Comparison of the new acceleration spectrum analysis with other time- and frequency-domain analyses of the signal-averaged electrocardiogram

Efficient Detection of Ventricular Late Potentials on ECG Signals Based on Wavelet Denoising and SVM Classification

The analysis of cardiac signals is still regarded as attractive by both the academic community and industry because it helps physicians in detecting abnormalities and improving the diagnosis and therapy of diseases. Electrocardiographic signal processing for detecting irregularities related to the occurrence of low-amplitude waveforms inside the cardiac signal has a considerable workload as cardiac signals are heavily contaminated by noise and other artifacts. This paper presents an effective approach for the detection of ventricular late potential occurrences which are considered as markers of sudden cardiac death risk. Three stages characterize the implemented method which performs a beat-to-beat processing of high-resolution electrocardiograms (HR-ECG). Fifteen lead HR-ECG signals are filtered and denoised for the improvement of signal-to-noise ratio. Five features were then extracted and used as inputs of a classifier based on a machine learning approach. For the performance evaluation of the proposed method, a HR-ECG database consisting of real ventricular late potential (VLP)-negative and semi-simulated VLP-positive patterns was used. Experimental results show that the implemented system reaches satisfactory performance in terms of sensitivity, specificity accuracy, and positive predictivity; in fact, the respective values equal to 98.33%, 98.36%, 98.35%, and 98.52% were achieved.

Marginal Component Analysis of ECG Signals for Beat-to-Beat Detection of Ventricular Late Potentials

Heart condition diagnosis based on electrocardiogram signal analysis is the basic method used in prevention of cardiovascular diseases, which are recognized as the leading cause of death globally. To anticipate the occurrence of ventricular arrhythmia, the detection of Ventricular Late Potentials (VLPs) is clinically worthwhile. VLPs are low-amplitude and high-frequency signals appearing at the end part of QRS complexes in the electrocardiogram, which can be considered as a robust feature for arrhythmia risk stratification in patients with cardiac diseases. This paper proposes a beat-to-beat VLP detection method based on the the marginal component analysis and investigates its performance taking into account different ratios between QRS and VLP power. After a denoising phase, performed adopting the singular vector decomposition technique, heartbeats characterized by VLP onsets are identified and extracted taking into account the vector magnitude of each high resolution ECG (HR-ECG) record. To evaluate the proposed method performance, a 15-lead HR-ECG database consisting of real VLP-negative and simulated VLP-positive patterns was used. The achieved results highlight the method validity for VLP detection.

Use of Fast Fourier Transform Analysis of Atrial Electrograms for Rapid Characterization of Atrial Activation-Implications for Delineating Possible Mechanisms of Atrial Tachyarrhythmias

INTRODUCTION

Different analysis techniques have been developed to help understand and characterize the mechanisms responsible for atrial arrhythmias. We tested the hypothesis that Fast Fourier Transform (FFT) analysis of recorded atrial electrograms (AEGs) will rapidly and accurately identify regular and irregular patterns of atrial activation, and, thereby, may provide evidence suggestive of underlying mechanisms of atrial tachyarrhythmias.

METHODS AND RESULTS

During induced atrial tachyarrhythmias in both the canine sterile pericarditis model and canine rapid ventricular pacing-induced congestive heart failure model; 380-404 AEGs were recorded simultaneously from epicardial electrodes on both atria. From AEGs, atrial activation sequences were determined during atrial flutter (AFL), focal atrial tachycardia (AT), and atrial fibrillation (AF). Four-second recording segments of each AEG were subjected to FFT analysis. Frequencies found during FFT analyses in all studies precisely corresponded to the cycle lengths of the AEGs. In AFL and AT, one dominant frequency peak was found throughout both atria. In AF due to multiple unstable reentry circuits, multiple and broad frequency peaks were found in both atria. In AF due to a stable rapid rhythm (driver) in the left atrium with fibrillatory conduction to the rest of the atria, one dominant frequency peak in areas with 1:1 conduction from the driver, and multiple and/or broad frequency peaks in areas with fibrillatory conduction produced by the driver were found. Computation time for all FFT analyses took <5 minutes.

CONCLUSION

FFT analysis accurately and rapidly identifies global atrial activation patterns during AFL, AT, and AF, thereby assisting in determining arrhythmia mechanisms.

[Predictors of sudden death in coronary artery disease]

Although advances in the management of acute myocardial infarction have resulted in a decline in long-term risk of sudden death, it continues to be high in certain subsets of patients. Thus, it is important to identify and treat these patients. Left ventricular ejection fraction less than 0.40, frequent premature ventricular ectopy on Holter monitoring, late potentials on signal-averaged electrocardiogram, impaired heart rate variability, abnormal baroreflex sensitivity and inducible sustained monomorphic ventricular tachycardia during electrophysiological study are predictors of sudden death and arrhythmic events. Although the negative predictive value of each factor is high, the positive predictive accuracy is low. Several tests can be combined to obtain higher positive predictive values. In fact, in some studies combined noninvasive tests have been used to select patients for ventricular stimulation study. Some preventive treatment can be applied in these patients. Available data do not justify prophylactic therapy with amiodarone in high-risk survivors of acute myocardial infarction. Sudden death and total mortality have been significantly reduced in postinfarction patients by long-term beta blockade. Hence, beta blockers should be given to all patients with acute myocardial infarction who do not have contraindications to their use. The MADIT study has shown the beneficial effect of implantable cardioverter defibrillator in reducing mortality in patients with prior myocardial infarction, an ejection fraction less than 0.36, asymptomatic nonsustained ventricular tachycardia, and inducible sustained ventricular tachycardia, unsuppressable by procainamide. Besides, several studies are under way to evaluate the prophylactic use of implantable defibrillator for improving survival in high-risk patients.

Prevalence of ventricular late potentials in patients with obstructive sleep apnea syndrome

BACKGROUND

It is known from various cardiac disorders that the presence of ventricular late potentials (VLP) in the signal-averaged electrocardiogram (ECG) is associated with an increased risk of sudden cardiac death.

HYPOTHESIS

In view of the increased cardiovascular mortality of patients with obstructive sleep apnea syndrome (OSAS), we assessed the prevalence of VLP in these patients.

METHODS

In all, 118 consecutive patients with polysomnographically verified OSAS were prospectively studied; 21 snorers without evidence of a sleep-related breathing disorder served as a control group. Signal-averaged ECG and 24-h Holter ECG were performed in all patients and controls, and left ventricular function was determined by radionuclide ventriculography in the OSAS group. Furthermore, patients and controls were followed for up to 45.5 months for arrhythmic events, syncopes, or sudden cardiac death.

RESULTS

An abnormal signal-averaged ECG was seen in seven patients (5.9%) and in one snorer (4.8%). Patients with and without VLP did not differ with respect to age, body mass index, left ventricular ejection fraction, or ectopic activity in the 24-h Holter ECG, but the former had significantly higher mean (standard deviation) apnea/hypopnea indices [55.4 (25.2)/h vs. 37.4 (22.6)/h; p < 0.05]. Of the 118 patients, 110 could be followed for 26.7 (7.9) months. During this period, two patients had syncopes and one patient had sudden cardiac death. The seven patients with VLP remained free of events during the follow-up period, as did the 21 snorers.

CONCLUSIONS

Patients with OSAS have a low prevalence of VLP in the signal-averaged ECG, not exceeding that in normal subjects. Moreover, abnormal signal-averaged ECGs do not appear to be useful as a prognostic marker.