Automatic Detection of Myocardial Infarction Based on High-Frequency QRS Analysis
Main Article Content
Abstract
In this paper, we present an algorithm for automatic detection of myocardial infarction using high-frequency components of the ECG signal. Firstly, the QRS complexes and their boundaries are identified. Then, the correlation matrix between the detected QRS complexes in each lead is determined to eliminate noises and ectopic oscillations. The dominant QRS complexes are finally determined using cluster analysis. These resulting values are averaged to have a unique representative QRS complex in a given lead. This averaged signal is then passed through a band-pass filter to obtain high-frequency components of the QRS complex. Finally, the High-Frequency Morphological Index (HFMI) for each lead is calculated and diagnosed with myocardial infarction based on decision rules. The performance of the proposed algorithm is evaluated on signals from the PTB database. The obtained results show that the proposed method reached satisfactory performance compared with the results from clinical studies.
Keywords: Myocardial infarction, High-frequency ECG, RAZ, RMS, HFMI.
Keywords: Myocardial infarction, High-frequency ECG, RAZ, RMS, HFMI.
References
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[3] T.T. Schlegel, W.B. Kulecz, J.L. DePalma, A.H. Feiveson, J.S. Wilson, M.A. Rahman, M.W. Bungo, Real-Time 12-Lead High-Frequency QRS Electrocardiography for Enhanced Detection of Myocardial Ischemia and Coronary Artery Disease, Mayo Clinic Proceedings 79 (2004) 339-350. https://doi.org/10.4065/79.3.339.
[4] B.H. Langner, Further Studies in High Fidelity Electrocardiography: Myocardial Infarction, Circulation VIII (1953) 905-913. https://doi.org/ 10.1161/01.CIR.8.6.905.
[5] M. Ringborn, J. Pettersson, E. Persson, S.G. Warren, P. Platonov, O. Pahlm, G.S. Wagner, Comparison of high-frequency QRS components and ST-segment elevation to detect and quantify acute myocardial ischemia, Journal of Electrocardiology 43 (2010) 113-120. https://doi. org/10.1016/j.jelectrocard.2009.11.009.
[6] D. Rosenmann, Y. Mogilevski, G. Amit, L.R. Davrath, D. Tzivoni, High-frequency QRS analysis improves the specificity of exercise ECG testing in women referred for angiography, Journal of Electrocardiology 46 (2013) 19-26. https://doi. org/10.1016/j.jelectrocard.2012.08.007.
[7] S. Abboud, Subtle alterations in the high-frequency QRS potentials during myocardial ischemia in dogs, Computers and Biomedical Research 20 (1987) 384-395. https://doi.org/10. 1016/j.jelectrocard.2012.08.007.
[8] A.L. Goldberger, V. Bhargava, V. Froelicher, J. Covell, Effect of myocardial infarction on high-frequency QRS potentials, Journal Electrocardiology 13 (1980) 367-372. https://doi. org/10.1161/01.CIR.64.1.34.
[9] J. Pettersson, O. Pahlm, E. Carro, L. Edenbrandt, M. Ringborn, L. Sörnmo, S.G. Warren, G.S. Wagner, Changes in high-frequency QRS components are more sensitive than ST-segment deviation for detecting acute coronary artery occlusion, Journal of the American College of Cardiology 36 (2000) 1827-1834. https://doi.org/ 10.1016/S0735-1097(00)00936-0.
[10] E. Toledo, J.A. Lipton, S.G. Warren, S. Abboud, M. Broce, D.R. Lilly, C. Maynard, B.D. Lucas Jr., G.S. Wagner, Detection of stress-induced myocardial ischemia from the depolarization phase of the cardiac cycle-a preliminary study, Journal of Electrocardiology 42 (2009) 240-247. https://doi.org/10.1016/j.jelectrocard.2008.12.023.
[11] G. Amit, O. Galante, L.R. Davrath, O. Luria, S. Abboud, D. Zahger, High-frequency QRS analysis in patients with acute myocardial infarction: A preliminary study, Annals of Noninvasive Electrocardiology 18 (2013) 149-156. https://doi. org/10.1111/anec.12023.
[12] E. Trägårdh, O. Pahlm, G.S. Wagner, J. Pettersson, Reduced high-frequency QRS components in patients with ischemic heart disease compared to normal subjects, Journal of Electrocardiology 37 (2004) 157-162. https://doi.org/10.1016/j.jelectro card.2004.02.004.
[13] A. Conti, A. Alesi, G. Aspesi, N.D. Bernardis, S. Bianchi, A. Coppa, C. Donnini, C. Grifoni, A. Becucci, C. Casula, High-frequency QRS analysis compared to conventional ST-segment analysis in patients with chest pain and normal ECG referred for exercise tolerance test, Cardiology Journal 22 (2015) 141-149. https://doi.org/10.1016/j.ajem.2015. 11.044.
[14] O. Galante, G. Amit, Y. Granot, L.R. Davrath, S. Abboud, D. Zahger, High-frequency QRS analysis in the evaluation of chest pain in the emergency department, Journal of Electrocardiology 50 (2017) 457-465. https://doi.org/10.1016/j.jelectrocard. 2017. 02.009.
[15] D. Rosenmann, Y. Mogilevski, G. Amit, L.R. Davrath, D. Tzivoni, High-frequency QRS analysis improves the specificity of exercise ECG testing in women referred for angiography, Journal of Electrocardiology 46 (2013) 19-26. https://doi. org/10.1016/j.jelectrocard.2012.08.007.
[16] G. Amit, Y. Granot, S. Abboud, Quantifying QRS changes during myocardial ischemia: Insights from high frequency electrocardiography, Journal of Electrocardiology 47 (2014) 505-511. https:// doi.org/10.1016/j.jelectrocard.2014.03.006.
[17] T. Sharir, K. Merzon, I. Kruchin, A, Bojko, E. Toledo, A. Asman, P. Chouraqui, Use of electrocardiographic depolarization abnormalities for detection of stress-induced ischemia as defined by myocardial perfusion imaging, American Journal of Cardiology 109 (2012) 642-650. https:// doi.org/10.1016/j.amjcard.2011.10.022.
[18] https://www.medcalc.org/calc/diagnostic_test.ph, (accessed 13 October 2019).
[19] https://physionet.org/content/ptbdb/1.0.0/ (accessed 10 September 2019).