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PubMed · 10217874

Modeling the relationship between concurrent epicardial action potentials and bipolar electrograms.

X S Zhang·Y S Zhu·N V Thakor·Z M Wang·Z Z Wang
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Abstract

A signal analysis approach to building the relationship between concurrent epicardial cell action potentials (AP's) and bipolar electrograms is presented. Wavelet network, one nonlinear black-box modeling method, is used to identify the relationship between cell AP's and bipolar electrocardiograms. The electrical signals were simultaneously measured from the epicardium of isolated Langendorff-perfused rabbit hearts during three different rhythm conditions: normal sinus rhythm (NSR), normal sinus rhythm after ischemia (NSRI), and ventricular fibrillation (VF). For NSR and NSRI, the proposed modeling method successfully captures the nonlinear input-output relationship and provides an accurate output, but the method fails in case of VF. This result suggests that a time-invariant nonlinear modeling method such as wavelet network is not appropriate for VF rhythm, which is thought to be time-varying as well as chaotic, but still useful in detection of VF. A new arrhythmia detection algorithm, with potential application in implantable devices, is proposed for identifying the time of rhythmic bifurcation.

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Action PotentialsAlgorithmsAnimalsElectrocardiographyIn Vitro TechniquesLinear ModelsModels, CardiovascularNeural Networks, ComputerNonlinear DynamicsPericardiumRabbitsReference ValuesSignal Processing, Computer-AssistedVentricular FibrillationComparative StudyJournal ArticleResearch Support, Non-U.S. Gov't

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X S Zhang, Y S Zhu, N V Thakor, Z M Wang, Z Z Wang. 1999. Modeling the relationship between concurrent epicardial action potentials and bipolar electrograms.. https://doi.org/10.1109/10.752933

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