Sample Entropy on Multidistance Signal Level Difference for Epileptic EEG Classification
Joint Authors
Rizal, Achmad
Hadiyoso, Sugondo
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-09-12
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Epilepsy is a disorder of the brain’s nerves as a result of excessive brain cell activity.
It is generally characterized by the recurrent unprovoked seizures.
This neurological abnormality can be detected and evaluated using Electroencephalogram (EEG) signal.
Many algorithms have been applied to achieve high performance for the EEG classification of epileptic.
However, the complexity and randomness of EEG signals become a challenge to researchers in applying the appropriate algorithms.
In this research, sample entropy on Multidistance Signal Level Difference (MSLD) was applied to obtain the characteristic of EEG signals, especially towards the epilepsy patients.
The test was performed on three classes of EEG data: EEG signals of epilepsy patient in ictal (seizure), interictal conditions (occurring between seizures) and normal EEG signals from healthy subjects with a closed eye condition.
In this study, classification and verification were done using the Support Vector Machine (SVM) method.
Through the 5-fold cross-validation, experimental results showed the highest accuracy of 97.7%.
American Psychological Association (APA)
Rizal, Achmad& Hadiyoso, Sugondo. 2018. Sample Entropy on Multidistance Signal Level Difference for Epileptic EEG Classification. The Scientific World Journal،Vol. 2018, no. 2018, pp.1-6.
https://search.emarefa.net/detail/BIM-1215670
Modern Language Association (MLA)
Rizal, Achmad& Hadiyoso, Sugondo. Sample Entropy on Multidistance Signal Level Difference for Epileptic EEG Classification. The Scientific World Journal No. 2018 (2018), pp.1-6.
https://search.emarefa.net/detail/BIM-1215670
American Medical Association (AMA)
Rizal, Achmad& Hadiyoso, Sugondo. Sample Entropy on Multidistance Signal Level Difference for Epileptic EEG Classification. The Scientific World Journal. 2018. Vol. 2018, no. 2018, pp.1-6.
https://search.emarefa.net/detail/BIM-1215670
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1215670