Classification of electrocardiographic P-wave morphology

The atrial activity of the human heart is normally visible in the electrocardiogram as a P-wave. In patients with intermittent atrial fibrillation, a different P-wave morphology can sometimes be seen, indicating atrial conduction defects. The purpose of this study was to develop a method to discriminate between such P-waves and normal ones. 20 recordings of each type were used in a classification which, based on impulse response analysis of the P-wave and linear discrimination between various parameters, produced a correct classification in 37 of the 40 recordings (sensitivity 95%, specificity 90%).     

Localization of the site of origin of cardiac activation by means of a heart-model-based electrocardiographic imaging approach

We have developed a new approach to solve the inverse problem of electrocardiography in terms of heart model parameters. The inverse solution of the electrocardiogram (ECG) inverse problem is defined, in the present study, as the parameters of the heart model, which are closely related to the physiological and pathophysiological status of the heart, and is estimated by using an optimization system of heart model parameters, instead of solving the matrix equation relating the body surface ECGs and equivalent cardiac sources. An artificial neural network based preliminary diagnosis system has been developed to limit the searching space of the optimization algorithm and to initialize the model parameters in the computer heart model. The optimal heart model parameters were obtained by minimizing the objective functions, as functions of the observed and model-generated body surface ECGs. We have tested the feasibility of the newly developed technique in localizing the site of origin of cardiac activation using a pace mapping protocol. The present computer simulation results show that, the present approach for localization of the site of origin of ventricular activation achieved an averaged localization error of about 3 mm [for 5-muV Gaussian white noise (GWN)] and 4 mm (for 10-muV GWN), with standard deviation of the localization errors of being about 1.5 mm. The present simulation study suggests that this newly developed approach provides a robust inverse solution, circumventing the difficulties of the ECG inverse problem, and may become an important alternative to other ECG inverse solutions.     

Correlation between P-wave morphology and origin of atrial focal tachycardia--insights from realistic models of the human atria and torso

Atrial arrhythmias resulting from abnormally rapid focal activity in the atria may be reflected in an altered P-wave morphology (PWM) in the ECG. Although clinically important, detailed relationships between PWM and origins of atrial focal excitations have not been established. To study such relationships, we developed computational models of the human atria and torso. The model simulation results were used to evaluate an extant clinical algorithm for locating the origin of atrial focal points from the ECG. The simulations showed that the algorithm was practical and could predict the atrial focal locations with 85% accuracy. We proposed a further refinement of the algorithm to distinguish between focal locations within the large atrial bundles.     

办公室环境下的超宽带信道测量与建模

依据广泛的频域信道测量数据,提出了符合中国超宽带(UWB)技术频率使用规定的办公室室内信道模型。信道总体模型采用修正Saleh-Valenzuela (S-V)模型。在信道测量信号的后处理中,使用过渡带为高斯滚降特性的类高斯窗来提取符合中国超宽带频谱规范的测量信号。利用CLEAN算法从时域测量数据中提取高分辨率的离散信道响应,并为信道时域测量信号提出了一种基于小波分析的自动分簇算法,统计提取出了大尺度和小尺度信道模型参数。结果表明:提出的办公室超宽带信道模型和实测数据具有相近的时延扩展特性和平均多径数量,可以比IEEE 802.15.4a信道模型更好地反映中国办公室环境下的UWB信道特性。     

A nonlinear Bayesian filtering framework for ECG denoising

In this paper, a nonlinear Bayesian filtering framework is proposed for the filtering of single channel noisy electrocardiogram (ECG) recordings. The necessary dynamic models of the ECG are based on a modified nonlinear dynamic model, previously suggested for the generation of a highly realistic synthetic ECG. A modified version of this model is used in several Bayesian filters, including the Extended Kalman Filter, Extended Kalman Smoother, and Unscented Kalman Filter. An automatic parameter selection method is also introduced, to facilitate the adaptation of the model parameters to a vast variety of ECGs. This approach is evaluated on several normal ECGs, by artificially adding white and colored Gaussian noises to visually inspected clean ECG recordings, and studying the SNR and morphology of the filter outputs. The results of the study demonstrate superior results compared with conventional ECG denoising approaches such as bandpass filtering, adaptive filtering, and wavelet denoising, over a wide range of ECG SNRs. The method is also successfully evaluated on real nonstationary muscle artifact. This method may therefore serve as an effective framework for the model-based filtering of noisy ECG recordings.     

Time-domain wavelet Galerkin modeling of two-dimensionalelectrically large dielectric waveguides

The time-domain wavelet-Galerkin method based on Daubechies' compactly supported scaling functions of high regularity has been applied to the analysis of two-dimensional dielectric slab waveguides that have typical dimensions and material parameters of optical integrated waveguide components, and the results are compared with those obtained with the conventional finite-difference time-domain method. It has been found that the proposed method allows discretization with a much coarser grid than the conventional time-domain analysis techniques due to its local sampling and highly linear numerical dispersion properties. A series of numerical experiments demonstrates the capability of the method to simulate the wave propagation of electrically large inhomogeneous media with reduced computational expenditure     

Maximum likelihood analysis of cardiac late potentials

This study presents a new time-domain method for the detection of late potentials in individual leads. Basic statistical properties of the ECG samples are modeled in order to estimate the amplitude and duration of late potentials. The signal model accounts for correlation in both time and across the ensemble of beats. Late potentials are modeled as a colored process with unknown amplitude which is disturbed by white, Gaussian noise. Maximum likelihood estimation is applied to the model for estimating the amplitude of the late potentials. The resulting estimator consists of an eigenvector-based filter followed by a nonlinear operation. The performance of the maximum likelihood procedure was compared to that obtained by traditional time-domain analysis based on the vector magnitude. It was found that the new technique yielded a substantial improvement of the signal-to-noise ratio in the function used for endpoint determination. This improvement leads to a prolongation of the filtered QRS duration in cases with late potentials     

Analysis of a novel expanded tip wire (ETW) antenna for microwave ablation of cardiac arrhythmias

A novel expanded tip wire (ETW) catheter antenna is proposed for microwave ablation for the treatment of atrial fibrillation (AF). The antenna is designed as an integral part of coaxial cable so that it can be inserted via a 6F catheter. A numerical model based on the rotationally symmetric finite-difference time-domain technique incorporating the generalized perfectly matched layer as the absorbing boundary condition has been utilized to accurately model the interaction between the antenna and the myocardium. Numerical and in-vitro experimental results are presented for specific absorption rate, return loss and heating pattern produced by the antenna. Both numerical modeling and in-vitro experimentation show that the proposed ETW antenna produces a well-defined electric field distribution that provides continuous long and linear lesions for the treatment of AF.     

Extraction and analysis of T waves in electrocardiograms during atrial flutter

Analysis of T waves in the ECG is an essential clinical tool for diagnosis, monitoring, and follow-up of patients with heart dysfunction. During atrial flutter, this analysis has been so far limited by the perturbation of flutter waves superimposed over the T wave. This paper presents a method based on missing data interpolation for eliminating flutter waves from the ECG during atrial flutter. To cope with the correlation between atrial and ventricular electrical activations, the CLEAN deconvolution algorithm was applied to reconstruct the spectrum of the atrial component of the ECG from signal segments corresponding to TQ intervals. The locations of these TQ intervals, where the atrial contribution is presumably dominant, were identified iteratively. The algorithm yields the extracted atrial and ventricular contributions to the ECG. Standard T-wave morphology parameters (T-wave amplitude, T peak-T end duration, QT interval) were measured. This technique was validated using synthetic signals, compared to average beat subtraction in a patient with a pacemaker, and tested on pseudo-orthogonal ECGs from patients in atrial flutter. Results demonstrated improvements in accuracy and robustness of T-wave analysis as compared to current clinical practice.     

A Time-Domain Approach for Extracting Broadband Macro- π Models of Differential Via Holes

A novel time-domain approach is proposed to synthesize the broadband macro-pi model of the differential vias based on time-domain reflected/transmitted waveforms either measured by time-domain reflectometry (TDR) or simulated by finite-difference time-domain (FDTD) method. The step responses of the differential via are solved in terms of rational functions by the generalized pencil-of-matrix (GPOM) method. The macro-pi model in terms of the rational functions pairs is obtained through an ABCD matrix transformation. The order of the macro-pi model can be reduced without losing the accuracy according to a residue criterion. The equivalent lumped circuits of the macro-pi model is synthesized by a lumped circuit extraction method (LCEM). The stability and passivity of the extracted models can be preserved based on this time-domain approach and the macro-pi topology. Two examples, one is an asymmentric via and the other is an differential via in four-layer PCB, are used to demonstrate the broadband accuracy of the proposed approach both in time-domain and frequency-domain     

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.      

A novel extraction method of fetal electrocardiogram from the composite abdominal signal

In contrast to the ultrasonic measurement of fetal heart motion, the fetal electrocardiogram (ECG) provides clinically significant information concerning the electrophysiological state of a fetus. In this paper, a novel method for extracting the fetal ECG from abdominal composite signals is proposed. This method consists of the cancellation of the mother's ECG and blind source separation with the reference signal (BSSR). The cancellation of the mother's ECG component was performed by subtracting the linear combination of mutually orthogonal projections of the heart vector. The BSSR is a fixed-point algorithm, the Lagrange function of which includes the higher order cross-correlation between the extracted signal and the reference signal as the cost term rather than a constraint. This realizes the convexity of the Lagrange function in a simple form, which guarantees the convergence of the algorithm. By practical application, the proposed method has been shown to be able to extract the P and T waves in addition to the R wave. The reliability and accuracy of the proposed method was confirmed by comparing the extracted signals with the directly recorded ECG at the second stage of labor. The gestational age-dependency of the physiological parameters of the extracted fetal ECG also coincided well with that of the magnetocardiogram, which proves the clinical applicability of the proposed method.     

How Many Leads Are Necessary for a Reliable Reconstruction of Surface Potentials During Atrial Fibrillation?

In this study, we aimed at determining how many leads are necessary for accurately reconstructing ECG potentials during atrial fibrillation (AF) on the body surface. Although the standard ECG is appropriate for the detection of this arrhythmia, its accuracy for extracting other diagnostic features or constructing surface potential maps may not be optimal. We evaluated the suitability of the standard ECG in AF and proposed a new lead system for improving the information content of AF signals in limited lead systems. We made use of 64-lead body surface potential mapping recordings of 17 patients during AF and 18 healthy subjects. Lead selection was performed by making use of a lead selection algorithm proposed by Lux, and error curves were calculated for increasing number of selected leads for QRS complexes and P waves from healthy subjects and AF signals. From our results, at least 23 leads are needed in order to have the same degree of accuracy in the derivation of AF waves as the 12-lead ECG for a normal QRS complex (25% error). The 12-lead ECG allows a reconstruction of surface potentials with 53% error. If a limited lead set is to be chosen, a repositioning of only four electrodes from the standard ECG reduces reconstruction error in 11%. This repositioning of electrodes may include more right anterior electrodes and one posterior electrode.     

Group-based spatio-temporal video analysis and abstraction using wavelet parameters

In this paper, we present a spatio-temporal event-based approach to video signal analysis and abstraction employing wavelet transform features. The video signal is assumed to be a sequence of overlapping independent visual components called events, which typically are temporally overlapping compact functions that describe temporal evolution of a given set of the spatial parameters of the video signal. We utilize event-based temporal decomposition technique to resolve the overlapping arrangement of the video signal that is known to be one of the main concerns in video analysis via conventional frame-based schemes. In our method, a set of spatial parameters, extracted from the video, is expressed as a linear combination of a set of temporally overlapping compact functions, called events, through an optimization process. First, to reduce computational complexity, the video sequence is divided into overlapped groups. Next, Generalized Gaussian Density (GGD) parameters, extracted from 2D wavelet transform subbands, are used as the spatial parameters. Temporal decomposition is then applied to the GGD parameters, structured as a frame-based matrix of GGD vectors, to compute the event functions and associated orthogonal GGD parameters. Frames located at event centroids, which are much smaller in number than the number of frames in the original video, are taken as candidates for the keyframes that are selected based on a distance criterion in the feature space. Our contribution is that this still image video abstraction scheme does not need shot or cluster boundary detection, unlike current methods. Experimental results confirm the efficiency and accuracy of our approach.     

Late potential recognition by artificial neural networks

Ventricular late potentials (LPs) are high-frequency low-amplitude signals obtained from signal-averaged electrocardiograms (ECGs) [SAECGs]. LPs are useful in identifying patients prone to ventricular tachycardia (VT), spontaneous or inducible during electrophysiology testing. A combination of self-organizing and supervised artificial neural network (ANN) models was developed to identify patients with a positive electrophysiology (PEP) test for inducible ventricular tachycardia from patients with a negative electrophysiology (NEP) test using LPs. We have added morphology information of vector magnitude waveform to an original set of three time-domain features of LPs, which are total QRS duration (TQRSD), high-frequency low-amplitude signal duration (HFLAD), and root-mean-square voltage (RMSV). Pattern recognition results from an ANN model with this combination feature set are superior to the results from Bayesian classification model based on conventional three time-domain features of SAECG. In order to increase the robustness of the recognition, a filtered QRS offset point is randomly shifted ±8 ms to form a fuzzy training set, which was to simulate the possible error in detecting QRS offset point of filtered SAECG. We also found that nonlinear transformation through the hidden layer of developed ANN model could increase Euclidean distance between PEP and NEP patterns     

基于CLDNN的物联网设备个体识别

针对目前个体识别中特征工程存在信号序列长、特征鲁棒性差等问题,研究了基于深度神经网络的个体识别技术。借鉴语音识别中的卷积长短时全连接神经网络(CLDNN),通过卷积神经网络提取信号的局部幅度特征,通过长短期记忆网络提取信号的全局时域特征,使用全连接网络实现特征图到设备标签的映射。在视距(LOS)信道下,采集8台LoRa调制的无线数传电台数据,加入高斯白噪声进行仿真测试。仿真表明,本文所提方法在信号序列长度为2 048点和低信噪比(0 dB)时,模型准确率达到95%;此外相较VGG16模型,本模型参数更少,在物联网设备部署方面具有一定的应用前景。     

Morphological operators

The author and colleagues have already proved that mediated morphological filters (MEDMFs) remove speckle, Gaussian or salt and pepper noise better than classical morphological filters (MFs) and linear methods. They have also demonstrated the dominance of MEDMFs in a multiple noisy environment compared with MFs and linear filters. Here, they describe novel new research that has led to new morphological operators being successfully devised, the performance of which is better than MEDMFs for both single and multiple denoising. The new operators employ a special combination of weighted median filters and MFs.     

用于光谱重叠峰和太赫兹波时域曲线的高斯拟合算法

为了拟合光谱重叠峰及太赫兹时域曲线,设计了一种动态增加高斯函数的高斯拟合算法.首先,利用去噪光谱数据的一阶导数粗略搜寻各高斯峰的位置,再根据高斯峰位置初始化多高斯函数.然后,将光谱数据与多高斯函数的均方差作为损失函数,用梯度下降法找到损失函数最小时的多高斯函数.最后,针对没有明显峰尖的光 谱重叠峰和存在负值的太赫兹时域...     

An extension of the lumped-network FDTD method to linear two-port lumped circuits

The lumped-network finite-difference time-domain (LN-FDTD) technique is an extension of the conventional finite-difference time-domain (FDTD) method that allows the systematic incorporation of linear one-port lumped networks (LNs) into a single FDTD cell. This paper presents an extension of the LN-FDTD technique, which allows linear two-port (TP)-LNs to be incorporated into the FDTD framework. The method basically consists of describing a TP-LN by means of its admittance matrix in the Laplace domain. By applying the Mobius transformation technique, we then obtain the admittance matrix of the TP-LN in the Z-transform domain. Finally, appropriate digital signal-processing methodologies are used to derive a set of difference equations that models the TP-LN behavior in the discrete-time domain. These equations are solved in combination with the Maxwell-Ampere's equation. To show the validity of the TP-LN-FDTD technique introduced here, we have considered the equivalent circuit of a chip capacitor and a linear circuit model of a generic metal-semiconductor field-effect transistor. These LNs have been placed on a microstrip gap and the scattering parameters of the resulting hybrid circuit have been computed. The results are compared with those obtained by using the electromagnetic simulator Agilent HFSS in combination with the circuital simulator ADS, and with those calculated by ADS alone. For the chip capacitor, experimental measurements have also been carried out. The agreement among all the simulated results is good. Generally speaking, the measured results agree with the simulated ones. The differences observed are mainly due to the influence of the subminiature A connectors and some mismatching at the ports.     

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.