Gastric slow wave rhythm identification using new approach based on noise-assisted multivariate empirical mode decomposition and Hilbert-Huang transform.

Background: Electrogastrography (EGG) is the method of cutaneous recording of the myoelectrical activity of the stomach. A multi-channel signal is recorded non-invasively by means of electrodes placed outside the epigastric area. The normal electrical rhythm of the stomach (slow wave) may become significantly disturbed due to disorders of gastrointestinal tract. Abnormally fast electrical rhythms are termed tachygastria, while abnormally slow rhythms are known as bradygastria. Because some features of biological signals may go undetected using the classical methods of signal spectral analysis, we propose a new method for EGG rhythm identification.

Methods: In this study, the calculation of the basic rhythms of multi-channel EGG signals is performed by means of the noise-assisted multivariate empirical mode decomposition (NA-MEMD) and Hilbert-Huang transform (HHT), using EGG data from eight healthy subjects. The results were compared with those obtained using classical spectral analysis.

Key Results: The mean values of the normogastric index for preprandial and two postprandial stages were found to be 64.78 ± 11.37%, 61.29 ± 15.86%, and 63.80 ± 13.24%, respectively. The obtained values of normogastric index are consistent with the normal human physiological value, which is approximately 70% for healthy subjects.

Conclusions: This method is able to capture features of the signal which are mostly undetectable by standard EGG processing methods. The EGG dominant rhythm identification using the instantaneous normogastric, bradygastric, and tachygastric indices provides new insights into biological EGG patterns.