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Development of an Automated Decision Support System for Diagnosis of Digestive Disorders Using Electrogastrograms: An Approach Based on Empirical Mode Decomposition and K-Means Algorithm

Development of an Automated Decision Support System for Diagnosis of Digestive Disorders Using Electrogastrograms: An Approach Based on Empirical Mode Decomposition and K-Means Algorithm
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Author(s): Arivarasu Rajagopal (Madras Institute of Technology, India), Paramasivam Alagumariappan (Madras Institute of Technology, India)and Kamalanand Krishnamurthy (Madras Institute of Technology, India)
Copyright: 2020
Pages: 18
Source title: Disruptive Technology: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-9273-0.ch032

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Abstract

The disorders of the digestive tract lead to various problems such as bleeding, bloating, nausea, etc. In order to diagnose various digestive abnormalities, the electrogastrograms (EGG) can serve as an efficient tool. In an EGG, several electrodes are placed onto the abdomen over the stomach and the electrical signals originating from the stomach muscles are recorded. By analyzing these electrical patterns, the abnormalities in digestive system can be analyzed. This chapter describes the developed system for measuring EGG signals along with the decision support system developed for automated classification of digestive disorders. The normal and abnormal EGG signals were acquired at Balaji Medical Hospital, Chennai. Further, the features were extracted using descriptive statistics and empirical mode decomposition (EMD) algorithm. Finally, an automated classification system was developed using k-means algorithm. This chapter explains the recording of electrogastrograms and a method for classification of normal and abnormal EGG signals.

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