Complexity Analysis on Normal and Abnormal Electrogastrograms using Tsallis Entropy

Electrogastrograms (EGG) are electrical signals generated by the muscles of the stomach and the features of these signals can be used to diagnose several digestive disorders. Entropy is a measure of the disorder associated with a system and hence is a measure of complexity of the system. In medical diagnostics, entropy has proved to be an efficient feature for discriminating the normal and abnormal states of biological systems. In this work the EGG signals have been obtained from normal and abnormal subjects having different digestive abnormalities (diarrhea, vomiting and stomach ulcer), from a local hospital. Further, the Tsallis entropy associated with the collected signals has been analyzed. Results demonstrate that the Mean Tsallis Entropy (MTE) (with α=0.5) of the EGG signals obtained from normal individuals (MTE=313.861) is high when compared to the individuals having diarrhea (MTE=278.0259), vomiting (MTE=105.1278) and stomach ulcer (MTE=-839.201). Since, entropy is the complexity associated with the signal, it is found that the complexity of the normal EGG signals is high when compared to the abnormal EGG signals. This work appears to be of high clinical relevance, since feature extraction from EGG signals is highly useful for diagnosis of digestive abnormalities.