Abstract
This paper reports on the design and implementation of a 12 lead high resolution electrocardiograph. The proposed equipment incorporates advanced digital techniques enabling the estimation of intra-QRS potentials. The analysis software should perform in real-time the averaging of QRS complexes as well as digital filtering for extracting the intra-QRS potentials. Additionally, the time-series corresponding to the RR intervals should be estimated and processed in the frequency and time domain. One of the contributions of this research will consist on the development of a robust technique for the estimation of QT intervals operating simultaneously on each of the recorded leads. Analysis of QT time-series intervals could be performed using either Principal Component Analysis (PCA) or wavelets, aiming at deducing quantitative indexes of heart pathologies. The proposed system is intended as tool for the early detection of Chagas disease and their stratification. For attaining this goal a fusion stage would be incorporated. During this stage the software should provide a quantitative index based on several electrocardiographic (ECG) quantitative parameters estimated from the recorded leads.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
Referencias
World Health Organization. Division of Control of Tropical Diseases. (WHO/CTD). Chagas Disease Elimination, 2000. URL http://www.who.int/ctd/chagas.
Rassi A. Jr., Rassi A, Little W. (2000) Chagas’ Heart Disease, Clin. Cardiol. 23, 883–889.
Carrasco H. (1983) Diagnóstico del daño miocárdico en la enfermedad de Chagas. Consejo de Publicaciones, ULA, Mérida-Venezuela.
Añez N, Carrasco H, Parada H, Crisante G, Rojas A, Gonzáles N, Ramírez J, Guevara P, Rivero C, Borges R, Scorza J. (1999) Acute Chagas’ disease in western Venezuela: a clinical, seroparasitologic, and epidemiologic study. American Journal of Tropical Medicine and Hygiene 20:215–222.
Ribeiro A, Schmidt G, Sousa M, Lombardi F, Gomes M, Perez A, Barros M, Machado F, Rocha M. (2003) Heart rate turbulence in Chagas disease. Pacing Clin Electrophysiology 26:406–10.
Salles G, Cardoso C, Xavier S, Sousa A, Hasslocher M. (2003) Electrocardiographic ventricular repolarization parameters in chronic Chagas’ disease as predictors of asymptomatic left ventricular systolic dysfunction. Pacing Clin Electrophysiol 26:1326–35.
Maehara K, Kokubun T, Awano N, Taira K, Ono M, Furukawa T, Shimizu Y, Maruyama Y. (1999) Detection of abnormal highfrequency components in the QRS complex by the wavelet transform in patients with idiopathic dilated cardiomyopathy. Jpn Circ J 63:25–32.
Delgado R, Poulin G, Vrtovec B, Eastwood C, Radovancevic B, Franklin W, Kar B, Schlegel T. (2004) The utility of high frequency QRS electrocardiogram in the diagnosis of cardiomyopathy. J Am Coll Cardiol 43:208A.
Schlegel T, Kulecz W, DePalma J, Feiveson A, Wilson J, Rahman M, Bungo M. (2004) Real-time 12-lead high frequency QRS electrocardiography for enhanced detection of myocardial ischemia and coronary artery disease. Mayo Clin Proc 79:339–350.
Gomis P, Suarez K, Passariello G, Mendoza I, Caminal P, Lander P. (996) Abnormal intra-QRS signals and late potentials in the high resolution ECG associated with Chagasic myocarditis. Piscataway: IEEE Computer Society Press, 23: 633–6.
Medina R, Jugo D, Carrasco H. (1992) An acquisition and processing system for the high resolution surface electrocardiogram. 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp 779–780.
Ribeiro A, Lombardi F, Sousa M, Barros L, Porta A, Barros V, Gomes M, Machado S, Costa O. (2002) Power-law behavior of heart rate variability in Chagas’ disease. Am J Cardiol 89:414–8.
Aversano T, Rudikoff B, Washington A, Traill S, Coombs V, Raqueno J. (1994) High frequency QRS electrocardiography in the detection of reperfusion following thrombolytic therapy. Clin Cardiol 17:175–82.
Simson M. (1991) Use of signals in the terminal QRS complex to identify patients with ventricular tachycardia after myocardial infarction. Circulation, 64:235–242.
Lander P, Berbari E. (1991) Optimal filtering of the signal averaged ECG using time-frequency representations, 13th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vol. 13, No 2.
Abboud S, Belhassen B, Miller HI, Sadeh D, Laniado S. (1986) High frequency electrocardiography using an advanced method of signal averaging for non-invasive detection of coronary artery disease in patients with normal conventional electrocardiogram. Journal Electrocardiology 19:371–80.
Garcia I, Prado R, Gomis P. (2000) Wavelet Based Bayesian Models for Characterizing Chagasic High-Resolution ECG Signals, Computers in Cardiology.
Starc V, Schlegel T. (2006) Real-time multichannel system for beatto-beat QT interval variability. Journal of Electrocardiology, vol. 39, pp. 358–367.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Dugarte, N., Medina, R., Rojas, R. (2007). Adquisición y procesamiento de la señal Electrocardiográfica, basado en la extracción de potenciales intra-QRS e índices de variabilidad del intervalo QT. In: Müller-Karger, C., Wong, S., La Cruz, A. (eds) IV Latin American Congress on Biomedical Engineering 2007, Bioengineering Solutions for Latin America Health. IFMBE Proceedings, vol 18. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74471-9_46
Download citation
DOI: https://doi.org/10.1007/978-3-540-74471-9_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74470-2
Online ISBN: 978-3-540-74471-9
eBook Packages: EngineeringEngineering (R0)