Computer modeling of ventricular rhythm during atrial fibrillation and ventricular pacing

We propose a unified atrial fibrillation (AF)-ventricular pacing (VP) (AF-VP) model to demonstrate the effects of VP on the ventricular rhythm during atrial fibrillation AF. In this model, the AV junction (AVJ) is treated as a lumped structure characterized by refractoriness and automaticity. Bombarded by random AF impulses, the AVJ can also be invaded by the VP-induced retrograde wave. The model includes bidirectional conduction delays in the AVJ and ventricle. Both refractory period and conduction delay of the AVJ are dependent upon its recovery time. The electrotonic modulation by blocked impulses is also considered in the model. Our simulations show that, with proper parameter settings, the present model can account for most principal statistical properties of the RR intervals during AF. We further demonstrate that the AV conduction property and the ventricular rate in AF depend on both AF rate and the degree of electrotonic modulation in the AVJ. Finally, we show that multilevel interactions between AF and VP can generate various patterns of ventricular rhythm that are consistent with previous experimental observations.     

An atrioventricular node model for analysis of the ventricular response during atrial fibrillation

This paper introduces a model of the atrioventricular node function during atrial fibrillation (AF), and describes the related ECG-based estimation method. The proposed model is defined by parameters that characterize the arrival rate of atrial impulses, the probability of an impulse choosing either one of the two atrioventricular nodal pathways, the refractory periods of these pathways, and the prolongation of the refractory periods. These parameters are estimated from the RR intervals using maximum likelihood estimation, except for the shorter refractory period which is estimated from the RR interval Poincaré plot, and the mean arrival rate of atrial impulses by the AF frequency. Simulations indicated that 200-300 RR intervals are generally needed for the estimates to be accurate. The model was evaluated on 30-min ECG segments from 36 AF patients. The results showed that 88% of the segments can be accurately modeled when the estimated probability density function (PDF) and an empirical PDF were at least 80% in agreement. The model parameters were estimated during head-up tilt test to assess differences caused by sympathetic stimulation. Both refractory periods decreased as a result of stimulation, and the likelihood of an impulse choosing the pathway with the shorter refractory period increased.     

A method to estimate statistics of rain depolarization

This paper is concerned with depolarization caused by rain due to nonsphericity of drops and the distribution of their axes orientations. The drops are assumed to be oblate spheroids having canting angles distribution obtained by Saunders. Differential phase shift as well as differential attenuation is important in the calculation of depolarization and the values proposed by Oguchi and Hosoya are utilized. In the first part expression to calculate depolarization amount for a uniform precipitation rate are presented. But communication engineers are usually interested on statistical variations of depolarization amount, so the second part of this paper is concerned with statistical distribution of depolarization. The rain cell proposed by Misme and Fimbel is used to describe the rain model over a path. If the precipitation rate distribution is known in one point of the path, the depolarization distribution is obtained by assuming only one rain cell along the path where, for a long time observation, the precipitation rate distribution for all points is the same.     

A new method for analysis of atrial activation during chronicatrial fibrillation in man

To further clarify the mechanisms maintaining chronic atrial fibrillation (CAF), a method identifying preferable activation patterns of the atria during fibrillation, by time averaging of multiple discrete excitation vectors, was developed. Repeated recordings, each of 56 atrial bipolar electrograms simultaneously acquired during 8 s, were made at multiple sites in the right atrial free wall and the left atrial appendage in 16 patients with CAF using a 2.17×3.54 cm electrode array. The local activation times (LAT's) in each recording were estimated as the median activation time at the respective measurement point. By calculating the time difference between the LAT's at adjacent measurement points in two spatial dimensions, a direction vector was created for each activation wave passing each set of measurement points, a total of 42 sets. By time averaging of the individual direction vectors (typically n=55) at each set of measurement points, preferable activation patterns were determined. Three types of activation patterns were found: 1) inconsistent activation (n=5), 2) consistent activation with preferential propagation directions (n=7) and 3) consistent activation with impulses originating from a localizable site within the recording area (n=4). All activation patterns were reproducible and the two latter patterns were proven significant using statistical tests. It is concluded that this new method is useful in further clarification of the mechanisms involved in the maintenance of atrial fibrillation     

基于核稀疏编码的阵发性房颤检测

阵发性房颤(PAF)是一种具有偶发性的心律失常,其较高的漏检率导致心脏相关疾病的增加。该文提出了一种基于核稀疏编码的自动检测方法,可以仅根据较短RR间期数据识别PAF发作。该方法采用特殊几何结构来分析数据高维特性,通过计算协方差矩阵作为特征描述子,找到蕴含在数据中的黎曼流形结构;然后基于Log-Euclid框架,利用核方法将流形空间映射到高维可再生核希尔伯特空间,以获取更准确的稀疏表示来快速识别PAF。经麻省理工学院-贝斯以色列医院房颤数据库验证,获得98.71%的敏感性、98.43%的特异度和98.57%的总准确率。因此,该研究对检测短暂发作的PAF有实质性的改善,在临床监测和治疗方面显示出良好的潜力。     

A technique for measurement of the extent of spatial organizationof atrial activation during atrial fibrillation in the intact humanheart

Atrial fibrillation (AF) is a common clinical problem, associated with considerable morbidity and motility, for which effective management strategies have yet to be devised. The absence of objective measures to guide selection of antiarrhythmic drug therapy for maintenance of sinus rhythm leaves only clinical endpoints (either beneficial or detrimental) for assessment of drug action, with occasional catastrophic consequences. As part of an attempt to provide an objective framework for the assessment of antiarrhythmic drug action on the electrophysiologic determinants of atrial fibrillation, the authors have developed a measure of the spatial organization of atrial activation processes during atrial fibrillation. By recording activation sequences at multiple equally spaced locations on the endocardial surface of the atrial during atrial fibrillation in humans and determining the degree of correlation between these activation sequences as a function of distance, the authors have been able to construct spatial correlation functions for atrial activation. They have found that atrial activation remains well-correlated, independent of distance during normal sinus rhythm and atrial flutter. During atrial fibrillation, correlation decays monotonically with distance and the space-constant for this decay may be used to describe the relative spatial organization of atrial fibrillation. The authors provide examples of the impact of antiarrhythmic agents on the space-constant and suggest that assessment of the relative spatial organization of atrial activation using this methodology may potentially provide an objective framework to guide therapy in patients with AF     

Theory for measuring the effective polarization parameters of rain from orthogonal linearly-polarized transmissions

The theory is presented for one method of determining the effective polarization parameters of rain from propagation measurements over a line-of-sight link. The method requires the transmission of orthogonal linearlypolarized signals and a set of three amplitude and two relative phase measurements. Approximate equations are given for determining both instantaneous and «statistical parametric» values of the effective parameters in a twoparameter Gaussian model of the raindrop canting angle distribution. The instantaneous values could be useful for comparison with in-situ measurements, while the statistical parametric values are required for prediction of rain depolarization statistics.     

A logical state model of circus movement atrial flutter. Role ofanatomic obstacles, anisotropic conduction and slow conduction zones oninduction, sustenance, and overdrive paced modulation of reentrantcircuits

Because the relative roles of anatomical obstacles, in combination with functional barriers, anisotropic conduction, and slow conduction can not be readily assessed with current electrophysiological techniques, an atrial activation model was developed to study the mechanisms of circus movement atrial flutter. A discrete state model consisting of 4,096 logically connected cardiac elements was used to simulate atrial activation; an inexcitable region simulating the inferior vena cava (IVC) was also incorporated in the model. Atrial flutter was induced by programmed premature stimulation, Anisotropic conduction velocity properties, regional variations in slow conduction, regional refractory gradients and stimulation parameters were specified for each simulation. The reentrant circuit generally consisted of a single reentrant impulse which circulated around a continuous line of functional bidirectional conduction block joined to the IVC. Rapid pacing, 5-30 ms shorter than the spontaneous reentrant cycle length, was applied to entrain and/or terminate the rhythm. The results of this study demonstrate that patterns of initiation, entrainment, termination and reinitiation of circus movement atrial flutter mimic results from in vivo activation mapping studies. The authors find that sustained circus movement atrial flutter circuits depend on: 1) natural anatomical obstacles to stabilize reentrant circuits, and 2) anisotropic conduction properties to reduce the degree of functional conduction block needed to maintain circus movement. Rapid pacing of simulated circus movement atrial flutter demonstrated that the entrainment criteria can be satisfied in a two-dimensional syncytium     

Cellular automaton model of ventricular fibrillation

A theoretical analysis of ventricular fibrillation and the requirements for fibrillation are performed using a discrete element neighborhood (cellular automaton) model of ventricular conduction. The model is configured as a 2500 element rectangular grid on the surface of a cylinder. It is shown that vulnerability to fibrillation is strongly influenced by excited state duration which primarily determines the nature of the underlying reentry activity. As excited state duration is increased fibrillation changes from "coarse" macroreentrant activity to the more chaotic "fine" fibrillation sustained by multiple wavelets of microreentry. In general, defibrillation is achieved by a stimulus strong enough to depolarize the majority of relative refractory elements. The threshold for defibrillation is increased for the more irregular microreentrant fibrillation.     

Characterization of atrial fibrillation using the surface ECG: time-dependent spectral properties

Time-frequency analysis is considered for characterizing atrial fibrillation in the surface electrocardiogram (ECG). Variations in fundamental frequency of the fibrillatory waves are tracked by using different time-frequency distributions which are appropriate to short- and long-term variations. The cross Wigner-Ville distribution is found to be particularly useful for short-term analysis due to its ability to handle poor signal-to-noise ratios. In patients with chronic atrial fibrillation, substantial short-term variations exist in fibrillation frequency and variations up to 2.5 Hz can be observed within a few seconds. Although time-frequency analysis is performed independently in each lead, short-term variations in fibrillation frequency often exhibit a similar pattern in the leads V1, V2 and V3. Using different techniques for short- and long-term analysis, it is possible to reliably detect subtle long-term changes in fibrillation frequency, e.g., related to an intervention, which otherwise would have been obscured by spontaneous variations in fibrillation frequency.     

A novel method for detection of the transition between atrial fibrillation and sinus rhythm

Automatic detection of atrial fibrillation (AF) for AF diagnosis, especially for AF monitoring, is necessarily desirable for clinical therapy. In this study, we proposed a novel method for detection of the transition between AF and sinus rhythm based on RR intervals. First, we obtained the delta RR interval distribution difference curve from the density histogram of delta RR intervals, and then detected its peaks, which represented the AF events. Once an AF event was detected, four successive steps were used to classify its type, and thus, determine the boundary of AF: 1) histogram analysis; 2) standard deviation analysis; 3) numbering aberrant rhythms recognition; and 4) Kolmogorov-Smirnov (K-S) test. A dataset of 24-h Holter ECG recordings (n = 433) and two MIT-BIH databases (MIT-BIH AF database and MIT-BIH normal sinus rhythm (NSR) database) were used for development and evaluation. Using the receiver operating characteristic curves for determining the threshold of the K-S test, we have achieved the highest performance of sensitivity and specificity (SP) (96.1% and 98.1%, respectively) for the MIT-BIH AF database, compared with other previously published algorithms. The SP was 97.9% for the MIT-BIH NSR database.     

A quantitative approach to modeling mammalian myelinated nervefibers for electrical prosthesis design

Presents an upgraded cable model of mammalian myelinated nerve fibers in an extracellularly applied field. The kinetics of the nodes is based upon voltage clamp data in rat motor fibers at 37°C (J.R. Schwartz and G. Eikhof, 1987), while the resting membrane potential is computed with the Goldman equation. The resulting spike shape, conduction velocity, strength/duration behavior, and absolute and relative refractory period are in good quantitative agreement with published experimental data in mammals at normal body temperature and at 20°C. Results at intermediate temperatures however, suggest that the widely used concept of a constant Q₁₀ for the rate constants is invalid. In addition, the model generates realistic abortive spikes towards the end of the absolute refractory period and it can describe the consequences of repetitive firing. The results stress the advantages of a multiple nonlinear node model even if only time aspects of nerve behavior are under study. It turned out, that the model presented here describes in vivo neural properties relevant for electrical prosthesis design better than previous models in literature     

Analysis of the statistical behavior of tandem-connectedburst-error links

The results of extensive simulations of the behavior of tandem channels show interesting trends of the statistical functions in the case of tandem-connected burst-error channels or binary symmetric channels and burst-error channels. The simulations can be divided into two different groups. In the first, the single channels are modeled by infinite Markov chains, the models are connected in tandem, and the behavior of the tandem is described in terms of significant features. In the second, the autocorrelation of the resulting channel is first calculated, and then the tandem is approximated by a renewal model, equivalent from the bit error rate and the conditional error probability points of view. The behavior of this model is discussed     

Intrinsic Data Retention in Nanoscaled Phase-Change Memories—Part I: Monte Carlo Model for Crystallization and Percolation

The amorphous phase of chalcogenide material in phase-change memories (PCMs) is subjected to spontaneous and thermal-activated crystallization. This represents a critical reliability issue and has to be carefully investigated and modeled for physically based projection of retention failure up to ten years. A new three-dimensional percolation model describing the statistical crystallization behavior in an intrinsic PCM cell for the amorphous state is developed. With this physical model, the authors were able to calculate the resistance evolution with time in the cell and the statistical distribution of retention failure times in a cell array. From the impact of geometrical parameters on the cell retention performance, PCM design guidelines to minimize data-loss effects can be obtained. The model allows the evaluation of nucleation and growth parameters and statistical extrapolations of intrinsic retention failure, which is shown in part 2     

Waveform Characterization of Atrial Fibrillation Using Phase Information

A novel method for characterization of f-wave morphology in atrial fibrillation (AF) is presented. The method decomposes atrial activity into fundamental and harmonic components, dividing each component into short blocks for which the amplitudes, frequencies, and phases are estimated. The phase delays between the fundamental and each of the harmonics, here referred to as harmonic phase relationships, are used as features of f-wave morphology. The estimated waves are clustered into typical morphologic patterns. The performance of the method is illustrated by simulated signals, ECG signals recorded from 36 patients with organized AF, and an ECG signal recorded during drug loading with flecainide. The results show that the method can distinguish a wide variety of f-wave morphologies, and that typical morphologies can be established for further analysis of AF.      

基于希尔伯特黄变换和深度卷积神经网络的房颤检测

房颤是一种常见的心律失常,其发病率会随着年龄增长而升高.因此,从心电(ECG)信号中尽早识别出房颤,有助于降低中风风险和心源性死亡率.为有效提高其检测准确率,该文提出一种基于希尔伯特黄变换(HHT)和深度卷积神经网络的房颤检测方法.1维的时域心电信号通过希尔伯特黄变换,转换为时频域信号,旨在通过时频分析,丰富原始信号的...     

Cancellation of ventricular activity in the ECG: evaluation of novel and existing methods

Due to the much higher amplitude of the electrical activity of the ventricles in the surface electrocardiogram (ECG), its cancellation is crucial for the analysis and characterization of atrial fibrillation. In this paper, two different methods are proposed for this cancellation. The first one is an average beat subtraction type of method. Two sets of templates are created: one set for the ventricular depolarization waves and one for the ventricular repolarization waves. Next, spatial optimization (rotation and amplitude scaling) is applied to the QRS templates. The second method is a single beat method that cancels the ventricular involvement in each cardiac cycle in an independent manner. The estimation and cancellation of the ventricular repolarization is based on the concept of dominant T and U waves. Subsequently, the atrial activities during the ventricular depolarization intervals are estimated by a weighted sum of sinusoids observed in the cleaned up segments. ECG signals generated by a biophysical model as well as clinical ECG signals are used to evaluate the performance of the proposed methods in comparison to two standard ABS-based methods.     

Variability of the QRS signal in high-resolution electrocardiograms and magnetocardiograms

The variability of electric and magnetic signals from the heart during the depolarization phase is investigated. A signal processing method is developed, which provides estimates for the beat-to-beat variability of the QRS-complex. The method is based on the decomposition of the depolarization signal into bandpass signals by means of the Morlet wavelet transform. The beat variability of the depolarization signal is estimated by normalized variances of the envelope and instantaneous frequency of bandpass signals. Time intervals of the bandpass filtered depolarization signals having a high signal-to-noise ratio are selected applying an analysis based on phase statistics. The method was tested by computer simulation and experimental data taken from electrocardiographic and magnetocardiographic measurements of healthy persons and patients prone to malignant ventricular tachycardia (VT) or ventricular fibrillation (VF). Results suggest that the calculated variance parameters permit the characterization of beat variable depolarization signals and distinguish VT/VF patients from healthy persons.     

Characterization of QT interval adaptation to RR interval changes and its use as a risk-stratifier of arrhythmic mortality in amiodarone-treated survivors of acute myocardial infarction

A new method is proposed to evaluate the dynamics of QT interval adaptation in response to heart rate (HR) changes. The method considers weighted averages of RR intervals (RR) preceding each cardiac beat to express RR interval history accounting for the influence on repolarization duration. A global optimization algorithm is used to determine the weight distribution leading to the lowest regression residual when curve fitting the [QT, RR1 data using a patient-specific regression model. From the optimum weight distribution, a memory lag L90 is estimated, expressing the delay in the QT adaptation to HR changes. On average, RR intervals of the past 150 beats (approximately 2.5 min) are required to model the QT response accurately. From a clinical point of view, the interval of the initial tens of seconds to one minute seems to be most important in the majority of cases. A measure of the optimum regression residual (r(opt)) has been calculated, discriminating between post-myocardial infarction patients at high and low risk of arrhythmic death while on treatment with amiodarone. A similar discrimination has been achieved with a variable expressing the character of QT lag behind the RR interval dynamics.     

Spatiotemporal QRST cancellation techniques for analysis of atrial fibrillation

A new method for QRST cancellation is presented for the analysis of atrial fibrillation in the surface electrocardiogram (ECG). The method is based on a spatiotemporal signal model which accounts for dynamic changes in QRS morphology caused, e.g., by variations in the electrical axis of the heart. Using simulated atrial fibrillation signals added to normal ECGs, the results show that the spatiotemporal method performs considerably better than does straightforward average beat subtraction (ABS). In comparison to the ABS method, the average QRST-related error was reduced to 58 percent. The results obtained from ECGs with atrial fibrillation agreed very well with those from simulated fibrillation signals.