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 possib ility of combining two methods: Independent Component Analysis (ICA) and Adaptive Signal Enhancement for the improvement of normogastric rhythm extraction from multichannel recording of electrogastrographic sign als (EGG). Unfortunately the electrogastrogram, is a transcutaneous measurement of gastric electrical activity, does no t contain pure signal but usually is a sort of mixt ure from both electrical activity of stomach as well as other org ans surrounding it and random noise. In order to be nefit the diagnostic power of multichannel recording of EGG, which can provide deeper understanding of gastric disorders, i t is necessity to extract gastric slow wave in each channel. One of t he parameters, which are analyzed and require prope r registration is so called normogastric rhythm. According to the lit erature, the normogastric rhythm should cover aroun d 70% of rhythmic behavior of signal for a healthy man. Prop er extraction of basic 3-cpm normogastric rhythm in each channel is a subject of this paper. Independent Component Anal ysis is applied for extracting the reference signal for adaptive filtering what next result in obtaining less contam inated signal in each channel. Analysis has been pe rform for two postprandial phases with five minutes break between them. In both mention cases proposed procedure gives a promising results.