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Current gold-standard algorithms for heart beat detection do not work properly in the case of high noise levels and do not make use of multichannel data collected by modern patient monitors. The main idea behind the method presented in this paper is to detect the most prominent part of the QRS complex, i.e. the RS slope. We localize the RS slope based on the consistency of its characteristics, i.e. adequate, automatically determined amplitude and duration. It is a very simple and non-standard, yet very effective, solution. Minor data pre-processing and parameter adaptations make our algorithm fast and noise-resistant. As one of a few algorithms in the PhysioNet/Computing in Cardiology Challenge 2014, our algorithm uses more than two channels (i.e. ECG, BP, EEG, EOG and EMG). Simple fundamental working rules make the algorithm universal: it is able to work on all of these channels with no or only little changes. The final result of our algorithm in phase III of the Challenge was 86.38 (88.07 for a 200 record test set), which gave us fourth place. Our algorithm shows that current standards for heart beat detection could be improved significantly by taking a multichannel approach. This is an open-source algorithm available through the PhysioNet library.

Existing atrial models with detailed anatomical structure and multi-variable cardiac transmembrane current models are too complex to allow to combine an investigation of long time dycal properties of the heart rhythm with the ability to effectively simulate cardiac electrical activity during arrhythmia. Other ways of modeling need to be investigated. Moreover, many stateof-the-art models of the right atrium do not include an atrioventricular node (AVN) and only rarely-the sinoatrial node (SAN). A model of the heart tissue within the right atrium including the SAN and AVN nodes was developed. Looking for a minimal model, currently we are testing our approach on chosen well-known arrhythmias, which were until now obtained only using much more complicated models, or were only observed in a clinical setting. Ultimately, the goal is to obtain a model able to generate sequences of RR intervals specific for the arrhythmias involving the AV junction as well as for other phenomena occurring within the atrium. The model should be fast enough to allow the study of heart rate variability and arrhythmias at a time scale of thousands of heart beats in real-time. In the model of the right atrium proposed here, different kinds of cardiac tissues are described by sets of different equations, with most of them belonging to the class of Liénard nonlinear dynamical systems. We have developed a series of models of the right atrium with differing anatomical simplifications, in the form of a 2D mapping of the atrium or of an idealized cylindrical geometry, including only those anatomical details required to reproduce a given physiological phenomenon. The simulations allowed to reconstruct the phase relations between the sinus rhythm and the location and properties of a parasystolic source together with the effect of this source on the resultant heart rhythm. We model the action potential conduction time alternans through the atrioventricular AVN junction observed in cardiac tissue in electrophysiological studies during the ventricular-triggered atrial tachycardia. A simulation of the atrio-ventricular nodal reentry tachycardia was performed together with an entrainment procedure in which the arrhythmia circuit was located by measuring the post-pacing interval (PPI) at simulated mapping catheters. The generation and interpretation of RR times series is the ultimate goal of our research. However, to reach that goal we need first to (1) somehow verify the validity of the model of the atrium with the nodes included and (2) include in the model the effect of the sympathetic and vagal ANS. The current paper serves as a partial solution of the 1). In particular we show, that measuring the PPI-TCL entrainment response in proximal (possibly-the slow-conducting pathway), the distal and at a mid-distance from CS could help in rapid distinction of AVNRT from other atrial tachycardias. Our simulations support the hypothesis that the alternans of the conduction time between the atria and the ventricles in the AV orthodromic reciprocating t...

Introduction: Electro-anatomical mapping of the atria is used to identify the substrate of atrial fibrillation (AF). Targeting this substrate by ablation in addition to pulmonary vein ablation did not consistently improve outcome in clinical trials. Generally, the assessment of the substrate is based on short recordings (≤10 s, often even shorter). Thus, targeting the AF substrate assumes spatiotemporal stationarity but little is known about the variability of electrophysiological properties of AF over time.Methods: Atrial fibrillation (AF) was maintained for 3–4 weeks after pericardial electrode implantation in 12 goats. Within a single AF episode 10 consecutive minutes were mapped on the left atrial free wall using a 249-electrode array (2.25 mm inter-electrode spacing). AF cycle length, fractionation index (FI), lateral dissociation, conduction velocity, breakthroughs, and preferentiality of conduction (Pref) were assessed per electrode and AF property maps were constructed. The Pearson correlation coefficient (PCC) between the 10 AF-property maps was calculated to quantify the degree spatiotemporal stationarity of AF properties. Furthermore, the number of waves and presence of re-entrant circuits were analyzed in the first 60-s file. Comparing conduction patterns over time identified recurrent patterns of AF with the use of recurrence plots.Results: The averages of AF property maps were highly stable throughout the ten 60-s-recordings. Spatiotemporal stationarity was high for all 6 property maps, PCC ranged from 0.66 ± 0.11 for Pref to 0.98 ± 0.01 for FI. High stationarity was lost when AF was interrupted for about 1 h. However, the time delay between the recorded files within one episode did not affect PCC. Yet, multiple waves (7.7 ± 2.3) were present simultaneously within the recording area and during 9.2 ± 11% of the analyzed period a re-entrant circuit was observed. Recurrent patterns occurred rarely and were observed in only 3 out of 12 goats.Conclusions: During non-self-terminating AF in the goat, AF properties were stationary. Since this could not be attributed to stable recurrent conduction patterns during AF, it is suggested that AF properties are determined by anatomical and structural properties of the atria even when the conduction patterns are very variable.

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The left atrium (LA) plays an important role in the maintenance of hemodynamic and electrical stability of the heart. One of the conditions altering the atrial mechanical function is atrial fibrillation (AF), leading to an increased thromboembolic risk due to impaired mechanical function. Preserving the regions of the LA that contribute the greatest to atrial mechanical function during curative strategies for AF is important. The purpose of this study is to introduce a novel method of regional assessment of mechanical function of the LA. We used cardiac MRI to reconstruct the 3D geometry of the LA in nine control and nine patients with paroxysmal atrial fibrillation (PAF). Regional mechanical function of the LA in pre-defined segments of the atrium was calculated using regional ejection fraction and wall velocity. We found significantly greater mechanical function in anterior, septal and lateral segments as opposed to roof and posterior segments, as well as a significant decrease of mechanical function in the PAF group. We suggest that in order to minimize the impact of the AF treatment on global atrial mechanical function, damage related to therapeutic intervention, such as catheter ablation, in those areas should be minimized.

Unipolar electrogram can detect local as well as remote electrical activity of the heart. Information on how the amplitude and morphology of the recorded signal changes with the distance from the source tissue undergoing depolarization can help to better understand unipolar electrograms fractionation and provide insights into the passive conduction properties of the atrial tissue. Ten second unipolar atrial fibrillation (AF) electrograms were recorded using high-density electrode array from the posterior left atrium (LA) and right atrium (RA) of 19 (8 persistent - PERS & 11 paroxysmal - PAF) AF patients undergoing cardiac surgery. Conduction along lines of conduction block was detected in the recorded activation patterns by a proposed automated algorithm. Changes of the amplitude of the unipolar electrogram with increasing distance from the conduction blocks were assessed and compared to predictions of a theoretical model. For each recording, the median far-field decay space constant (FF0.5) was calculated. Overall, we found a significant difference between FF0.5 for patients with paroxysmal and persistent AF. Estimation of maximum FF0.5 from both RA and LA resulted in a mean FF0.5 of 1.5±0.2 mm for PERS patients and 2.1±0.6 mm for PAF patients (p=0.03). Moreover, detected conduction blocks demonstrated high spatial organization and appeared in distinctive areas of the mapped area in all patients, regardless of the type of AF, while the total number of detected block lines was higher in PERS patients.

This prospective study comprised 30 patients (26 males, mean age = 55±16 years) referred for ablation of either atrial or ventricular © 2014 American Heart Association, Inc. Original Article Background-The difference between the postpacing interval (PPI) and the tachycardia cycle length (TCL; PPI−TCL) is a useful tool in mapping macro-reentrant tachycardias. However, entrainment pacing causes some perturbation of the conduction velocity within the tachycardia circuit, which may affect the repeatability and consequently the accuracy of the measurement of PPI−TCL. The aim of this study was to assess PPI−TCL repeatability both in vivo and in silico. Methods and Results-In the experimental part, entrainment pacing was performed twice at each of the 124 tested sites for 30 patients undergoing radiofrequency ablation of atrial and ventricular re-entrant arrhythmias. A similar protocol was used in a simplified computer model of the cardiac tachycardia circuit in a 2-dimensional tissue strip using a Fenton-Karma model of cardiac tissue. In vivo, in the case of fast tachycardias (<350 ms), PPI−TCL variability observed was doubled compared with slow tachycardias (>350 ms; 95% Limits of Agreement ranged from −21.4 to 21.6 ms for TCL<350 ms and from −10.8 to 11.5 ms for TCL>350 ms). Simulations show that this increase of variability may be because of the oscillations of the conduction velocity inside the tachycardia circuits. The effect of the restitution properties of cardiac tissue on the outcome of entrainment pacing is discussed. Conclusions-PPI−TCL is characterized by a high repeatability with the differences between the results for individual stimulations of ≤20 ms. The variability of this parameter is significantly lower in the case of slow tachycardias.(Circ Arrhythm Electrophysiol. 2014;7:497-504.)