Paul Lander

Analysis of abnormal intra-QRS potentials : Improved predictive value for arrhythmic events with the signal-averaged electrocardiogram

BACKGROUND Using the signal-averaged ECG (SAECG), this study developed a new electrical index for predicting arrhythmic events: abnormal intra-QRS potentials (AIQP). METHODS AND RESULTS We studied 173 patients followed after myocardial infarction for a mean duration of 14 +/- 7 months. Sixteen arrhythmic events occurred, defined as sudden cardiac death, documented sustained ventricular tachycardia, or non-fatal cardiac arrest. Noninvasive indices of arrhythmia risk were measured, including AIQP, conventional SAECG, Holter, and left ventricular ejection fraction (LVEF). Abnormal intra-QRS potentials were defined as abnormal signals occurring anywhere within the QRS period. They were estimated with a lead-specific, parametric modeling method that removed the smooth, predictable part of the QRS. AIQPs are characterized by the remaining transient, unpredictable component of the QRS and manifest as low-amplitude notches and slurs. A combined XYZ-lead AIQP index exhibited higher specificity (95%) and predictive value (PV) (+PV, 47%; -PV, 94%) than the conventional SAECG in combination with Holter and LVEF (specificity, 89%; +PV, 25%; -PV, 93%). CONCLUSIONS AIQP improved specificity and predictive value, compared with conventional tests, for prediction of arrhythmic events. AIQP emerged as the best noninvasive univariate predictor of arrhythmic events after myocardial infarction in this study. A review of several other reports shows that AIQP in the present study outperformed the conventional predictive indices reported in those other data sets.

Critical analysis of the signal-averaged electrocardiogram. Improved identification of late potentials.

BackgroundThis study performed a critical analysis of signal-averaging methods. The objective was to optimize detection of late potentials. Methods and ResultsWe studied two patient populations: a low-arrhythmia-risk group with no evidence of heart disease and a group with clinically documented ventricular tachycardia (VT). Filtered QRS duration (QRSD) and terminal QRS amplitude (RMS40) were measured from the vector magnitude. A QRS duration based on the latest detectable ventricular activity in any of the three individual XYZ leads was also measured. Because of improved signal-to-noise ratio, both individual lead analysis and extended (600- versus 200-beat) averaging yielded significant changes in signal-averaged ECG parameters. Both approaches gave an increased sensitivity for VT identification. Sensitivity, specificity, and accuracy were evaluated as functions of critical values of QRSD and RMS40. RMS measurements in the terminal QRS, ranging from 20 to 100 msec and including RMS40, did not contribute to maximizing sensitivity and were highly correlated with QRSD. Our results from the low-arrhythmia-risk group suggest that age and sex should be considered in the definition of late potentials. ConclusionsWe propose a VT risk stratification scheme using signal-averaged ECG parameters obtained from both individual lead and vector magnitude analysis. This allows definition of four categories of VT risk derived statistically from the study data. This definition is based on combined measures of sensitivity, specificity, and negative and positive predictive value.

Principles and signal processing techniques of the high-resolution electrocardiogram

T HIS ARTICLE presents an overview of the signal processing methods used to estimate and subsequently analyze late potentials in the high-resolution electrocardiogram (ECG). The high-resolution ECG is universally acquired using signal averaging techniques. The goal in acquisition is to improve the signal-tonoise ratio of the ECG: Resolution of signals on the order of 0.5 uV is required to detect late potentials accurately. The essential elements of signal averaging include computerized data acquisition, QRS detection and alignment, averaging, and noise measurement, and each is discussed in detail. Analysis of the signal average in the time domain is presented with discussions of filtering, vector magnitude transformation, and measurement techniques. Frequency domain analysis is introduced, with a discussion of spectral analysis techniques. Application to the high-resolution ECG is presented. Arguments for time-varying spectral representations and advanced time-frequency distributions are then considered. A summary of applications of other signal processing techniques to the high-resolution ECG follows. Several classes of Wiener filtering methods that have the potential to improve the signal-to-noise ratio significantly, compared with conventional signal averaging, are introduced. The review concludes with a description of techniques of high-resolution ECG analysis from Holter recordings and possible time-varying late potential activity.

Use of high-pass filtering to detect late potentials in the signal-averaged ECG

The authors investigate the use of digital filters for analysis of the signal-averaged ECG. They consider the basic types of digital filters and examine respective advantages and disadvantages for ECG analysis. An approach to analyzing the signal-averaged ECG using separate filters for measuring QRS offset and amplitudes is proposed. A study of 19 subjects explores the use of filters to detect low-level activity anywhere in the QRS complex.

Time-frequency plane Wiener filtering of the high-resolution ECG: development and application

The time-frequency plane Wiener (TFPW) filter is a new method, based on a posteriori Wiener filtering principles, to enhance the performance of ensemble averaging. This paper develops the mathematical aspects of the TFPW filter, and assesses its performance with elementary signals, such as sine waves and chirps, and authentic high-resolution electrocardiogram (HRECG) ensembles. The principal feature of the TFPW filter is its use of the time-frequency plane to accommodate signal nonstationarity. Using a posteriori computed statistics of the ensemble, the filter matches itself to the time-frequency structure of the signal to be estimated. The method is sufficiently general to be applicable to any class of repetitive signal with a deterministic time-frequency structure and additive noise in the ensemble. It is concluded that significant improvements in both estimated signal fidelity and noise reduction are possible with the TFPW filter, compared to conventional ensemble averaging.

The analysis of ventricular late potentials using orthogonal recordings

The use of orthogonal lead recordings to characterize signal-averaged late potentials is discussed. A theoretical analysis is made of the performances of individual orthogonal leads and their vector magnitude. Some limitations of the vector magnitude for characterizing late potentials are developed in relation to the distribution of signal and noise among its component orthogonal leads. Starting from the basic statistical assumptions required for signal averaging, an analysis of late potentials was simulated using ideal signal and noise functions. The results from theory and practice show an ability to predict the relative performances of signal-averaged orthogonal leads and their vector magnitude under typical recording conditions. This is illustrated with some observations from patient data. The conclusion of this investigation is that the vector magnitude waveform is not always able to reflect accurately the original information available in the signal-averaged orthogonal leads.<<ETX>>

Advanced time-frequency methods for signal-averaged ECG analysis

Frequency-domain techniques have been extensively investigated for the analysis of high-resolution electrocardiograms (ECGs), although the merit of frequency-domain analysis is still subject to controversy. Time-frequency analysis methods, which estimate the frequency content of a signal as a function of time, potentially provide even more information for improved ECG analysis. Some researchers report impressive results in predicting the outcome of electrophysiologic studies using the short-time Fourier transform (spectrogram). Other time-frequency representations, such as the Wigner distribution, short-time spectral estimators, and the wavelet transform, have also been investigated. The authors present a unified overview of time-frequency representations, showing that only four classes characterize most time-frequency representations. The authors describe the advantages and drawbacks of the various approaches and speculate on their promise for ECG analysis. Very preliminary experiments in applying some of these techniques to the prediction of the outcome of electrophysiologic studies have suggested some possible new research directions.

Temporal evolution of traditional versus transformed ECG-based indexes in patients with induced myocardial ischemia

The time course of changes in the electrocardiogram as a result of myocardial ischemia induced during prolonged coronary angioplasty has been studied. We have analyzed the electrocardiogram evolution during the occlusion in terms of the Ischemic Changes Sensor, which is a parameter that describes the capacity of different indexes to detect induced changes. Traditional indexes at specific time locations (ST level, T wave amplitude and position, and durations of QT interval and QRS complex) and global indexes (based on the Karhunen-Loève transform as applied to the QRS complex, ST-T complex, ST segment and T wave) have been considered. The global indexes better detected ischemic changes than the traditional indexes. The most sensitive were the index for the ST-T complex (89%) in the Karhunen-Loève transform-derived group and for the ST level (61%) in the traditional group. Changes in the ventricular repolarization period usually appeared earlier (77% of patients) than changes in the depolarization period (23% of patients). A similar percentage of patients exhibited the earliest ischemic changes in the T wave (41%) and in the ST segment (36%). The evolution of the Ischemic Changes Sensor parameters showed that the majority (60%) of the total changes occurred during the first minute of occlusion. The results suggest that the use of global electrocardiogram indexes better reflect ischemic changes than do traditional indexes, such as the ST segment deviation.

Time-frequency plane Wiener filtering of the high-resolution ECG: background and time-frequency representations

This paper introduces the concept of a posteriori Wiener filtering (APWF), performed in the time-frequency plane. The objective is to improve the signal-to-noise ratio (SNR) of the ensemble-averaged high-resolution electrocardiogram (HRECG). APWF was developed to address the problem of a limited ensemble size for estimating ensemble-averaged evoked potentials. For the HRECG, the authors identify the major challenge as adapting the time-frequency structure of the filter to that of low-level cardiac signals. Technical limitations and the characteristics of HRECG signals make time-frequency analysis of the ensemble average problematic. Normal and abnormal signal components are difficult to distinguish due to low time-frequency energy concentration and limited spectrotemporal resolution. However, considering the entire ensemble of repetitive ECG records, signal and noise components are separable in the time-frequency plane. This forms the basis of the new time-frequency plane Wiener (TFPW) filter, applicable to any ensemble averaging problem involving repetitive deterministic signals mixed with uncorrelated noise.

Analysis of high-resolution ECG changes during percutaneous transluminal coronary angioplasty

The authors have hypothesized that low-level, electrocardiographic changes may accompany transient ischemia induced by percutaneous transluminal coronary angioplasty. Altered repolarization may manifest as subclinical changes in ST-T morphology. Changes in depolarization may manifest as low-amplitude notches and slurs, a phenomenon the authors term abnormal intra-QRS potentials. The initial aim of this study was to characterize changes in high-resolution electrocardiograph signals that might be linked to ischemic involvement of the ventricular myocardium.