Filament behavior in a computational model of ventricular fibrillation in the canine heart

The aim of this paper was to quantify the behavior of filaments in a computational model of re-entrant ventricular fibrillation. We simulated cardiac activation in an anisotropic monodomain with excitation described by the Fenton-Karma model with Beeler-Reuter restitution, and geometry by the Auckland canine ventricle. We initiated re-entry in the left and right ventricular free walls, as well as the septum. The number of filaments increased during the first 1.5 s before reaching a plateau with a mean value of about 36 in each simulation. Most re-entrant filaments were between 10 and 20 mm long. The proportion of filaments touching the epicardial surface was 65%, but most of these were visible for much less than one period of re-entry. This paper shows that useful information about filament dynamics can be gleaned from models of fibrillation in complex geometries, and suggests that the interplay of filament creation and destruction may offer a target for antifibrillatory therapy.     

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.     

Detecting ventricular fibrillation by time-delay methods

A pivotal component in automated external defibrillators (AEDs) is the detection of ventricular fibrillation (VF) by means of appropriate detection algorithms. In scientific literature there exists a wide variety of methods and ideas for handling this task. These algorithms should have a high detection quality, be easily implementable, and work in realtime in an AED. Testing of these algorithms should be done by using a large amount of annotated data under equal conditions. For our investigation we simulated a continuous analysis by selecting the data in steps of 1 s without any preselection. We used the complete BIH-MIT arrhythmia database, the CU database, and files 7001-8210 of the AHA database. For a new VF detection algorithm we calculated the sensitivity, specificity, and the area under its receiver operating characteristic curve and compared these values with the results from an earlier investigation of several VF detection algorithms. This new algorithm is based on time-delay methods and outperforms all other investigated algorithms.     

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.     

Finite automaton intrusion tolerance system model based on Markov

To ensure that the system could still provide normal service for legitimate users when the LAN being invaded,a finite automaton intrusion tolerance model was designed.Based on Markov’s theory,the state transformation relationship of the service provided by the system by establishing the state transition probability matrix was described,quantified the transition state and found the key nodes in the system.The maintenance of key nodes could enhance the tolerance of the system and improve the reliability of the service.Experimental comparison shows that this model not only has strong intrusion tolerance,but also has obvious advantages in the integrity of the security system when it is invaded.     

Estimation of the ventricular fibrillation duration byautoregressive modeling

An accurate estimation of ventricular fibrillation (VF) duration could be critical in selecting the most effective therapeutic intervention. The authors test the hypothesis that changes in frequency content of VF signals can be quantified by using autoregressive (AR) modeling, and the duration since the onset of VF can be estimated by using this method. VF signals were recorded for up to 300 s in five isolated rabbit hearts. Fourth-order AR parameters of successive segments were estimated, and frequencies of the first poles (the pole with lower frequency) were pooled together and a curve was fitted: F(t)=Aexp(-α_t)+B, where F(t) is the estimated frequency of the first pole at t'th time instant, α is the decay constant, B is the offset frequency, and A is the frequency at time zero minus the offset frequency. The utility of this curve in estimating the VF duration was tested in four new experiments, and the difference between the actual and the estimated VF duration (estimation error) was calculated. F(t), the frequency of the first pole, decreased from 12 to 6 Hz with duration of VF, while the frequency of the other pole decreased from 25 to 20 Hz. Parameters of the fitted curve were calculated as A=7.8, α=0.0041 and B was selected as four. Testing on a new set of VF signals produced very little estimation error for the first 100 s of VF, although this error increased with VF duration, For these new signals, the mean value of the absolute estimation error was 26 s. Results of this study show that changes in the frequency content of electrocardiogram (ECG) during VF can be quantified by AR modeling and that the frequency changes associated with a pole of this model can be used to estimate the VF duration     

A density-based cellular automaton model for studying the clustering of noninvasive cells

We investigated whether cluster formation by noninvasive cells can be explained by a global attractive potential. Indices quantifying the persistence of migration in experimental conditions were compared to the same indexes computed from simulations with a density-based cellular automaton. The results indicate that the attractive potential hypothesis must be rejected.     

Variation in the dominant period during ventricular fibrillation

Time-varying periodicities are commonly observed in biological time series. In this paper, we discuss three different algorithms to detect and quantify change in periodicity. Each technique uses a sliding window to estimate periodic components in short subseries of a longer recording. The three techniques we utilize are based on: 1) standard Fourier spectral estimation; 2) an information theoretic adaption of linear (autoregressive) modeling; and 3) geometric properties of the embedded time series. We compare the results obtained from each of these methods using artificial data and experimental data from swine ventricular fibrillation (VF). Spectral estimates have previously been applied to VF time series to show a time-dependent trend in the dominant frequency. We confirm this result by showing that the dominant period of VF, following onset, first decreases to a minimum and then rises to a plateau. Furthermore, our algorithms detect longer period correlations which may indicate the presence of additional periodic oscillations or more complex nonlinear structure. We show that in general this possibly nonlinear structure is most apparent immediately after the onset of VF.     

Detecting ventricular tachycardia and fibrillation by complexity measure

Sinus rhythm (SR), ventricular tachycardia (VT) and ventricular fibrillation (VF) belong to different nonlinear physiological processes with different complexity. In this study, we present a novel, and computationally fast method to detect VT and VF, which utilizes a complexity measure suggested by Lempel and Ziv [1]. For a specific window length (i.e., the length of data segment to be analyzed), the method first generates a 0-1 string by comparing the raw electrocardiogram (ECG) data to a selected suitable threshold. The complexity measure can be obtained from the 0-1 string only using two simple operations, comparison and accumulation. When the window length is 7 s, the detection accuracy for each of SR, VT, and VF is 100% for a test set of 204 body surface records (34 SR, 85 monomorphic VT, and 85 VF). Compared with other conventional time- and frequency-domain methods, such as rate and irregularity, VF-filter leakage, and sequential hypothesis testing, the new algorithm is simple, computationally efficient, and well suited for real-time implementation in automatic external defibrillators (AED's).     

Integration of absolute ventricular fibrillation voltage correlateswith successful defibrillation

Previous work has suggested that at higher absolute ventricular fibrillation voltages (AVFV), the heart is more amenable to defibrillation. This study investigated in a canine model whether voltage integration of the AVFV is associated with the defibrillation success rate. The moving-average filter was used to process the ventricular fibrillation (VF) waveform recorded from Lead II of the electrocardiogram (ECG). In seven animals, defibrillation trials were analyzed using a DC shock (DCS) successful approximately 50% of the time when delivered randomly. For each of a total of 84 DCS (40% successes, 60% failures), the fibrillation waveform just prior to DCS was analyzed. The integration of the AVPV waveform was performed over various sample sizes including 1, 4, 8, 16, 64, and 128 ms, as well as the time equal to the mean VF cycle length. The results suggest that dc shocks delivered at instants of higher values of integrated AVFV over the various window sizes are associated with successful defibrillation. Window sizes less than 16 ms appeared to offer the best discrimination. The integration of AVFV over the entire VF cycle length was significantly higher for successful rather than unsuccessful DCS. This interesting observation is consistent with the clinical observation that “coarse” VF (high AVFV) is easier to defibrillate than “fine” VF (low AVFV). The use of voltage integration of AVFV may have potential implications in the improvement of defibrillation success in implantable devices     

基于不同安全间距的元胞自动机交通流模型的研究

文中在NaSch模型的基础上提出一个改进的元胞自动机模型来模拟周期性边界条件下高速公路上车流运动。考虑到不同速度应有不同的安全车间距、反应时间和减速距离,根据车辆与前方紧邻车辆之间的间距和车辆的速度来确定该车的运动,这样就可以间接地反映出前方紧邻车辆对当前车辆的影响。通过引入不同的安全间距可以描述不同速度运动的车辆接近前方车辆时的减速行为。由于不同的安全车间距的引入,并且考虑到速度的差异,因而可以较好地描述交通流中的不同现象,可以对车辆微观运动进行合理地描述。     

Efficient electrode spacing for examining spatial organizationduring ventricular fibrillation

Spatial organization has been observed during episodes of ventricular fibrillation (VF) by recording epicardial unipolar electrograms on a grid of electrodes. In such studies, the choice of spacing between electrodes is an important decision, affecting the resolution and the size of the domain to be studied. A basic tenet of sampling theory, the Nyquist criterion, states that an electrode spacing smaller than half the smallest significant wavelength is required to capture the important details of a spatially sampled process. The authors suggest a method to choose a practical interelectrode spacing by examining wavenumber power spectra of high-resolution VF data recorded from a square 11×11 array of electrodes spaced 0.28 mm apart. The plaque was sutured on the epicardium near the left ventricular apex in 7 anesthetized pigs. VF was induced with AC simulation. Unipolar extracellular electrograms were simultaneously recorded from each channel for 2 s after the induction of VF. Each signal was sampled in time at 1000 Hz. Wavenumber power spectra were calculated for 100 ms segments using the zero-delay wavenumber spectrum method, for a total of 140 power spectra. All spectra had dominant peaks at the origin and fell off rapidly with increasing wavenumber (decreasing wavelength). In all the spectra, every wavelength shorter than 1.4 mm contributed insignificant power. Furthermore, in 134 of 140 spectra (96%), insignificant power levels were associated with every wavelength shorter than 2.8 mm. These results suggest that, for unipolar extracellular electrodes, an intersensor spacing on the order of 1 mm is appropriate to study organization during early VF     

Taser dart-to-heart distance that causes ventricular fibrillation in pigs

Electromuscular incapacitating devices (EMDs), such as Tasers, deliver high current, short duration pulses that cause muscular contractions and temporarily incapacitate the human subject. Some reports suggest that EMDs can kill. To help answer the question, "Can the EMD directly cause ventricular fibrillation (VF)?", ten tests were conducted to measure the dart-to-heart distance that causes VF in anesthetized pigs [mass = 64 kg +/- 6.67 standard deviation (SD)] for the most common X26 Taser. The dart-to-heart distance that caused VF was 17 mm +/- 6.48 (SD) for the first VF event and 13.7 mm +/- 6.79 (SD) for the average of the successive VF events. The result shows that when the stimulation dart is close enough to the heart, X26 Taser current will directly trigger VF in pigs. Echocardiography of erect humans shows skin-to-heart distances from 10 to 57 mm (dart-to-heart distances of 1-48 mm). These results suggest that the probability of a dart on the body landing in 1 cm2 over the ventricle and causing VF is 0.000172.     

Time domain and spectral analysis of electrograms in man during regular ventricular activity and ventricular fibrillation

Electrogram signals from intramyocardially placed wire electrodes were recorded in 24 open heart surgery patients during regular heart activity (RHA) and ventricular fibrillation (VF). Time domain parameters, maximal amplitudes (AMAX, UMAX), maximal derivatives (DMAX, SMAX), and power spectra in the frequency region up to 100 Hz were analyzed off-line on a digital computer. DMAX, AMAX, SMAX, and UMAX were significantly lower postoperatively than during the operation in RHA, median values reduced by 37, 23, 54, and 50 percent. Corresponding reductions in median values of 64, 39, 58, and 30 percent occurred in the transition from RHA to VF during the operation (peroperatively).     

Quantifying ventricular fibrillation: in silico research and clinical implications

Cardiovascular disease remains the leading cause of death in otherwise healthy humans. In particular, most cases of sudden cardiac death occur as a result of failure of the mechanical function of the heart which is triggered by a turbulent pattern of electrical excitation of the heart e.g., ventricular fibrillation (VF). Although the exact mechanisms of VF remain unknown, increasing evidence indicates that it is organized by multiple reentrant sources (wavelets).     

An algorithm used for ventricular fibrillation detection without interrupting chest compression

Ventricular fibrillation (VF) is the primary arrhythmic event in the majority of patients suffering from sudden cardiac arrest. Attention has been focused on this particular rhythm since it is recognized that prompt therapy, especially electrical defibrillation, may lead to a successful outcome. However, current versions of automated external defibrillators (AEDs) mandate repetitive interruptions of chest compression for rhythm analyses since artifacts produced by chest compression during cardiopulmonary resuscitation (CPR) preclude reliable electrocardiographic (ECG) rhythm analysis. Yet, repetitive interruptions in chest compression are detrimental to the success of defibrillation. The capability for rhythm analysis without requiring "hands-off" intervals will allow for more effective resuscitation. In this paper, a novel continuous-wavelet-transformation-based morphology consistency evaluation algorithm was developed for the detection of disorganized VF from organized sinus rhythm (SR) without interrupting the ongoing chest compression. The performance of this method was evaluated on both uncorrupted and corrupted ECG signals recorded from AEDs obtained from out-of-hospital victims of cardiac arrest. A total of 232 patients and 31,092 episodes of either VF or SR were accessed, in which 8195 episodes were corrupted by artifacts produced by chest compressions. We also compared the performance of this method with three other established algorithms, including VF filter, spectrum analysis, and complexity measurement. Even though there was a modest decrease in specificity and accuracy when chest compression artifact was present, the performance of this method was still superior to other reported methods for VF detection during uninterrupted CPR.     

Combined phase singularity and wavefront analysis for optical maps of ventricular fibrillation

Much of the research into the mechanisms of ventricular fibrillation (VF) employs high-resolution mapping of electrical activation and recovery patterns. We previously developed a method for analyzing electrically mapped VF patterns that was based on identifying individual VF wavefronts. We now introduce a related method designed to take into account the information on repolarization that is present in optically mapped VF data. The new method first converts raw fluorescence data to an angular variable that tracks the phase of the mapped tissue through the depolarization-repolarization cycle. We define wavefronts in this context as isolines of phase that terminate either at boundaries or at singular points within the phase field. These singularities are the pivots of functional reentry and are important determinants of VF patterns. We parameterize VF by constructing data structures that describe wavefronts and singularities and also maintain wavefront-wavefront, wavefront-singularity, and singularity-singularity relationships. We describe one important application of this parameterization, which is to identify, localize, and characterize the importance of occurrences of propagation block during VF.     

Effect of electrode surface area on thresholds for AC stimulation and ventricular fibrillation

Unintended, weak AC stimulation (leakage currents) from medical devices can cause blood pressure collapse and ventricular fibrillation (VF), potentially even death. Yet, little is understood about AC cardiac stimulation. The objective of this paper is to establish the relationship between the stimulation and VF thresholds for electrode size and stimulation frequency. Twenty-four retired male breeder guinea pigs were anesthetized with isoflurane, a tracheotomy and thoracotomy were performed, and vitals were monitored using the lead II ECG and an optical plethysmograph. The circular flat ends of eleven stainless steel rods were used as electrodes with areas ranging from 0.1 to 26.79 mm2. In the first study, 60-Hz AC stimuli of 5 s duration were delivered with strengths from 25-3000 microA or until VF was induced. In the second group, the current thresholds at 20, 40, 80, and 160 Hz were determined at electrode areas of 0.2, 2.01, and 16.4 mm2. Reactions were categorized as having no effect, having some effect (EFFECT, typically blood pressure collapse), and inducing VF. On a log-log scale, electrode radii had a piecewise-linear relationship with the current thresholds for EFFECT (p < 0.005) and VF (p < 0.01). The liminal area determined by the piecewise-linear fit was 2.0 and 2.84 mm2 for EFFECT and VF, respectively. Above the liminal area, the threshold increased proportional to r(1.25) and r(0.95) (r = radius of electrode), for EFFECT and VF, respectively. Based on these experimental results, we present a theoretical framework to explain the electrode size-stimulation threshold variation for both low strength AC stimulation and VF initiation.     

A simple time domain algorithm for the detection of ventricular fibrillation in electrocardiogram

Ventricular fibrillation (VF) is the most serious variety of arrhythmia which requires quick and accurate detection to save lives. In this paper, we propose a new time domain algorithm, called threshold crossing sample count (TCSC), which is an improved version of the threshold crossing interval (TCI) algorithm for VF detection. The algorithm is based on an important feature of the VF signal which relies on the random behavior of the electrical heart vector. By two simple operations: comparison and count, the technique calculates an effective measure which is used to separate life-threatening VF from other heart rhythms. For assessment of the performance of the algorithm, the method is applied on the complete MIT-BIH arrhythmia and CU databases, and a promising good performance is observed. Seven other classical and new VF detection algorithms, including TCI, have been simulated and comparative performance results in terms of different quality parameters are presented. The TCSC algorithm yields the highest value of the area under the receiver operating characteristic curve (AUC). The new algorithm shows strong potential to be applied in clinical applications for faster and accurate detection of VF.