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

2015; Elsevier BV; Volume: 65; Linguagem: Inglês

10.1016/j.compbiomed.2015.04.027

1879-0534

Chris D. Cantwell, Caroline H. Roney, Fu Siong Ng, Jennifer H. Siggers, Spencer J. Sherwin, Nicholas S. Peters,

EEG and Brain-Computer Interfaces

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.