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Despite regular medication management, many patients continue to have seizures. Thus, there is a need of  more tailored therapy and consequently more sophisticated and accurate seizure diagnostic tools. Background EEG activity is used by physicians for finding information regarding dysfunction of associated central nervous system and  risk of seizures. Considering its importance, background activity is exploited in this work for computation of relative  entropy, Cauchy-Schwartz divergence, change in median absolute deviation, change in normalized coefficient of  variation and change in Katz fractal dimension. The results are highly promising and comparative study suggests  that considering background activity outperforms the other techniques.

Automatic Seizure Onset Detection in Long Term Pediatric EEG Signals