Modeling the relationship between concurrent epicardial action potentials and bipolar electrograms

Xu Sheng Zhang, Yi Sheng Zhu, Nitish V. Thakor, Zi Ming Wang, Zhi Zhong Wang

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)365-376
Number of pages12
JournalIEEE Transactions on Biomedical Engineering
Issue number4
StatePublished - 1999


  • Arrhythmia detection
  • Bipolar electrograms
  • Epicardial action potentials (AP's)
  • Nonlinear modeling
  • System identification
  • Wavelet networks

ASJC Scopus subject areas

  • Biomedical Engineering

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