Spatial Filtering Methods for Local Activation Determination in Fractionated Electrograms from Simulated Infarcted Hearts

I. Chouvarda; N. Maglaveras; J. de Bakker; F. J. L. van Capelle; C. Pappas

doi:10.1055/s-0038-1634273

Methods of Information in Medicine, Table of Contents

Methods Inf Med 2000; 39(02): 164-167
DOI: 10.1055/s-0038-1634273

Original Article

Schattauer GmbH

Spatial Filtering Methods for Local Activation Determination in Fractionated Electrograms from Simulated Infarcted Hearts

I. Chouvarda

¹Aristotelian University, Lab of Medical Informatics, The Medical School, Thessaloniki, Macedonia, Greece

,

N. Maglaveras

¹Aristotelian University, Lab of Medical Informatics, The Medical School, Thessaloniki, Macedonia, Greece

,

J. de Bakker

²University of Amsterdam, Lab of Experimental Cardiology, Amsterdam, The Netherlands

,

F. J. L. van Capelle

²University of Amsterdam, Lab of Experimental Cardiology, Amsterdam, The Netherlands

,

C. Pappas

¹Aristotelian University, Lab of Medical Informatics, The Medical School, Thessaloniki, Macedonia, Greece

› Author Affiliations

Abstract

Abstract:

The purpose of this work is the enhancement of local activation in multiphasic extracellular recordings coming from infarcted myocardial tissue and, consequently, the distinction of local from distal activation. Deconvolution procedures are applied, in the form of spatial filtering, in order to estimate transmembrane currents from the extracellular recordings. Simulated data are used in order to test the methods. The current source estimates are compared to the actual transmembrane currents and to Laplacian estimates.

Keywords:

Local Activation - Electrogram - Deconvolution

Full Text

References

REFERENCES
1 Spach MS, Dolber P. Relating extracellular potentials and their derivatives to anisotropic propagation at a microscopic level in human cardiac tissue. Circulat Res 1986; 58: 356-71.
2 Anderson KP, Walker R, Ershler PR, Fuller M, Dustman T, Menlove R, Karwandee SV, Lux RL. Determination of Local Myocardial Electrical Activation for Activation Sequence Mapping: A statistical Approach. Circulat Res 1991; 69: 898-917.
3 Romberg D, Gezelowitz DB, Berbari EJ, Dyer JW, Persson P. Spatial Filtering of Epicardial Electrograms from Infarcted Regions: An in Vitro Study. Comput Cardiol. 1994: 153-6.
4 Gezelowitz DB. Use of Laplacian to extract Local Activation From Epicardial Electrograms. Comput Cardiol. 1996: 129-32.
5 Ellis WS, Eisenberg SJ, Auslander DM, Dae MW, Zakhor A, Lesh MD. Deconvolution: a novel signal processing approach for determining activation time from fractionated electrograms and detecting infracted tissue. Circulation 1995; 94: 2633-40.
6 Reiger MA, Dyer JW, Geselowitz DB, Berbari EJ. Interpolation of Local Activation Times Versus Potentials to Derive an Activation Map in Infarcted Myocardium. Comput Cardiol. 1996: 137-40.
7 Chipman H, Kolaczyk E, McCulloch R. Adaptive Bayesian Wavelet Shrinkage. J Am Statist Assoc. 1997; 1413-21.
8 Mallat S. A theory for Multiresolution Signal Decomposition: The Wavelet Representation. IEEE Trans on PAMI 1989; 7: 674-93.
9 Henriquez CS, Papazoglou A. Using Computer Models to Understand the Roles of Tissue and Membrane Dynamics in Arrhythmogenesis. Proc IEEE 1996; 84: 334-54.
10 Maglaveras N, Van Capelle FJL. Effects of Barriers on Propagation of Action Potentials in Two-dimensional Cardiac Tissue. J Electrocardiol 1995; 28: 17-31.
11 Maglaveras N, De Bakker JMT, Van Capelle FJL. Activation delay in healed myocardial infarction: a comparison between model and experiment. Am J Physiol 1995; 269: (Heart Circ Physiol 38): H1441-H1449.