An improved method for the estimation and visualization of velocity fields from gastric high-resolution electrical mapping

IEEE Trans Biomed Eng. 2012 Mar;59(3):882-9. doi: 10.1109/TBME.2011.2181845. Epub 2011 Dec 26.

Abstract

High-resolution (HR) electrical mapping is an important clinical research tool for understanding normal and abnormal gastric electrophysiology. Analyzing velocities of gastric electrical activity in a reliable and accurate manner can provide additional valuable information for quantitatively and qualitatively comparing features across and within subjects, particularly during gastric dysrhythmias. In this study, we compared three methods of estimating velocities from HR recordings to determine which method was the most reliable for use with gastric HR electrical mapping. The three methods were 1) simple finite difference (FD) 2) smoothed finite difference (FDSM), and 3) a polynomial-based method. With synthetic data, the accuracy of the simple FD method resulted in velocity errors almost twice that of the FDSM and the polynomial-based method, in the presence of activation time error up to 0.5 s. With three synthetic cases under various noise types and levels, the FDSM resulted in average speed error of 3.2% and an average angle error of 2.0° and the polynomial-based method had an average speed error of 3.3% and an average angle error of 1.7°. With experimental gastric slow wave recordings performed in pigs, the three methods estimated similar velocities (6.3-7.3 mm/s), but the FDSM method had a lower standard deviation in its velocity estimate than the simple FD and the polynomial-based method, leading it to be the method of choice for velocity estimation in gastric slow wave propagation. An improved method for visualizing velocity fields is also presented.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Animals
  • Electrophysiological Phenomena*
  • Muscle Contraction / physiology
  • Muscle, Smooth / physiology
  • Reproducibility of Results
  • Signal Processing, Computer-Assisted
  • Stomach / physiology*
  • Swine