Analysis of Noise Level Effects on Signal-Averaged Electrocardiograms

Authors: Chun-Cheng Lin

Abstract:

Noise level has critical effects on the diagnostic performance of signal-averaged electrocardiogram (SAECG), because the true starting and end points of QRS complex would be masked by the residual noise and sensitive to the noise level. Several studies and commercial machines have used a fixed number of heart beats (typically between 200 to 600 beats) or set a predefined noise level (typically between 0.3 to 1.0 μV) in each X, Y and Z lead to perform SAECG analysis. However different criteria or methods used to perform SAECG would cause the discrepancies of the noise levels among study subjects. According to the recommendations of 1991 ESC, AHA and ACC Task Force Consensus Document for the use of SAECG, the determinations of onset and offset are related closely to the mean and standard deviation of noise sample. Hence this study would try to perform SAECG using consistent root-mean-square (RMS) noise levels among study subjects and analyze the noise level effects on SAECG. This study would also evaluate the differences between normal subjects and chronic renal failure (CRF) patients in the time-domain SAECG parameters. The study subjects were composed of 50 normal Taiwanese and 20 CRF patients. During the signal-averaged processing, different RMS noise levels were adjusted to evaluate their effects on three time domain parameters (1) filtered total QRS duration (fQRSD), (2) RMS voltage of the last QRS 40 ms (RMS40), and (3) duration of the low amplitude signals below 40 μV (LAS40). The study results demonstrated that the reduction of RMS noise level can increase fQRSD and LAS40 and decrease the RMS40, and can further increase the differences of fQRSD and RMS40 between normal subjects and CRF patients. The SAECG may also become abnormal due to the reduction of RMS noise level. In conclusion, it is essential to establish diagnostic criteria of SAECG using consistent RMS noise levels for the reduction of the noise level effects.

Keywords: Signal-averaged electrocardiogram, Ventricular latepotentials, Chronic renal failure, Noise level effects.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1070067

References:

[1] M. B. Simson, "Use of signals in the terminal QRS complex to identify patients with ventricular tachycardia after myocardial infarction", Circulation, vol. 64, pp. 235-242, 1981.
[2] M. E. Cain, H. D. Ambos, F. X. Witkowski, B.E. Sobel, "Fast-Fourier transform danalysis of signal-averaged electrocardiogram for identification of patients prone to sustained ventricular tachycardia", Circulation, vol. 69, pp. 711-720, 1984.
[3] J. R. Jarrett, N. C. Flowers, "Signal-averaged electrocardiography: history, techniques, and clinical applications", Clin. Cardiol., vol. 14, pp. 984-994, 1991.
[4] C. C. Lin, C. M. Chen, I. F. Yang, T. F. Yang, "Automatic optimal order selection of parametric modeling for the evaluation of abnormal intra-QRS signals in signal-averaged electrocardiograms", Med. Biol. Eng. Comput., vol. 43, pp. 218-224, 2005.
[5] C. C. Lin, "Enhancement of accuracy and reproducibility of parametric modeling for estimating abnormal intra-QRS potentials in signal-averaged electrocardiograms", Med. Eng. Phys., vol. 30, pp. 834-842, 2008.
[6] C. C. Lin, "Analysis of Unpredictable Intra-QRS Potentials in Signal-Averaged Electrocardiograms Using an Autoregressive Moving Average Prediction Model", Med. Eng. Phys., vol. 32, pp. 136-144, 2010.
[7] O. Rompelman, H. H. Ros, "Coherent averaging technique: a tutorial review. Part 1: Noise reduction and the equivalent filter", J. Biomed. Eng., vol. 8, pp. 24-29, 1986.
[8] O. Rompelman, H. H. Ros, "Coherent averaging technique: a tutorial review. Part 2: trigger jitter, overlapping responses and non-periodic stimulation", J. Biomed. Eng., vol. 8, pp. 30-35, 1986.
[9] G. Breithardt, M. E. Cain, N. El-Sherif, N. C. Flowers, V. Hombach, M. Janse, M. B. Simson, G. Steinbeck, "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., vol. 17, pp. 999-1006, 1991.
[10] M. E. Cain, J. L. Anderson, M. F. Arnsdorf, J. W. Mason, M. M. Scheinman, A. L. Waldo, "Signal-Averaged Electrocardiography", J. Am. Coll. Cardiol., vol. 27, pp. 238-249, 1996.
[11] H. Tatsumi, M. Takagi, E. Nakagawa, H. Yamashita, M. Yoshiyama, "Risk stratification in patients with Brugada syndrome: analysis of daily fluctuations in 12-lead electrocardiogram (ECG) and signal-averaged electrocardiogram (SAECG)", J. Cardiovasc. Electrophysiol., vol. 17(7), pp. 705-711, 2006.
[12] A. L. Ribeiro, P. S. Cavalvanti, F. Lombardi, C. Mdo Nunes, M. V. Barros, M. O. Rocha, "Prognostic value of signal-averaged electrocardiogram in Chagas disease", J. Cardiovasc. Electrophysiol., vol. 19(5), pp. 502-509, 2008.
[13] H. Isma'eel, W. Shamseddeen, A. Taher, W. Gharzuddine, A. Dimassi, S. Alam, L. Masri, M. Khoury, "Ventricular late potentials among thalassemia patients", Int. J. Cardiol., vol. 132(3), pp. 453-455, 2009.
[14] H. Ichikawa, Y. Nagake, H. Makino, "Signal averaged electrocardiography (SAECG) in patients on hemodialysis", J. Med., vol. 28, pp. 229-243, 1997.
[15] M. A. Morales, C. Gremigni, P. Dattolo, et al., "Signal-averaged ECG abnormalities in haemodialysis patients. Role of dialysis", Nephrol. Dial. Transplant, vol. 13, pp. 668-673, 1988.
[16] I. Girgis, G. Contreras, S. Chakko, et al., "Effect of hemodialysis on the signal-averaged electrocardiogram", Am. J. Kidney Dis., vol. 34, pp. 1105-1113, 1999.
[17] A. Yildiz, V. Akkaya, S. Sahin, T. Tukek, M. Besler, S. Bozfakioglu, "QT dispersion and signal-averaged electrocardiogram in hemodialysis and CAPD patients", Perit. Dial. Int., vol. 21, pp. 186-192, 2001.
[18] R. N. Foley, P. S. Pafrey, M. J. Sarnak, "Epidemiology of cardiovascular disease in chronic renal disease", J. Am. Soc. Nephrol., vol. 9, pp. S16-S23, 1998.
[19] J. S. Steinberg, J. T. Jr Bigger, "Importance of the endpoint of noise reduction in analysis of the signal-averaged electrocardiogram", Am. J. Cardiol., vol. 63, pp. 556-560, 1989.
[20] E. H. Christiansen, L. Frost, H. Molgaard, T. T. Nielsen, A. K. Pedersen, "Noise in the signal-averaged electrocardiogram and accuracy for identification of patients with sustained monomorphic ventricular tachycardia after myocardial infarction", Eur. Heart J., vol. 17, pp. 911-916, 1996.
[21] E.H. Christiansen, L. Frost, H. Molgaard, T. T. Nielsen, A. K. Pedersen, "Effect of residual noise level on reproducibility of the signal-averaged ECG", J. Electrocardiol., vol. 29, pp. 235-241, 1996.
[22] T. N. Maounis, E. Kyrozi, I. Chiladakis, V. P. Vassilikos, A. S. Manolis, D. V. Cokkinos, "Comparison of signal-averaged electrocardiograms with different levels of noise: time-domain, frequency-domain, and spectrotemporal analysis", Pacing Clin. Electrophysiol., vol. 20, pp. 671-682, 1997.
[23] P. Lander, E. J. Berbari, C. V. Rajagopalan, P. Vatterott, R. Lazzara, "Critical analysis of the signal-averaged electrocardiogram, Improved identification of late potentials", Circulation, vol. 87, pp. 105-117, 1993.
[24] P. Lander, E. J. Berbari, R. Lazzara, "Optimal filtering and quality control of the signal-averaged ECG. High-fidelity 1-minute recordings", Circulation, vol. 91, pp. 1495-1505, 1995.
[25] J. J. Goldberger, S. Challapalli, M. Waligora, A. H. Kadish, D. A. Johnson, M. W. Ahmed, S. Inbar, "Uncertainty principle of signal-averaged electrocardiography", Circulation, vol. 101, pp. 2909-2915, 2000.