Reyna-Carranza MA, Jané-Campos R

Language: Spanish
References: 9
Page: 98-110
PDF size: 181.41 Kb.

ABSTRACT

Introduction. Ventricular late potentials can be used for indicating abnormal ventricular conduction, because they are associated with the arrhythmogenic ventricular activity produced by damaged cardiac tissue after an infarct. Most researchers have designed procedures for detecting ventricular conduction abnormalities analyzing High Resolution ECG (HRECG) by means of the wavelet transform. However, few scientists have obtained satisfactory quantitative results. Material and Methods. We are proposing to analyze HRECG’s of post-infarcted patients by quantifying the singularities within the QRS complex. For their detection we use four wavelets, instead of one as the majority of the reported methods. We have tested the methods with a database of 132 HRECG recordings. 59 HRECG recordings were taken from postinfarcted patients, and the remaining 73 from healthy subjects. Results. When using more than one wavelet in the analysis, the number of false negatives (FN’s) was reduced from 5 to 1, wit hout considerably increasing the number of false positives (FP’s) from 9 to 11. Therefore, the predictive value of the method increased too. Discussion. The abnormal ventricular potentials are unstable structures that not only change in amplitude, shape and frequency, but also in temporal localization, due to the intrinsic characteristics of the arrhythmic substrates. A single wavelet function can not adjust to the unstable structures for each HRECG in the database. Therefore, we are suggesting the use of a group of 4 wavelet functions to solve the problem. If one of the four wavelet functions does not detect the conduction abnormality (in case the shape can not be adjusted to the abnormality pattern), it is still possible that one of the remaining wavelets can be adjusted and, therefore, that the irregularity will be detected.

REFERENCES

1. Breithardt G, Cain M, El-Sherif N, Flowers N, Hombach V, Janse M, et al. Standards for analysis of ventricular late potentials using high-resolution signalaveraged electrocardiography. A joint statement. Task Force committee of the European Society of Cardiology, the American Heart Association and the American College of Cardiology. J Am Coll Cardiol 1991; 17:999-1006.

2. Gomis PR. Análisis de AIQP en la predicción de eventos arrítmicos. Caracterización de potenciales anormales intra-QRS en el ECG de alta resolución: aplicación en la evaluación de cardiopatías [Tesis Doctoral]. Barcelona, Inst. de Cibernética, UPC.; 1996.

3. Simson MB. Use of signals in the terminal QRS complex to identify patients with ventricular tachycardia after myocardial infarction. Circulation 1981; 64:235-42.

4. Haberl R, Jilge G, Pulter R, Steinbigler P, Steinbeck G. Spectrotemporal mapping of the surface ECG for detection of ventricular late potentials. Signal Average Electrocardiography 1993; 125-36.

5. D Gabor. Theory of communication. Journal of Institution of Electrical Engineers (London) 1946; 93:429-57.

6. Daubechies. Ten Lectures on Wavelets, SIAM 1992.

7. Riol O, Vetterli M. Wavelets and Signal Processing. IEEE Signal Processing Magazine 1991; 8 (4): 14-38.

8. Rubel P, Courdec J Ph, Morlet D, Fayn J, Peyrin F, Touboul P. Spectral analisys of high-resolution ECGs. En: Moss A.J, and Stern S, editores. Noninvasive Electrocardiology. Clinical Aspects of Holter Monitoring. London: W. B. Saunders Company Ltd; 1996. p. 291-314.

9. Mehra R. Pathophysilogy of late potentials: Experimental observation of late potentials. En: Gomes JA editor. Signal Averaged Electrocardiography Concepts, Methods and Applications. Lancaster: Kluwer Academic Publishers; 1993. p. 11-14.