Discrimination of atrial fibrillation from regular atrial rhythmsby spatial precision of local activation direction

This study tests the hypothesis that atrial fibrillation (AFib) can be discriminated from regular atrial rhythms by a measure of the variation in local activation direction. Human endocardial atrial recordings of AFib, sinus rhythm, atrial flutter, and supraventricular tachycardia were collected using a catheter with orthogonally placed electrodes, and the direction of each activation was calculated using methods previously described by our laboratory. Each recording was divided into segments containing 100 activations, and the spatial precision for each segment was calculated in three dimensions, as well as in each of the three two-dimensional (2-D) planes. The three-dimensional (3-D) spatial precision for 1161 segments of AFib in 11 recordings ranged from 0.09-0.85 (mean=0.45), whereas the spatial precision for 138 segments of regular rhythms in 28 recordings was ⩾0.91 in all but four instances. The 2-D spatial precision values overlapped for all rhythms. The results indicate that 3-D spatial precision of local activation direction is a useful discriminator of AFib     

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     

Temporal and spatial phase analyses of the electrocardiogram stratify intra-atrial and intra-ventricular organization

We hypothesized that electrocardiogram (ECG) spatial phase analysis would define a spectrum of intracardiac organization from atrial fibrillation (AF), nonisthmus-dependent and isthmus-dependent atrial flutter (AFL) to supraventricular tachycardias (SVT), and similarly for ventricular arrhythmias. We analyzed arrhythmia ECGs of 33 patients with isthmus (n = 9) and nonisthmus (n = 5) dependent AFL and SVT: atrial (n = 3), atrioventricular nodal (n = 3), and orthodromic reciprocating (n = 3) tachycardias, as well as AF (n = 5), ventricular tachycardia (monomorphic, VT-MM; n = 7), and fibrillation (VF; n = 3). ECG spatial phase was considered coherent when the correlation coefficient of an atrial (or ventricular) template to its ECG over time maintained a constant relationship in XY, XZ, and YZ planes. Regularity was quantified spectrally from ECG and correlation series. Spatial coherence occurred in 9/9 cases of isthmus--but only 1/5 of cases of nonisthmus-dependent AFL (p < 0.01; chi2). All showed one dominant spectral peak (temporal coherence). In AF, spatial phase was inconsistent in all planes and spectra were broad band. Temporal and spatial coherence occurred in other SVT. VT-MM maintained spatial phase and a single spectral peak, while VF displayed neither. Our conclusions are that temporal and spatial phase analysis from the ECG stratifies intra-atrial and intra-ventricular organization and reveals subtle variability lost on visual inspection.     

Averaging analysis approach for stability analysis of speed-sensorless induction motor drives with stator resistance estimation

In this paper, the stability property of speed-sensorless induction motor drives with stator resistance estimation is analyzed using the averaging analysis technique. Explicit stability conditions are then derived to clarify analytically when the instability may occur and how the regressor vectors used in the estimation and the integral adaptation gains should be designed to assure stability. The derived stability conditions also reveal that the coupling between the speed and the stator resistance estimation loops is the main cause of instability and that stabilization of each individual estimation loop is necessary but insufficient to guarantee stability. Instead of the conventional regressor vectors that are shown to make the estimation unstable in some regenerative regions, two new regressor vectors are introduced to achieve stability for the whole operating conditions. Moreover, investigation of the persistently exciting (PE) conditions points out theoretically the loss of identifiability of the rotor speed and the stator resistance at no loads and at zero frequency operations. Validity of all the analytical results is verified by simulation and experiment.     

基于压缩感知的循环平稳特征检测方法

在认知无线电中,传统的循环平稳特征检测技术为了达到理想的感知效果,需要大量的数据采样点,导致其感知过程复杂度大,感知时间长.针对此问题,提出了一种基于压缩感知的改进循环平稳特征检测方法,该算法利用信号循环自相关函数(Cyclic Autocorrelation Function,CAF)的稀疏特性,基于分段平均的时变自相关函数估计值,通过压缩感知技术重构二维CAF矩阵,再根据重构结果实现循环平稳特征检测.该方法不仅可有效降低计算复杂度和检测时间,而且提高了二维CAF的估计精度.仿真结果表明该方法的检测性能优于基于经典CAF估计的循环平稳特征检测技术.     

Classification of paroxysmal and persistent atrial fibrillation in ambulatory ECG recordings

The problem of classifying short atrial fibrillatory segments in ambulatory ECG recordings as being either paroxysmal or persistent is addressed by investigating a robust approach to signal characterization. The method comprises preprocessing estimation of the dominant atrial frequency for the purpose of controlling the subbands of a filter bank, computation of the relative subband (harmonics) energy, and the subband sample entropy. Using minimum-error-rate classification of different feature vectors, a data set consisting of 24-h ambulatory recordings from 50 subjects with either paroxysmal (26) or persistent (24) atrial fibrillation (AF) was analyzed on a 10-s segment basis; a total of 212,196 segments were classified. The best performance in terms of area under the receiver operating characteristic curve was obtained for a feature vector defined by the subband sample entropy of the dominant atrial frequency and the relative harmonics energy, resulting in a value of 0.923, whereas that of the dominant atrial frequency was equal to 0.826. It is concluded that paroxysmal and persistent AFs can be discriminated from short segments with good accuracy at any time of an ambulatory recording.     

基于断裂面匹配的破碎物体拼接技术

该文研究了曲面三角网格模型顶点法矢、主曲率和主方向的计算方法,分析了曲面上点的类型,提出了一种基于断裂面匹配的破碎物体拼接方法。分别用曲面上点的有向脚标和无向脚标构成有向特征向量和无向特征向量,在无向特征向量匹配的基础上,经过匹配点方向映射方法判断其它无向特征匹配点对的有向特征向量的相似性,完成断裂面匹配计算。在断裂面匹配的基础上,通过匹配点方向映射实现破碎物体的拼接。实验结果表明该算法可靠地实现了破碎物体的拼接。     

A Quantitative Model for the Ventricular Response During Atrial Fibrillation

We review the principal statistical properties of the RR interval sequence during atrial fibrillation. A simple quantitative electrophysiologic model is presented which successfully accounts for these statistical features. In this model the atrioventricular junction (AVJ) is treated as a single cell equivalent characterized by a refractory period and spontaneous rate of phase 4 depolarization. The atria are presumed to bombard the AVJ with impulses that arrive randomly in time; each impulse induces a partial depolarization of the AVJ equivalent cell. We show that other models for the ventricular response during atrial fibrillation (e. g., concealed conduction models) do not adequately account for the salient statistical features of the RR interval sequence. The present model may be utilized to characterize a sequence of RR intervals recorded from a given individual in terms of the numerical magnitudes of the model's four parameters: the mean rate at which atrial impulses bombard the AVJ, the relative amplitude of the impulses, the relative rate of spontaneous phase 4 depolarization of the AVJ equivalent cell, and the refractory period of the AVJ equivalent cell. Such a characterization may be useful in studying mechanisms of drug action and interaction, as well as potentially offering a quantitative means for optimizing pharmacologic manangement of chronic atrial fibrillation.     

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.     

An automatic system for the analysis and classification of human atrial fibrillation patterns from intracardiac electrograms

This paper presents an automatic system for the analysis and classification of atrial fibrillation (AF) patterns from bipolar intracardiac signals. The system is made up of: 1) a feature-extraction module that defines and extracts a set of measures potentially useful for characterizing AF types on the basis of their degree of organization; 2) a feature-selection module (based on the Jeffries-Matusita distance and a branch and bound search algorithm) identifying the best subset of features for discriminating different AF types; and 3) a support vector machine technique-based classification module that automatically discriminates the AF types according to the Wells' criteria. The automatic system was applied on 100 intracardiac AF signal strips and on a selection of 11 representative features, demonstrating: a) the possibility to properly identify the most significant features for the discrimination of AF types; b) higher accuracy (97.7% using the seven most informative features) than the traditional maximum likelihood classifier; and c) effectiveness in AF classification also with few training samples (accuracy = 88.3% with only five training signals). Finally, the system identifies a combination of indices characterizing changes of morphology of atrial activation waves and perturbation of the isoelectric line as the most effective in separating the AF types.     

High efficiency activation of L-type Ca2+ current by 5-HT in human atrial myocytes

In human atrial myocytes, serotonin rather than sympathetic, stimulation is more frequently associated with atrial fibrillation. So does the arrhythmogenic effect of serotonin result from the mechanism of action of the receptor or the context of its action upon cardiac myocytes? The capacity of agonists to produce cAMP followed the sequence 5-HT < Iso < Forskolin to increase ICaL with 5-HT = Iso = Forskolin. The simultaneous application of threshold concentrations of 5-HT and Iso maximally increased ICaL. We will show that the effect of 5-HT upon human atrial myocytes is an imbalance between low production of cAMP and maximal activation of ICaL.     

宽带自适应和差波束形成与测角方法研究

针对宽带自适应空频处理的信噪比要求高、计算量大等问题,本文提出了一种基于均匀线阵的无需预延迟处理宽带空时处理结构的自适应和差波束形成与测角方法。方法利用和波束指向在多频点处的响应来建立多约束条件,以此获得基于线性约束最小方差的自适应和波束权向量,对多频点的空时二维向量修正和波束权向量得到差波束权向量,最后进行和差波束形成,对每个样本和差比幅单脉冲测角。本方法相比于常规的自适应单脉冲测角方法,可有效地处理宽带信号,不需要对每个频带信号进行检测,具有低信噪比条件下可测角、测角精确度高等特点,而且仿真分析验证了当存在主瓣干扰时,该方法仍然有效。      

线结构光三维测量系统扫描方向的标定

提出一种基于平面标靶的线结构光三维传感器扫描方向的标定方法。利用平面标靶对摄像头进行标定,得到摄像头的内部参数,将棋盘格平面标靶固定在空间某一位置,测量系统沿着扫描方向移动并采集一系列图像。根据这一系列图像求出摄像机的外部参数,并结合已经求出的摄像机内部参数计算出标靶上同一特征点在摄像机坐标系下的坐标值,对这些点进行直线拟合得到一直线方程,直线的方向就是测量系统的扫描方向。实验表明,该方法测量精度高,操作简单,无需辅助的调整设备,降低了标定设备的成本和系统校准的难度,适合现场标定。     

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.     

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,丰富原始信号的特征。进而,采用DenseNet深度卷积神经网络来处理精细的时频图,并在迭代过程中选出最佳检测模型。该方法获得的最佳检测模型在麻省理工学院-贝斯以色列医院(MIT-BIH)和2017年生理信号竞赛(2017 PhysioNet Challenge)的房颤数据集上分别取得了99.11%和97.25%的检测准确率。此外,该文将希尔伯特黄变换与其他时频分析方法以及稠密网络(DenseNet)与其他卷积神经网络进行了对比。相比于其他检测方法,实验结果表明希尔伯特黄变换和深度卷积神经网络(DCNN)为房颤检测提供了更加准确的识别方式。     

Preventive ablation strategies in a biophysical model of atrial fibrillation based on realistic anatomical data.

Ablation strategies to prevent episodes of paroxysmal atrial fibrillation (AF) have been subject to many clinical studies. The issues mainly concern pattern and transmurality of the lesions. This paper investigates ten different ablation strategies on a multilayered 3-D anatomical model of the atria with respect to 23 different setups of AF initiation in a biophysical computer model. There were 495 simulations carried out showing that circumferential lesions around the pulmonary veins (PVs) yield the highest success rate if at least two additional linear lesions are carried out. The findings compare with clinical studies as well as with other computer simulations. The anatomy and the setup of ectopic beats play an important role in the initiation and maintenance of AF as well as the resulting therapy. The computer model presented in this paper is a suitable tool to investigate different ablation strategies. By including individual patient anatomy and electrophysiological measurement, the model could be parameterized to yield an effective tool for future investigation of tailored ablation strategies and their effects on atrial fibrillation.     

一种新的快速局部不变特征算法

针对传统局部不变特征算子主方向提取不准确和匹配阶段过于耗时的问题,提出一种基于RI-LBP 算子和混合spill 树的快速局部不变特征算法。首先提出一种FAST-Difference 算法,提取出模板图像和待匹配图像的稳定特征点,然后使用旋转不变的RI-LBP 描述符计算特征向量,最后对特征向量集使用混合spill 树进行匹配并使用RANSAC 算法剔除误匹配点。RI-LBP 算子自身的旋转不变性能够在一定程度上克服特征点主方向确定不准确的缺点,使特征描述符的提取更加稳定,并生成更简单的53 维局部不变特征描述符。混合spill 树相对于kd-tree 省略了回溯过程,对于高维数据拥有更好的匹配效率。实验证明:该算法与SURF 算法描述能力相近,旋转和光照条件下比SURF 性能更优,并且匹配速度更快。     

Propagation pattern analysis during atrial fibrillation based on sparse modeling

In this study, sparse modeling is introduced for the estimation of propagation patterns in intracardiac atrial fibrillation (AF) signals. The estimation is based on the partial directed coherence function, derived from fitting a multivariate autoregressive model to the observed signal using least-squares (LS) estimation. The propagation pattern analysis incorporates prior information on sparse coupling as well as the distance between the recording sites. Two optimization methods are employed for estimation of the model parameters, namely, the adaptive group least absolute selection and shrinkage operator (aLASSO), and a novel method named the distance-adaptive group LASSO (dLASSO). Using simulated data, both optimization methods were superior to LS estimation with respect to detection and estimation performance. The normalized error between the true and estimated model parameters dropped from 0.20 ± 0.04 for LS estimation to 0.03 ± 0.01 for both aLASSO and dLASSO when the number of available data samples exceeded the number of model parameters by a factor of 5. For shorter data segments, the error reduction was more pronounced and information on the distance gained in importance. Propagation pattern analysis was also studied on intracardiac AF data, the results showing that the identification of propagation patterns is substantially simplified by the sparsity assumption.     

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. The remaining artifacts tend to induce erroneous DF estimates. In this paper, we report on the use of PRSA in the context of noninvasive AF classification procedures for improving DF estimation. The potential of PRSA is demonstrated by experiments both on synthetic and clinical ECG signals.