Multielectrode Mapping of the Heart

  • Edward J. Berbari
  • Haris Sih

Multielectrode cardiac mapping has at least a 50-year history in cardiac research, and the development of this methodology has closely followed the technological advances in instrumentation and computing. The methodology has proven to be quite effective in characterizing potential distributions on both the body surface and the epicardial surface of the heart.1–4 However, the more challenging problem for multielectrode systems is the identification and display of cardiac activation or isochronal maps. In the earlier era of cardiac mapping, hardware limitations, particularly the speed of computer processing and digital data acquisition, were the major challenges for obtaining continuous data from a high number of recording channels. For the current generation of digital electronics and computers this is no longer a significant challenge. The analysis and interpretation of the data still pose a number of challenges, since in many cases, such as diseased myocardium or during complex tachyarrhythmias, the biophysical basis of conduction is not fully developed. For example, the use of contour-generation software often does not consider the actual nature of the underlying pathophysiology. Many standard interpolation algorithms will indeed create contours overlying scar tissue within infarcted regions. This is an inherent error.

A number of newer mapping approaches rely on mathematical models to create images based on data at some distance from the actual sources. In some cases these systems are proprietary and may have indeed conquered some long-standing problems. In other cases, because the systems produce “good looking” images that fit a preconceived model of activation, their underlying models are not challenged. This chapter focuses on the issues surrounding direct contact, multielectrode mapping approaches and will concentrate on the problems associated with producing activation maps, especially from regions surrounding and within infarct regions.


Extracellular Recording Epicardial Surface Microelectrode Recording Contour Generation Epicardial Mapping 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC. 2009

Authors and Affiliations

  • Edward J. Berbari
    • 1
  • Haris Sih
    • 2
  1. 1.Biomedical Engineering DepartmentIndiana University — Purdue University IndianapolisIndianapolisUSA
  2. 2.Cardiac Surgery DivisionBoston ScientificSt. PaulUSA

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