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The First Experience with the Use of Noise-Assisted Empirical Mode Decomposition Algorithm in the Processing of Multi-channel Electrogastrography Signals

  • Dariusz KomorowskiEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 471)

Abstract

The electrogastrographic examination (EGG) is a non invasive method for the investigation of the myoelectrical stomach activities that is performed with the electrodes placed on the skin of the patient’s abdomen. The main aim of EGG examination is the assessment of gastric slow wave propagation. Observation and measurement of the wave parameters changes (e.g. amplitude and frequency) facilitates diagnosing certain abnormalities and disorders associated with the impaired gastric activity. Such abnormalities are usually difficult to detect with the traditional diagnostic methods. One of the main tasks of this study is to extract the gastric slow wave, occurring naturally in the EGG signals, from the raw multi-channel EGG signal. In the presented work, in order to extract slow waves from multi-channel EGG, a modified method of the Multivariate Empirical Mode Decomposition (MEMD) called the Noise-Assisted Empirical Mode Decomposition (NA-MEMD) is proposed to apply. The use of NA-MEMD algorithm and Hilbert-Huang spectrum (HHS) seems to be the appropriate method for analysing non-linear and non-stationary signals and so is the multi-channel EGG.

Keywords

Electrogastrography Noise assisted empirical mode decomposition Slow wave 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Faculty of Biomedical Engineering, Department of Biosensors and Biomedical Signals ProcessingSilesian University of TechnologyZabrzePoland

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