Machine Learning Classification of Epileptic Seizures Based on EEG: using Third-Ordered Cumulants and Adaptive Fractal Analysis Techniques - Softcover

Gajula, Buchanna

Softcover

ISBN 10: 6206152960 ISBN 13: 9786206152965

Publisher: LAP LAMBERT Academic Publishing, 2023

Synopsis

Machine Learning Classification of Epileptic Seizures Based on Electroencephalogram using Third-Ordered Cumulants and Adaptive Fractal Analysis Techniques1 IntroductionEpilepsy is one of the serious neurological diseases in the world. Indeed, early detection of epileptic seizures will extend the life span of epileptic patients. In this regard, a lot of efforts has been done to predict epileptic seizures based on electroencephalography (EEG) signals. In literature, there are many feature-based seizure classification methods quoted. No method is proved perfectly in capturing a standard set of features with the dynamics of signals. It is a common neurological disorder caused by the abnormally rapid release of brain nerve cells that is characterized by seizures. The scalp or intracranial Electroencephalogram (EEG) signals obtained in the clinic typically exhibit characteristics such as chaos, nonlinearity, etc.Deep neural networks have made significant advances in the field of machine learning during the last era. The model can learn effective representations from raw data in both supervised and unsupervised contexts by creating a hierarchical or "deep" structure.

Edition details

• Publisher: LAP LAMBERT Academic Publishing
• Publication date: 2023
• Language: English
• ISBN 10: 6206152960
• ISBN 13: 9786206152965
• Binding: Paperback
• Number of pages: 128