Identification of the spectral features in ECGs that distinguish patients prone to ventricular tachycardia (VT) is a prerequisite to increasing the diagnostic power of the signal-averaged ECG (SAECG). To determine distinguishing features of the magnitude spectrum, we analyzed the spectra of SAECGs of sinus beats over the entire cardiac cycle from 32 patients with VT, 30 without VT, and 10 normal controls. The magnitude spectra of the Frank SAECGs separated patients with VT from those without VT over the band from 7 to 140 Hz with a p value of 0.000000047. To determine distinguishing features of phase and group-delay spectra, we analyzed SAECGs of sinus beats over the entire cardiac cycle from 57 patients with VT, 65 without VT, and 20 normal controls. Unwrapped phase spectra from SAECGs of the entire cardiac cycle were calculated with respect to the onset of the Q wave. Phase spectra of SAECGs from patients with VT differed from those from non-VT patients at frequencies ³ 60 Hz (p = 0.00085). Average group delays in SAECGs from patients with and without VT differed (p = 0.00000069) from 14 to 24 Hz. Group delays in the VT patients in the 14-24 Hz band were on average 9 msec and 5 msec longer than those of the non-VTs and normals, respectively. Time-domain reconstructions demonstrated that distinguishing frequency bands were detectable throughout the QRS complex, ST segment, and T wave in SAECGs from each group. Thus the spectra of SAECGs over the cardiac cycle contain features that together with temporal features from throughout the cardiac cycle are essential in improving methods for stratifying risk of VT.

Keywords: Cardiac cycle, Fourier transform, signal-averaged ECG, spectral analysis, ventricular tachycardia