Imperial College London

ProfessorSpencerSherwin

Faculty of EngineeringDepartment of Aeronautics

Professor of Computational Fluid Mechanics
 
 
 
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Contact

 

+44 (0)20 7594 5052s.sherwin Website

 
 
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Location

 

313BCity and Guilds BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Cantwell:2015:10.1016/j.compbiomed.2015.04.027,
author = {Cantwell, CD and Roney, CH and Ng, FS and Siggers, JH and Sherwin, SJ and Peters, NS},
doi = {10.1016/j.compbiomed.2015.04.027},
journal = {Computers in Biology and Medicine},
pages = {229--242},
title = {Techniques for automated local activation time annotation and conduction velocity estimation in cardiac mapping},
url = {http://dx.doi.org/10.1016/j.compbiomed.2015.04.027},
volume = {65},
year = {2015}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - 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.
AU - Cantwell,CD
AU - Roney,CH
AU - Ng,FS
AU - Siggers,JH
AU - Sherwin,SJ
AU - Peters,NS
DO - 10.1016/j.compbiomed.2015.04.027
EP - 242
PY - 2015///
SN - 0010-4825
SP - 229
TI - Techniques for automated local activation time annotation and conduction velocity estimation in cardiac mapping
T2 - Computers in Biology and Medicine
UR - http://dx.doi.org/10.1016/j.compbiomed.2015.04.027
UR - http://hdl.handle.net/10044/1/24088
VL - 65
ER -