APPLICATION OF SOM IN CLASSIFICATION OF EGG SIGNALS
Journal Title: Metrology and Measurement Systems - Year 2006, Vol 13, Issue 3
Abstract
The report presents problems associated with computer aided gastric diagnosis. The subject of the study are electrogastrographic (EGG) signals (non-invasively measured electrical signals generated by the human stomach). The signals were digitally recorded and then parametrized, with linear autoregressive models (AR). The data and parametrization method used in the study were the same as used by the authors in the previous study; therefore here they are only shortly described. The sets of numbers, obtained by these means, were treated as information vectors, and classified with the Self Organizing Map (SOM) classifier. The structure and parameters of the algorithm used for classification of the parametrized EGG data are described. The final efficiency of the whole system (SOM classifier with the parametrization method applied), reaching 80%, is promising. It is similar to the results of other classifiers. The ways to improve the effectiveness are also outlined.
Authors and Affiliations
ZBIGNIEW ŚWIERCZYŃSKI
Keywords
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