Prediction of paroxysmal atrial fibrillation by analysis of atrial premature complexes

Currently, no reliable method exists to predict the onset of paroxysmal atrial fibrillation (PAF). We propose a predictor that includes an analysis of the R-R time series. The predictor uses three criteria: the number of premature atrial complexes (PAC) not followed by a regular R-R interval, runs of atrial bigeminy and trigeminy, and the length of any short run of paroxysmal atrial tachycardia. An increase in activity detected by any of these three criteria is an indication of an imminent episode of PAF. Using the Physionet database of the Computers in Cardiology 2001 Challenge, the predictor achieved a sensitivity of 89% and a specificity of 91%.     

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.     

Adaptive interference cancellation for DS-CDMA systems using neuralnetwork techniques

The objective of this study is to apply and investigate a neural network-based decision feedback scheme for interference suppression in direct sequence code division multiple access (DS-CDMA) wireless networks. It is demonstrated that a decision feedback functional link equalizer (DFFLE) in combination with an eigenvector network can closely approximate a Bayesian receiver with significant advantages, such as improved bit-error ratio (BER) performance, adaptive operation, and single-user detection in a multiuser environment. It is assumed that the spreading codes of the interfering users will be unknown to the receiver. This detector configuration is appropriate for downlink communication between a base station and a mobile user in a digital wireless network. The BER performance in the presence of interfering users is evaluated. The improved performance of such a DFFLE receiver for CDMA is attributed to the nonlinear decision boundary it evaluates for the desired user. The receiver structure is also capable of rapid adaptation in a dynamic communications scenario for which there is entry/exit of users and imperfect power control. The convergence performance and error propagation of the DFFLE receiver are also considered and exhibit reasonable promise for third generation wireless DS-CDMA networks     

Pilot aided techniques for system caused phase jitter cancellation

A pilot-based method of extracting and cancelling system caused pilot jitter (SCPJ) in broadcasting systems is introduced and analyzed. It was demonstrated that, by using a wideband pilot extraction system instead of the frequently used minimal bandwidth one, the system performance can be improved considerably. Analytical results for the CNR degradation of a 16-QAM system operated in the presence of sinusoidal SCPJ were obtained as a function of the extraction filters bandwidth, as well as their amplitude and group delay distortions. It was shown that to achieve efficient SCPJ cancellation, it is important to compensate for both of these distortions. However, as far as implementation issues are concerned, group delay distortion seems to be a more prominent source of degradation     

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     

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.     

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.     

MPEG-2视频信号错误控制和错误掩盖技术

以ＭＰＥＧ－２的语法规范作基础,从控制错误发生和控制错误传播的角度,简述了ＭＥＰＧ－２的分级工具和视频码流层结构,比较详细地介绍了Ｉ帧、Ｐ帧和Ｂ帧的错误掩盖技术,此外,还推荐了一些错误掩盖方法。     

Spectral analysis of arterial blood pressure in the rat during atrial fibrillation

This paper describes the development of a systems identification protocol in the rat for use in studies of the dynamics of blood pressure control The method is based on Taylor's canine random heart model and employs electrically induced atrial fibrillation to generate random fluctuations in arterial blood pressure. In order to evaluate the utility of the protocol, recordings of pulsatile blood pressure were obtained from the femoral arteries of anesthetized rats during atrial fibrillation. The data were reduced to spectral density function estimates using standard techniques of discrete spectral analysis. The results indicate that during atrial fibrillation, the time course of arterial blood pressure constitutes a white noise source in the frequency band from 0.01 to 10 Hz, in sharp contrast to the concentration of energy from the normal cardiac cycle into narrow frequency bands within this range. Thus, the protocol should be useful in the analysis of the dynamics of most physiological processes which respond to changes in blood pressure.     

Prediction/cancellation techniques for fading broadcastingchannels. II. CPM signals

For pt.I see ibid., vol.36, no.2, p.146-55, 1990. The authors study and generalize the application of the fading prediction/cancellation technique introduced in pt.I, to mobile broadcasting transmission systems employing continuous phase modulation (CPM) signaling formats. Based on the maximum likelihood ratio test (MLRT), an algorithm was developed that results in a fading cancellation detector. The previously proposed technique is extended to include novel multisample per received symbol receivers. Although the methodology is general enough to accommodate any CPM signalling format, the authors are dealing mainly with signals of the minimum shift keying (MSK) type. The analysis includes also various generalizations, such as processing in a continuous-time fashion as well as reduced-complexity detectors. The obtained performance evaluation results indicate that for the same channel conditions as in pt.I, i.e. for a mixture of additive with Gaussian noise and multiplicative, nonselective fading, even higher bit error rate (BER) performance improvements as compared to those reported are possible     

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.     

Echo identification and cancellation techniques for antenna measurement in non-anechoic test sites

This paper focuses on the measurement of the antenna radiation patterns when fully anechoic conditions are not available and, as consequence, some undesirable echoes are initially present in the measure. Two techniques are analyzed and compared, which - starting from data measured in the frequency domain - allow the echo contributions to be identified and the antenna radiation pattern to be retrieved. The accuracy of both techniques is evaluated at the frequency of 22 GHz by comparison with measurements obtained in an anechoic chamber.     

Prediction/cancellation techniques for fading broadcastingchannels. I. PSK signals

An approach for reducing the effects of multiplicative noise, such as fading, on the performance of mobile broadcasting transmission systems is introduced. The proposed method is based on a noise prediction/cancellation technique and is applied to phase-shift keyed (PSK) signals. By exploiting the statistical characteristics of the multipath fading signal and its strong correlation properties, a novel sequential receiver structure is derived that uses a detection algorithm which identifies the most probable transmitted sequence in the maximum-likelihood detection sense. The algorithm has been obtained for both Rayleigh and Rician fading channels. The proposed detection technique has been evaluated for various QPSK schemes operated in channels corrupted by a combination of additive white Gaussian noise (AWGN) and fading. The computer simulation results obtained show that by using a relatively simple receiver with a prediction algorithm of second order, considerable error floor reductions are achieved by the proposed receivers. As a direct result of these error floor reductions substantial bit error rate (BER) improvements of more than three orders of magnitude over conventionally detected schemes are obtained     

Use of cancellation techniques in the measurement of atmospheric crosspolarisation

Some of the errors implicit in atmospheric crosspolarisation-measurement systems are given, together with their limitations on the accuracy of the resultant measurements. A cancellation technique is described that allows the `clear-weather? performance of measurement links to be considerably improved. The limitations due to rainfall of such a cancellation system on the accuracy of crosspolarisation measurements are investigated, and the system is shown to be preferable to a conventional one.     

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.     

A high-temporal resolution algorithm for quantifying organization during atrial fibrillation

Atrial fibrillation (AF) has been described as a "random" or "chaotic" rhythm. Evidence suggests that AF may have transient episodes of temporal and spatial organization. We introduce a new algorithm that quantifies AF organization by the mean-squared error (MSE) in the linear prediction between two cardiac electrograms. This algorithm calculates organization at a finer temporal resolution. (approximately 300 ms) than previously published algorithms. Using canine atrial epicardial mapping data, we verified that the MSE algorithm showed nonfibrillatory rhythms to be significantly more organized than fibrillatory rhythms (p < .00001). Further, we compared the sensitivity of MSE to that of two previously published algorithms by analyzing AF with simulated noise and AF manipulated with vagal stimulation or by adenosine administration to alter the character of the AF. MSE performed favorably in the presence of noise. While all three algorithms distinguished between low and high vagal AF, MSE was the most sensitive in its discrimination. Only MSE could distinguish baseline AF from AF with adenosine. We conclude that our algorithm can distinguish different levels of organization during AF with a greater temporal resolution and sensitivity than previously described algorithms. This algorithm could lead to new ways of analyzing and understanding AF as well as improved techniques in AF therapy.     

Constrained registration for motion compensation in atrial fibrillation ablation procedures

Fluoroscopic overlay images rendered from preoperative volumetric data can provide additional anatomical details to guide physicians during catheter ablation procedures for treatment of atrial fibrillation (AFib). As these overlay images are often compromised by cardiac and respiratory motion, motion compensation methods are needed to keep the overlay images in sync with the fluoroscopic images. So far, these approaches have either required simultaneous biplane imaging for 3-D motion compensation, or in case of monoplane X-ray imaging, provided only a limited 2-D functionality. To overcome the downsides of the previously suggested methods, we propose an approach that facilitates a full 3-D motion compensation even if only monoplane X-ray images are available. To this end, we use a training phase that employs a biplane sequence to establish a patient specific motion model. Afterwards, a constrained model-based 2-D/3-D registration method is used to track a circumferential mapping catheter. This device is commonly used for AFib catheter ablation procedures. Based on the experiments on real patient data, we found that our constrained monoplane 2-D/3-D registration outperformed the unconstrained counterpart and yielded an average 2-D tracking error of 0.6 mm and an average 3-D tracking error of 1.6 mm. The unconstrained 2-D/3-D registration technique yielded a similar 2-D performance, but the 3-D tracking error increased to 3.2 mm mostly due to wrongly estimated 3-D motion components in X-ray view direction. Compared to the conventional 2-D monoplane method, the proposed method provides a more seamless workflow by removing the need for catheter model re-initialization otherwise required when the C-arm view orientation changes. In addition, the proposed method can be straightforwardly combined with the previously introduced biplane motion compensation technique to obtain a good trade-off between accuracy and radiation dose reduction.     

两种相位抵消法消侧音原理及其电路形式

为帮助正确理解及运用常见的消侧音电路,分别讨论了加法和减法电路实现的相位抵消法消侧音原理。几种典型电路均用到运算放大器。为直观认识每种电路的特点,估算了接收方获得信号和发送方输出信号的比值（电压比）,每种电路均经TINA-TI软件仿真和实际电路验证,估算值和仿真、验证结果一致。这些消侧音原理和电路可应用在楼宇对讲、无线对讲等场合。最后,分享了一些设计和制作消侧音电路的经验。     

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.