コンピュータサイエンスとシステム生物学のジャーナル

Automatic Seizure Onset Detection in Long Term Pediatric EEG Signals

Abstract

Saeed MT, Zuhaib M, Khan YU and Azeem MF

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.