Epilepsy is a common neurological disorders characterized by sudden recurrent seizures. Electroencephalogram (EEG) is widely used to diagnose possible epileptic seizure. Many research works have been devoted to predict epileptic seizure by analyzing EEG signal. Seizure prediction by analyzing EEG signals are challenging task due to variations of brain signals of different patients. In this paper, we propose a new approach for feature extraction based on phase correlation in EEG signals. In phase correlation, we calculate relative change between two consecutive segments of an EEG signal and then combine the changes with neighboring signals to extract features. These features are then used to classify preictal/ictal and interictal EEG signals for seizure prediction. Experiment results show that the proposed method carries good prediction rate with greater consistence for the benchmark data set in different brain locations compared to the existing state-of-the-art methods.
|Number of pages||1|
|Publication status||Published - 2015|
|Event||17th International Conference on Bioinformatics and Biological Engineering (ICBBE 2015) - Park Inn Stockholm Hammarby Sjöstad, Stockholm, Sweden|
Duration: 13 Jul 2015 → 14 Jul 2015
https://waset.org/conference/2015/07/stockholm/ICBBE/home (Conference website)
|Conference||17th International Conference on Bioinformatics and Biological Engineering (ICBBE 2015)|
|Period||13/07/15 → 14/07/15|
|Other||The ICBBE 2015: 17th International Conference on Bioinformatics and Biological Engineering aims to bring together leading academic scientists, researchers and research scholars to exchange and share their experiences and research results about all aspects of Bioinformatics and Biological Engineering. It also provides the premier interdisciplinary forum for researchers, practitioners and educators to present and discuss the most recent innovations, trends, and concerns, practical challenges encountered and the solutions adopted in the field of Bioinformatics and Biological Engineering.|
Parvez, M., & Paul, M. (2015). Epileptic Seizure Prediction Focusing on Relative Change in Consecutive Segments of EEG Signal. 1-1. Abstract from 17th International Conference on Bioinformatics and Biological Engineering (ICBBE 2015), Stockholm, Sweden.