considered a key component for the top-down control of perception.

Phase-rectified signal averaging used to estimate the dominant frequencies in ECG signals during atrial fibrillation.

Phase-rectified signal averaging (PRSA) is a technique recently introduced to enhance quasi-periodic signal components. An important parameter that can be extracted from surface ECG is the dominant frequency (DF) of atrial fibrillation (AF). AF signal components are always highly contaminated by the ventricular complexes, and the cancellation of these components is never perfect.

Propagation velocity kinetics and repolarization alternans in a free-behaving sheep model of pacing-induced atrial fibrillation.

Aims: Experimental models have reported conflicting results regarding the role of dispersion of repolarization in promoting atrial fibrillation (AF). Repolarization alternans, a beat-to-beat alternation in action potential duration, enhances dispersion of repolarization when propagation velocity is involved.

Methods And Results: In this work, original electrophysiological parameters were analysed to study AF susceptibility in a chronic sheep model of pacing-induced AF.

Phase-rectified signal averaging: a useful tool for the estimation of the dominant frequency in ECG signals during atrial fibrillation.

Atrial fibrillation (AF) is the most common type of human cardiac arrhythmia. An important parameter that can be extracted from surface electrocardiogram (ECG) during AF is the dominant frequency (DF) of AF. Unfortunately, AF signal components are always highly contaminated by the ventricular QRST complexes, and the cancellation of these components is never perfect.