Objective of this study is to parallelize and apply distributed system paradigm to the whole process of EEG signal analysis including the signal segmentation, signal processing, feature extraction, and classification. This study is focused only on time required for execution of every signal processing part within real–time epileptic seizure prediction. CHB–MIT database, containing 22 pediatric patients, is used for this purpose. Based on the achieved results, parallelization has significantly decreased the execution time for more than 50 %.