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Technical aspects of the signal-averaged electrocardiogram

Sanjiv M Narayan, MD, PhD
Michael E Cain, MD
Section Editor
Ary L Goldberger, MD
Deputy Editor
Brian C Downey, MD, FACC


The signal-averaged electrocardiogram (SAECG) is a signal processing approach to detect subtle abnormalities in the surface electrocardiogram (ECG) that are not visible to the naked eye. The SAECG is derived by computing the arithmetic mean of multiple ECG complexes. This process emphasizes consistent signals between complexes while diminishing the more variable noise, thus increasing the signal-to-noise ratio of cardiac potentials to enable detection of small (ie, microvolt-level) signals than would otherwise be discernible on visual inspection of the surface ECG [1]. Signals from the His bundle as well as subtle abnormalities of atrial or ventricular complexes, anomalies not visualized on a surface ECG, are detectable using the SAECG [2,3].

The SAECG has most often been used to identify low-amplitude signals at the end of the QRS complex, referred to as "ventricular late potentials". These late potentials represent delayed ventricular activation, which may reflect the presence of myocardial scar tissue and identify patients at increased risk for reentrant ventricular tachyarrhythmias [4]. The SAECG is particularly useful in understanding the arrhythmic substrate and stratifying risk for ventricular tachyarrhythmias in patients with cardiomyopathies of various etiologies. (See "Reentry and the development of cardiac arrhythmias".)

However, the SAECG can also be useful in evaluating the risk for atrial arrhythmias. Studies suggest that a prolonged SAECG P-wave, equivalent to "atrial late potentials", may identify patients at risk for atrial fibrillation [5,6]. Finally, the SAECG can also improve the resolution of atrial from ventricular activation for improved ECG diagnosis of supraventricular tachyarrhythmias.

The technical aspects of the SAECG and the characteristics of late potentials will be reviewed here. The clinical use of the SAECG is discussed separately. (See "Use of the signal-averaged electrocardiogram in arrhythmia evaluation and management" and "Use of the signal-averaged electrocardiogram in ischemic heart disease" and "Use of the signal-averaged electrocardiogram in nonischemic heart disease and cardiac transplantation".)


The electrical signals of interest that reflect delayed conduction through ventricular or atrial scar are minute compared with the size of the QRS complex or P-wave seen on a surface ECG. Although simple amplification of the ECG may reveal these signals, it also amplifies ambient noise, which typically masks the useful low-amplitude signals. Conversely, averaging multiple QRS complexes (or P-waves) "reinforces" the consistent ventricular or atrial components while diminishing the inconsistent noise components, thus improving the signal-to-noise ratio. The ECG can be averaged over time ("temporal averaging") or spatially, and this process has been further enhanced by digital filtering and spectral analysis.


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Literature review current through: Sep 2016. | This topic last updated: Jun 22, 2016.
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  1. Berbari EJ, Scherlag BJ, Hope RR, Lazzara R. Recording from the body surface of arrhythmogenic ventricular activity during the S-T segment. Am J Cardiol 1978; 41:697.
  2. Berbari EJ, Lazzara R, Samet P, Scherlag BJ. Noninvasive technique for detection of electrical activity during the P-R segment. Circulation 1973; 48:1005.
  3. Cain ME, Anderson JL, Arnsdorf MF, et, al. Signal-averaged electrocardiography. ACC Expert Consensus Document. J Am Coll Cardiol 1996; 27:238.
  4. Hood MA, Pogwizd SM, Peirick J, Cain ME. Contribution of myocardium responsible for ventricular tachycardia to abnormalities detected by analysis of signal-averaged ECGs. Circulation 1992; 86:1888.
  5. Ehlert FA, Steinberg JS. The P wave signal-averaged ECG. J Electrocardiol 1995; 28 Suppl:33.
  6. Abe Y, Fukunami M, Yamada T, et al. Prediction of transition to chronic atrial fibrillation in patients with paroxysmal atrial fibrillation by signal-averaged electrocardiography: a prospective study. Circulation 1997; 96:2612.
  7. Simson MB, Untereker WJ, Spielman SR, et al. Relation between late potentials on the body surface and directly recorded fragmented electrograms in patients with ventricular tachycardia. Am J Cardiol 1983; 51:105.
  8. Narayan SM, Smith JM. Spectral analysis of periodic fluctuations in electrocardiographic repolarization. IEEE Trans Biomed Eng 1999; 46:203.
  9. Steinberg JS, Bigger JT Jr. Importance of the endpoint of noise reduction in analysis of the signal-averaged electrocardiogram. Am J Cardiol 1989; 63:556.
  10. El-Sherif N, Mehra R, Gomes JA, Kelen G. Appraisal of a Low Noise Electrocardiogram. J Am Coll Cardiol 1983; 1:456.
  11. He B, Cohen RJ. Body surface Laplacian electrocardiographic mapping--a review. Crit Rev Biomed Eng 1995; 23:475.
  12. Kavesh NG, Cain ME, Ambos HD, Arthur RM. Enhanced detection of distinguishing features in signal-averaged electrocardiograms from patients with ventricular tachycardia by combined spatial and spectral analyses of entire cardiac cycle. Circulation 1994; 90:254.
  13. SippensGroenewegen A, Lesh MD, Roithinger FX, et al. Body surface mapping of counterclockwise and clockwise typical atrial flutter: a comparative analysis with endocardial activation sequence mapping. J Am Coll Cardiol 2000; 35:1276.
  14. Cain ME, Ambos HD, Witkowski FX, Sobel BE. Fast-Fourier transform analysis of signal-averaged electrocardiograms for identification of patients prone to sustained ventricular tachycardia. Circulation 1984; 69:711.
  15. Machac J, Weiss A, Winters SL, et al. A comparative study of frequency domain and time domain analysis of signal-averaged electrocardiograms in patients with ventricular tachycardia. J Am Coll Cardiol 1988; 11:284.
  16. Haberl R, Jilge G, Pulter R, Steinbeck G. Spectral mapping of the electrocardiogram with Fourier transform for identification of patients with sustained ventricular tachycardia and coronary artery disease. Eur Heart J 1989; 10:316.
  17. Vázquez R, Caref EB, Torres F, et al. Improved diagnostic value of combined time and frequency domain analysis of the signal-averaged electrocardiogram after myocardial infarction. J Am Coll Cardiol 1999; 33:385.
  18. Wolzt M, Schmetterer L, Kastner J, et al. Short-term drug effects on the signal-averaged electrocardiogram in healthy men: assessment of intra- and interindividual variability of spectral temporal mapping and time-domain analysis. J Pharmacol Exp Ther 1995; 275:1375.
  19. Simson MB. Use of signals in the terminal QRS complex to identify patients with ventricular tachycardia after myocardial infarction. Circulation 1981; 64:235.
  20. Breithardt G, Cain ME, el-Sherif N, et al. Standards for analysis of ventricular late potentials using high-resolution or signal-averaged electrocardiography: a statement by a task force committee of the European Society of Cardiology, the American Heart Association, and the American College of Cardiology. J Am Coll Cardiol 1991; 17:999.