Detection of Epileptic Seizures Using Hybrid Deep Learning Approaches

Authors

  • K. Dileep Kumar Ph.D Scholar Computer Science & Engineering GIET University
  • Sachikanta Dash Associate Professor, Computer Science & Engineering, GIET University
  • Rajendra Kumar Ganiya Professor Computer Science &Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, A.P, 522302, India

Keywords:

Epilepsy, electroencephalography (EEG), Deep Learning (DL), epileptic seizures

Abstract

Epilepsy is a brain disorder that results in abnormal electrical activity in the brain. Epilepsy is also called a seizure disorder. The diagnosis of epilepsy can be made if the person suffers from two or more seizures. Seizures are the main symptom of epilepsy. Different models are introduced to diagnose epileptic seizures with the help of electroencephalography (EEG). EEG are wavelet signals that are most widely used to find the abnormal events identified in the brain. Deep Learning (DL) algorithms can efficiently discover epileptic seizures based on their features. In this paper, an automated epilepsy seizure detection system (AESD) is developed to diagnose and detect epilepsy seizures from the human brain. The existing models analyze many challenges to seeing this disease. The dataset attributes include patient family history, age, and information about patient medicines that have been used for a long time. The performance is analyzed based on the parameters.

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Published

27.10.2023

How to Cite

Kumar, K. D. ., Dash, S. ., & Ganiya, R. K. . (2023). Detection of Epileptic Seizures Using Hybrid Deep Learning Approaches. International Journal of Intelligent Systems and Applications in Engineering, 12(2s), 174–180. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3568

Issue

Vol. 12 No. 2s (2024)

Section

Research Article

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