A novel interpolation method for electric potential fields in the heart during excitation.
In mapping the electrical activity of the heart, interpolation of electric potentials plays two important roles. First, it permits the estimation of potentials in regions that could not be sampled or where signal quality was poor, and second, it supports the construction of isopotential lines and surfaces for visualization. The difficulty in developing robust interpolation techniques for cardiac applications lies in the abrupt change in potential in the vicinity of the activation wave front. Despite the resulting nonlinearities in spatial potential distributions, simple linear interpolation methods are the current standard and the resulting errors due to aliasing can be large if electrode spacing does not lie on the order of 0.5-2 mm--the thickness of the activation wave front. We have developed a novel interpolation method that is based on two observations specific to the spread of excitation in the heart: (1) that propagation velocity changes smoothly within a region large enough to contain several measurement electrodes and (2) that electrogram morphology varies very little in the neighborhood of each sample point except for a time shift in the potential wave forms. The resulting interpolation scheme breaks the interpolation of one highly nonlinear variable--extracellular potential--into two separate interpolations of variables with much less drastic spatial variation--activation time and electrogram morphology. We have applied this method to potentials originally recorded at 1.5 mm spacing and then subsampled at a range of densities for testing of the interpolation. The results based both on reconstruction of isopotential contour maps and statistical comparison showed significant improvement of this novel approach over standard linear techniques. The applications of the new method include improved determination of electrophysiological parameters such as spatial gradients of potential and the path of cardiac activation and recovery, estimation of electrograms at desired locations, and visualization of electric potential distributions.
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Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah, Salt Lake City 84112, USA.
MacLeod
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Taccardi
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D000465:Algorithms; D000818:Animals; D001698:Biomedical Engineering; D004285:Dogs; D004562:Electrocardiography / Q000295:instrumentation / Q000379:methods* / Q000706:statistics & numerical data; D004566:Electrodes; D004594:Electrophysiology; D006321:Heart / Q000502:physiology*; D006329:Heart Conduction System / Q000502:physiology; D008955:Models, Cardiovascular