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. It is investigated whether or not 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 the 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 modelling previously developed by the author is used to obtain high quality HRV spectral parameters.
|Original language||English (US)|
|Number of pages||6|
|Journal||IEE Proceedings: Science, Measurement and Technology|
|State||Published - Nov 2000|
ASJC Scopus subject areas
- Electrical and Electronic Engineering