@article{(Open Science Index):https://publications.waset.org/pdf/10003072, title = {Epileptic Seizure Prediction by Exploiting Signal Transitions Phenomena}, author = {Mohammad Zavid Parvez and Manoranjan Paul}, country = {}, institution = {}, abstract = {A seizure prediction method is proposed by extracting global features using phase correlation between adjacent epochs for detecting relative changes and local features using fluctuation/ deviation within an epoch for determining fine changes of different EEG signals. A classifier and a regularization technique are applied for the reduction of false alarms and improvement of the overall prediction accuracy. The experiments show that the proposed method outperforms the state-of-the-art methods and provides high prediction accuracy (i.e., 97.70%) with low false alarm using EEG signals in different brain locations from a benchmark data set.}, journal = {International Journal of Medical and Health Sciences}, volume = {9}, number = {12}, year = {2015}, pages = {844 - 848}, ee = {https://publications.waset.org/pdf/10003072}, url = {https://publications.waset.org/vol/108}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 108, 2015}, }