Use of fuzzy similarity index for epileptic seizure prediction

G. Ouyang, Xiaoli Li, X.P. Guan
Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788)  
A fuzzy similarity index is proposed to indicate the preictal state with EEG signal. First, during the process of calculating the correlation integral, a Heavyside function is replaced by a Gaussian function, which eliminates the effect of the crisp boundary of the Heavyside since the Gaussian function's boundary is not sharp. Second, using a real EEG to compare the fuzzy similarity index and dynamical similarity index, it is found that the fuzzy similarity index is insensitive to the selection
more » ... ve to the selection of the radius value and the EEG signal length. Finally, the fuzzy similarity index is applied to indicate the preictal state of a rat with EEG signal. The result shows that the performance of fuzzy similarity index of predicting epileptic seizure is better than that of dynamical similarity index.
doi:10.1109/wcica.2004.1343748 fatcat:mgryjccj6vbdxpckpu3dwqruce