4.7 Article

Techniques for automated local activation time annotation and conduction velocity estimation in cardiac mapping

Journal

COMPUTERS IN BIOLOGY AND MEDICINE
Volume 65, Issue -, Pages 229-242

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compbiomed.2015.04.027

Keywords

Conduction velocity; Cardiac electrophysiology; Local activation time; Cardiac mapping; Arrhythmias

Funding

  1. British Heart Foundation (BHF) [FS/11/22/28745, RG/10/11/28457]
  2. EPSRC [EP/K038788/1]
  3. Imperial BHF Centre of Research Excellence
  4. Academy of Medical Sciences Starter Grant [AMS-SGCL8-Ng]
  5. National Institute of Health Research Clinical Lectureship [LDN/007/255/A]
  6. NIHR Biomedical Research Centre
  7. ElectroCardioMaths programme, part of the Imperial BHF Centre of Research Excellence
  8. Academy of Medical Sciences (AMS) [AMS-SGCL8-Ng] Funding Source: researchfish
  9. British Heart Foundation [RG/10/11/28457, FS/11/22/28745, FS/11/69/29017] Funding Source: researchfish
  10. Engineering and Physical Sciences Research Council [EP/K038788/1] Funding Source: researchfish
  11. Medical Research Council [G0900396] Funding Source: researchfish
  12. National Institute for Health Research [CL-2011-21-001] Funding Source: researchfish
  13. EPSRC [EP/K038788/1] Funding Source: UKRI
  14. MRC [G0900396] Funding Source: UKRI

Ask authors/readers for more resources

Measurements of cardiac conduction velocity provide valuable functional and structural insight into the initiation and perpetuation of cardiac arrhythmias, in both a clinical and laboratory context. The interpretation of activation wavefronts and their propagation can identify mechanistic properties of a broad range of electrophysiological pathologies. However, the sparsity, distribution and uncertainty of recorded data make accurate conduction velocity calculation difficult. A wide range of mathematical approaches have been proposed for addressing this challenge, often targeted towards specific data modalities, species or recording environments. Many of these algorithms require identification of activation times from electrogram recordings which themselves may have complex morphology or low signal-to-noise ratio. This paper surveys algorithms designed for identifying local activation times and computing conduction direction and speed. Their suitability for use in different recording contexts and applications is assessed. (C) 2015 The Authors. Published by Elsevier Ltd.

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