Independent component analysis and adaptive filtering as successful tools for an improvement of normogastric rhythm extraction in electrogastrographic signals

The aim of this study was to investigate the possibility of combining two methods: Independent Component Analysis (ICA) and Adaptive Signal Enhancement for the improvement of normogastric rhythm extraction from multichannel recording of electrogastrographic signals (EGG). Unfortunately the electrogastrogram, is a transcutaneous measurement of gastric electrical activity, does not contain pure signal but usually is a sort of mixture from both electrical activity of stomach as well as other organs surrounding it and random noise. In order to benefit the diagnostic power of multichannel recording of EGG, which can provide deeper understanding of gastric disorders, it is necessity to extract gastric slow wave in each channel. One of the parameters, which are analyzed and require proper registration is so called normogastric rhythm. According to the literature, the normogastric rhythm should cover around 70% of rhythmic behavior of signal for a healthy man. Proper extraction of basic 3-cpm normogastric rhythm in each channel is a subject of this paper. Independent Component Analysis is applied for extracting the reference signal for adaptive filtering what next result in obtaining less contaminated signal in each channel. Analysis has been perform for two postprandial phases with five minutes break between them. In both mention cases proposed procedure gives a promising results.