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.     

Computer analysis of the electrocardiogram during esophageal pacingcardiac stress

It has been estimated that 15 to 30% of patients with suspected or known coronary artery disease are unable to perform an adequate exercise stress test due to a variety of reasons such as obesity, poor physical condition, claudication, etc. Transesophageal atrial pacing has been proposed as a noninvasive alternative for inducing cardiac stress in patients who cannot exercise. Although computer analysis is commonly employed to analyze the electrocardiogram (ECG) during the conventional exercise stress test, the surface ECG recorded during transesophageal atrial pacing is contaminated with large pacing artifacts which confound beat identification by standard computer software. We report the development of a robust signal processing algorithm for interpretation of the surface ECG during transesophageal atrial pacing stress. The algorithm employs novel schemes using both linear and nonlinear transformations to detect and differentiate between the pacing artifact and QRS complex even in difficult situations where the pacing artifact is in proximity to or superimposed on the QRS complex. The algorithm uses sophisticated logic for automatic recognition of sustained capture. It subsequently calculates beat-by-beat and average (over five beats) ST segment amplitude and slope. The algorithm also reports the instantaneous heart rate, RR interval, pace-to-R interval, R-wave amplitude, and estimated sinus node recovery time upon loss of sustained capture. The limitations of present exercise ECG computer methods in processing the ECG during transesophageal atrial pacing stress are evaluated and significantly improved performance by our algorithm is demonstrated.     

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.      

Effects of strong pulsed magnetic fields on the cardiac activity ofan open chest dog

The heart of an open chest dog was stimulated by strong magnetic fields which were damped sinusoidal pulses with the one-cycle period of 1.47 ms. Stimulation effects were detected by electrocardiograph (ECG) and arterial blood pressure as a function of the strength of the field, the triggering point in the cardiac cycle, and the position of a stimulating coil. The threshold for arrhythmias was a minimum for the stimuli triggered at the apex of the T wave and on the P wave in the ECG. Premature ventricular and premature atrial contractions occurred according to whether the coil was placed over the ventricles or the atria. Ventricular defibrillation can not be attained by the magnetic stimulus with the flux density of 9.2 T which was the maximum field used     

n电平空间矢量算法的优化及其硬件实现

 本文提出了一种适合硬件实现的多电平空间矢量调制算法,该算法利用空间矢量图的几何对称性来实现算法优化.多电平空间矢量图可以划分为几何形状完全一致的六大扇区,优化算法通过扇区之间的对应关系把矢量调制算法的计算集中在一个扇区内完成.与传统的空间矢量算法相比,计算量减少为原来的1/6,更适合用硬件实现.为了设计出的硬件电路具有通用性,本文给出了具体设计过程.最后,文章以两电平和三电平IP(Intellectual Property)核的设计为实例验证了优化算法的正确性和有效性.     

Adaptive optimal pulse-width modulation for the line-side converterof electric locomotives

Two methods of generating synchronous online optimal PWM sequences for the line-side converter of electrical locomotives are described. The properties of the feeding supply line render the system oscillatory at multiple resonance frequencies, which are time-variable functions of the railway track topography and of the respective locations of traction vehicles. The prevailing topographic conditions define a time-variable virtual model of the overhead line, the harmonic energy of which is the optimum criterion to be minimized. The 176 switching instants of a nine-level PWM converter voltage are optimized using an online algorithm. The necessary computations are performed in the time intervals between two commutations. The performance is illustrated by measurements obtained from a real-time multiprocessing model of an extended railway track topography, including substations and locomotives. The developed hardware structure is designed for the implementation in a railway traction vehicle     

Spatiotemporal blind source separation approach to atrial activity estimation in atrial tachyarrhythmias

The analysis and characterization of atrial tachyarrhythmias requires, in a previous step, the extraction of the atrial activity (AA) free from ventricular activity and other artefacts. This contribution adopts the blind source separation (BSS) approach to AA estimation from multilead electrocardiograms (ECGs). Previously proposed BSS methods for AA extraction-e.g., independent component analysis (ICA)-exploit only the spatial diversity introduced by the multiple spatially-separated electrodes. However, AA typically shows certain degree of temporal correlation, with a narrowband spectrum featuring a main frequency peak around 3.5-9 Hz. Taking advantage of this observation, we put forward a novel two-step BSS-based technique which exploits both spatial and temporal information contained in the recorded ECG signals. The spatiotemporal BSS algorithm is validated on simulated and real ECGs from a significant number of atrial fibrillation (AF) and atrial flutter (AFL) episodes, and proves consistently superior to a spatial-only ICA method. In simulated ECGs, a new methodology for the synthetic generation of realistic AF episodes is proposed, which includes a judicious comparison between the known AA content and the estimated AA sources. Using this methodology, the ICA technique obtains correlation indexes of 0.751, whereas the proposed approach obtains a correlation of 0.830 and an error in the estimated signal reduced by a factor of 40%. In real ECG recordings, we propose to measure performance by the spectral concentration (SC) around the main frequency peak. The spatiotemporal algorithm outperforms the ICA method, obtaining a SC of 58.8% and 44.7%, respectively.     

Direct computation of ultrasound phased-array driving signals froma specified temperature distribution for hyperthermia

This paper presents a new method which obtains ultrasound hyperthermia applicator phased-array element driving signals from a desired temperature distribution. The approach combines a technique which computes array element driving signals from focal point locations and intensities with a new technique which calculates focal point locations and power deposition values from temperature requirements. Temperature specifications appear here as upper and lower bounds within the tumor volume, and a focal point placement algorithm chooses focal patterns capable of achieving the temperature range objective. The linear algebraic structure of the method allows rapid calculation of both the phased-array driving signals and an approximate temperature field response. Computer simulations verify the method with a spherical section array (SSA) for a variety of temperature specifications and blood perfusion values. This scheme, which applies to any phased-array geometry, completes an essential step in both treatment planning and feedback for hyperthermia with ultrasound phased-array applicators.     

Atrial activity extraction for atrial fibrillation analysis using blind source separation

This contribution addresses the extraction of atrial activity (AA) from real electrocardiogram (ECG) recordings of atrial fibrillation (AF). We show the appropriateness of independent component analysis (ICA) to tackle this biomedical challenge when regarded as a blind source separation (BSS) problem. ICA is a statistical tool able to reconstruct the unobservable independent sources of bioelectric activity which generate, through instantaneous linear mixing, a measurable set of signals. The three key hypothesis that make ICA applicable in the present scenario are discussed and validated: 1) AA and ventricular activity (VA) are generated by sources of independent bioelectric activity; 2) AA and VA present non-Gaussian distributions; and 3) the generation of the surface ECG potentials from the cardioelectric sources can be regarded as a narrow-band linear propagation process. To empirically endorse these claims, an ICA algorithm is applied to recordings from seven patients with persistent AF. We demonstrate that the AA source can be identified using a kurtosis-based reordering of the separated signals followed by spectral analysis of the sub-Gaussian sources. In contrast to traditional methods, the proposed BSS-based approach is able to obtain a unified AA signal by exploiting the atrial information present in every ECG lead, which results in an increased robustness with respect to electrode selection and placement.     

Statistical accuracy of a moving equivalent dipole method to identify sites of origin of cardiac electrical activation

While radio frequency (RF) catheter ablation (RCA) procedures for treating ventricular arrhythmias have evolved significantly over the past several years, the use of RCA has been limited to treating slow ventricular tachycardias (VTs). In this paper, we present preliminary results from computer and animal studies to evaluate the accuracy of an algorithm that uses the single equivalent moving dipole (SEMD) model in an infinite homogeneous volume conductor to guide the RF catheter to the site of origin of the arrhythmia. Our method involves measuring body surface electrocardiographic (ECG) signals generated by arrhythmic activity and by bipolar current pulses emanating from a catheter tip, and representing each of them by a SEMD model source at each instant of the cardiac cycle, thus enabling rapid repositioning of the catheter tip requiring only a few cycles of the arrhythmia. We found that the SEMD model accurately reproduced body surface ECG signals with a correlation coefficients > 0.95. We used a variety of methods to estimate the uncertainty of the SEMD parameters due to measurement noise and found that at the time when the arrhythmia is mostly localized during the cardiac cycle, the estimates of the uncertainty of the spatial SEMD parameters (from ECG signals) are between 1 and 3 mm. We used pacing data from spatially separated epicardial sites in a swine model as surrogates for focal ventricular arrhythmic sources and found that the spatial SEMD estimates of the two pacing sites agreed with both their physical separation and orientation with respect to each other. In conclusion, our algorithm to estimate the SEMD parameters from body surface ECG can potentially be a useful method for rapidly positioning the catheter tip to the arrhythmic focus during an RCA procedure.     

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.     

Thermal-electrical modeling for epicardial atrial radiofrequency ablation

Epicardial radiofrequency ablation is increasingly being used for intraoperative treatment of atrial fibrillation. However, the effect of different parameters on the lesion characteristics has not been sufficiently characterized. We used a finite element model to calculate the temperature distribution in the atrial tissue under different conditions during a constant voltage radiofrequency ablation. Our simulation results show that although in the case of a thin atrium the lesion was less deep for a thin atrium, it was easier to achieve transmurality. While considering a thinner atrium, the location of the hottest point of the lesion shifted from the electrode tip to epicardial surface. This effect was due to the convective cooling of the circulating blood inside the atrium. This convective cooling phenomenon has almost negligible effects for atria thicker than 3 mm. The variability of the cooling values has no significant effect on the lesion, even for thin atria (1-2 mm). Increasing the electrode insertion depth (ID) in the tissue produced larger lesions. However, for thinner atria (thickness <2 mm), this increase in the ID reduced the lesion width. It was also proved that the presence of a fat layer between the electrode and the atrial tissue decreased significantly the lesion dimensions.     

Convolutive blind source separation algorithms applied to the electrocardiogram of atrial fibrillation: study of performance

The analysis of the surface electrocardiogram (ECG) is the most extended noninvasive technique in medical diagnosis of atrial fibrillation (AF). In order to use the ECG as a tool for the analysis of AF, we need to separate the atrial activity (AA) from other cardioelectric signals. In this matter, statistical signal processing techniques, like blind source separation (BSS), are able to perform a multilead statistical analysis with the aim to obtain the AA. Linear BSS techniques can be divided in two groups depending on the mixing model: algorithms where instantaneous mixing of sources is assumed, and convolutive BSS (CBSS) algorithms. In this work, a comparison of performance between one relevant CBSS algorithm, namely Infomax, and one of the most effective independent component analysis (ICA) algorithms, namely FastICA, is developed. To carry out the study, pseudoreal AF ECGs have been synthesized by adding fibrillation activity to normal sinus rhythm. The algorithm performances are expressed by two indexes: the signal to interference ratio (SIRAA) and the cross-correlation (RAA) between the original and the estimated AA. Results empirically prove that the instantaneous mixing model is the one that obtains the best results in the AA extraction, given that the mean SIRAA obtained by the FastICA algorithm (37.6 +/- 17.0 dB) is higher than the main SIRAA obtained by Infomax (28.5 +/- 14.2 dB). Also the RAA obtained by FastICA (0.92 +/- 0.13) is higher than the one obtained by Infomax (0.78 +/- 0.16).     

一种心电监测和房颤预警系统的研究

随着社会进步和经济的发展,在人们生活水平提高的同时,各种心血管疾病成为人类健康的隐形杀手。本文提出了一种基于嵌入式架构的便携式心电监测和房颤预警系统,实现了受试者心电信号实时采集监测的功能,采集数据通过无线网络传输至云端进行存储,监测者可以远程获取云上存储的心电监测数据,下载并采用基于主分量解析分析去获取受试者心电房颤的特征信息,准确判断受试者是否出现房颤的情况,从而实现受试者的心脏健康状况,监测结果可以在监测设备显示屏以及远程安卓手机的APP程序中进行显示。本研究所开发的系统具有成本低廉、操作简便、运行可靠等优势。     

Frequency tracking of atrial fibrillation using hidden Markov models.

A hidden Markov model (HMM) is employed to improve noise robustness when tracking the dominant frequency of atrial fibrillation (AF) in the electrocardiogram (ECG). Following QRST cancellation, a sequence of observed frequency states is obtained from the residual ECG, using the short-time Fourier transform. Based on the observed state sequence, the Viterbi algorithm retrieves the optimal state sequence by exploiting the state transition matrix, incorporating knowledge on AF characteristics, and the observation matrix, incorporating knowledge of the frequency estimation method and signal-to-noise ratio (SNR). The tracking method is evaluated with simulated AF signals to which noise, obtained from ECG recordings, has been added at different SNRs. The results show that the use of HMM improves performance considerably by reducing the rms error associated with frequency tracking: at 4-dB SNR, the rms error drops from 0.2 to 0.04 Hz.     

A new Walsh domain technique of harmonic elimination and voltagecontrol in pulse-width modulated inverters

A method for selective harmonic elimination in pulse-width-modulated (PWM) inverter waveforms by the use of Walsh functions is presented. The Walsh operational matrix of PWM is introduced as a means of obtaining the Walsh spectral equations of PWM waveforms. The slope and intercept Fourier operational matrices of PWM are also introduced as a means of obtaining Fourier spectral equations of PWM waveforms. A noniterative algorithm that produces piecewise-linear, global solutions between angles and for the angles is proposed. The algorithm also produces the full range of variation of fundamental voltage for given harmonic elimination constraints. The set of systems of linear equations obtained replaces the system of nonlinear transcendental equations used in the Fourier series harmonic elimination approach. In general, the algorithm makes possible the synthesis of two-state PWM inverter waveforms with specified old harmonic content     

Relationship between space-vector modulation and three-phasecarrier-based PWM: a comprehensive analysis [three-phase inverters]

This paper comprehensively analyzes the relationship between space-vector modulation and three-phase carrier-based pulse width modulation (PWM). The relationships involved, such as the relationship between modulation signals (including zero-sequence component and fundamental components) and space vectors, the relationship between the modulation signals and the space-vector sectors, the relationship between the switching pattern of space-vector modulation and the type of carrier, and the relationship between the distribution of zero vectors and different zero-sequence signal are systematically established. All the relationships provide a bidirectional bridge for the transformation between carrier-based PWM modulators and space-vector modulation modulators. It is shown that all the drawn conclusions are independent of the load type. Furthermore, the implementations of both space-vector modulation and carrier-based PWM in a closed-loop feedback converter are discussed     

一种新颖的脉宽调制平均分割调光算法的设计与实现

提出了一种新颖的16bit脉宽调制(PWM)平均分割调光算法,其映射电路满足LED光亮度在0～100%间精细调光。该算法将整个PWM周期均分为多个小的灰度周期,同时对灰度数据权值位进行分割处理,以克服高权值位对灰度均匀性的影响,提高了灰阶亮度的视觉刷新率,且有效消除低亮度时的闪烁问题。采用HSIM对整体电路进行了仿真验证,结果表明,PWM输出波形具有良好的均匀性。基于TSMC0.6μm BCD工艺实现的调光电路有效芯片面积小于0.3mm2,对采用本设计的一款RGBLED驱动芯片进行流片、测试,验证了该调光电路能够正常工作。     

Comparison of atrial signal extraction algorithms in 12-lead ECGs with atrial fibrillation

Analysis of atrial rhythm is important in the treatment and management of patients with atrial fibrillation. Several algorithms exist for extracting the atrial signal from the electrocardiogram (ECG) in atrial fibrillation, but there are few reports on how well these techniques are able to recover the atrial signal. We assessed and compared three algorithms for extracting the atrial signal from the 12-lead ECG. The 12-lead ECGs of 30 patients in atrial fibrillation were analyzed. Atrial activity was extracted by three algorithms, Spatiotemporal QRST cancellation (STC), principal component analysis (PCA), and independent component analysis (ICA). The amplitude and frequency characteristics of the extracted atrial signals were compared between algorithms and against reference data. Mean (standard deviation) amplitude of QRST segments of V1 was 0.99 (0.54) mV, compared to 0.18 (0.11) mV (STC), 0.19 (0.13) mV (PCA), and 0.29 (0.22) mV (ICA). Hence, for all algorithms there were significant reductions in the amplitude of the ventricular activity compared with that in V1. Reference atrial signal amplitude in V1 was 0.18 (0.11) mV, compared to 0.17 (0.10) mV (STC), 0.12 (0.09) mV (PCA), and 0.18 (0.13) mV (ICA) in the extracted atrial signals. PCA tended to attenuate the atrial signal in these segments. There were no significant differences for any of the algorithms when comparing the amplitude of the reference atrial signal with that of the extracted atrial signals in segments in which ventricular activity had been removed. There were no significant differences between algorithms in the frequency characteristics of the extracted atrial signals. There were discrepancies in amplitude and frequency characteristics of the atrial signal in only a few cases resulting from notable residual ventricular activity for PCA and ICA algorithms. In conclusion, the extracted atrial signals from these algorithms exhibit very similar amplitude and frequency characteristics. Users of these algorithms should be observant of residual ventricular activities which can affect the analysis of the fibrillatory waveform in clinical practice.     

Gaussian Noise Filtering from ECG by Wiener Filter and Ensemble Empirical Mode Decomposition

Empirical mode decomposition (EMD) is a powerful algorithm that decomposes signals as a set of intrinsic mode function (IMF) based on the signal complexity. In this study, partial reconstruction of IMF acting as a filter was used for noise reduction in ECG. An improved algorithm, ensemble EMD (EEMD), was used for the first time to improve the noise-filtering performance, based on the mode-mixing reduction between near IMF scales. Both standard ECG templates derived from simulator and Arrhythmia ECG database were used as ECG signal, while Gaussian white noise was used as noise source. Mean square error (MSE) between the reconstructed ECG and original ECG was used as the filter performance indicator. FIR Wiener filter was also used to compare the filtering performance with EEMD. Experimental result showed that EEMD had better noise-filtering performance than EMD and FIR Wiener filter. The average MSE ratios of EEMD to EMD and FIR Wiener filter were 0.71 and 0.61, respectively. Thus, this study investigated an ECG noise-filtering procedure based on EEMD. Also, the optimal added noise power and trial number for EEMD was also examined.