Robust ECG R-R wave peak detection using Evolutionary-Programming-based Fuzzy Inference System (EPFIS) and its application to assessing brain-gut interaction

Z. S. Wang, J. D.Z. Chen

Research output: Contribution to journalConference article

Abstract

Some recent studies have shown that gastric electrical stimulation can entrain gastric dysrhythmia, reduce chronic symptoms and accelerate gastric emptying. However, possible mechanisms involved remain unknown. The aim of this study is to investigate whether electrical stimulation is vagally mediated by assessing the heart rate variability (HRV). The study is performed in six healthy female hound dogs implanted with four pairs of bipolar serosal electrodes, which are used to measure gastric myoelectrical activity. A special fuzzy neural network, which is called Evolutionary-Programming-based Fuzzy Inference System (EPFIS), is developed to identify the R-R wave to precisely extract the R-R interval and derive the HRV data. A high-resolution adaptive time-frequency analysis method based on ARMA modeling developed previously in our laboratory is used to obtain high-quality HRV spectral parameters.

Original languageEnglish (US)
Pages (from-to)265-274
Number of pages10
JournalIEE Conference Publication
Issue number476
DOIs
StatePublished - 2000
EventInterantional Conference on Advances in Medical Signal and Information Processing (MEDSIP 2000) - Bristol, UK
Duration: Sep 4 2000Sep 6 2000

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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