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

Abstract

Aim To compare four analysis techniques of the signalaveraged-electrocardiogram, including time-domain, spectral temporal mapping, spectral turbulence analysis and the new acceleration spectrum analysis. Methods and ResultsWe studied 634 subjects (77 with bundle branch block) divided into three groups. Group 1 comprised 117 post-myocardial infarction patients tested for inducibility of sustained ventricular tachycardia, and which was induced in 54 of them. Group 2 comprised 407 consecutive acute myocardial infarction survivors, followed for 1 year; 29 of them had suffered major arrhythmic events: 15 were cases of sustained ventricular tachycardia, three resuscitated ventricular fibrillation and 11 sudden cardiac death. Group 3 comprised 110 control subjects. The different analysis techniques were compared by their likelihood ratio for the prediction of ventricular tachycardia inducibility (Group 1) or major arrhythmic events (Group 2). The likelihood ratios of spectral-turbulence-analysis, acceleration spectrum analysis, spectral temporal mapping and time-domain were 8·0, 3·3, 1·7, 1·3 in Group 1, and 3·8, 2·1, 1·5, 2·6, in Group 2, while the corresponding falsepositive rates in Group 3 (control) were 0·9%, 10·0%, 4·5%, and 3·6%, respectively. ConclusionSpectral turbulence analysis was the most accurate technique for the prediction of either ventricular tachycardia inducibility or major arrhythmic events after myocardial infarction. It also showed the highest specificity among control subjects.

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

“…Many different analysis techniques 1–9 have been developed to help understand and characterize the mechanisms responsible for atrial arrhythmias, including atrial fibrillation (AF), atrial flutter (AFL), and focal atrial tachycardia (AT). Techniques such as sequential site mapping, simultaneous multisite mapping, optical mapping, and body surface potential mapping have also been used to help identify and characterize these atrial arrhythmias.…”

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

“…Unlike time analysis, a standard for the frequency domain approach has not yet been defined. Several studies have considered Fourier transformation [31] and the short-time Fourier transform, other methods have used maximum entropy spectrum estimation [32,33], time-variant autoregressive spectral study [34], spectral turbulence analysis [35,36] and Wigner distribution [37]. Some evident limits of the aforementioned methods concern the fixed duration of the window adopted for selection of QRS complex segments, the generation of interference terms, and poor choice of a fixed time-frequency resolution for the analysis of nonstationary signals such as VLPs.…”

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

“…Unlike time analysis, a standard for a frequency domain approach has not yet been defined. Several studies have considered the Fourier transformation [12] and the Short Time Fourier transform, while other methods have used the maximum entropy spectrum estimation [13,14], the time variant auto-regressive spectral study [15], the spectral turbulence analysis [6,16] and the Wigner distribution [17]. Some evident limits of the aforementioned methods concern the fixed duration of the window adopted for the selection of QRS complex segments, the generation of interference terms and the fixed time-frequency resolution that is a poor choice for the analysis of non-stationary signals such as VLPs.…”