Concepts, Techniques, Challenges and Future Trends of EEG Seizure Detection: A Survey

Authors

  • Suresh Nalla Research Scholar, Department of ECE, Chaitanya Deemed to be University, Hanamkonda , Warangal ,Telangana ,India.
  • Seetharam Khetavath Professor, Department of ECE, Chaitanya Deemed to be University, Hanamkonda , Warangal ,Telangana ,India.

Keywords:

Epilepsy, Electroencephalography (EEG), Features extraction, Classification, Artificial intelligence

Abstract

Epilepsy is a term that is commonly used to refer to a condition of the central nervous system. Epilepsy is characterized by an aberrant pattern of brain activity, which can result in episodes of bizarre behavior, seizures, and even a temporary loss of awareness. Patients with epilepsy experience difficulties in their day-to-day lives as a direct result of the measures they are need to take in order to adapt to their disease. This is especially true for situations in which they are required to utilize heavy equipment, such as when driving a vehicle. Studies on epilepsy rely heavily on electroencephalography (EEG) signals as their primary method for analyzing the activity of the brain during seizures. To manually determine the location of seizures in EEG signals is a laborious and time-consuming process that can be frustrating at times. One of the most important instruments that can assist medical professionals and people in taking the necessary safety measures is the automatic detection framework. This article explores the mental disorder of epilepsy, along with the various forms of seizures. It also discusses the preprocessing operations carried out on EEG data, which is a commonly retrieved feature from the signal. Additionally, it provides a full overview of the classification processes employed in addressing this issue. Furthermore, this essay provides valuable perspectives on the difficulties and prospective areas for future investigation in this innovative topic. This paper offers a comprehensive review of recent approaches to studying epileptic seizures. It also presents researchers with ideas and concepts for developing an automated system that uses EEG data, Internet of Things technology, and machine learning classifiers to remotely monitor patients with epilepsy in smart healthcare systems. Furthermore, this paper provides an overview of new approaches employed in studying the epileptic seizure phenomenon. The identification of seizures using EEG poses several challenges and unresolved research questions, which are the focus of this last examination.

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24.03.2024

How to Cite

Nalla, S. ., & Khetavath, S. . (2024). Concepts, Techniques, Challenges and Future Trends of EEG Seizure Detection: A Survey. International Journal of Intelligent Systems and Applications in Engineering, 12(20s), 598–610. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5191

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Vol. 12 No. 20s (2024)

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Research Article

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