International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | A Survey on Epileptic Seizure Detection Using Deep Learning |
|---|---|
| ABSTRACT | Epilepsy is a neurological disorder characterized by recurrent seizures caused by abnormal electrical activity in the brain. Electroencephalography (EEG) is widely used for epilepsy diagnosis because of its high temporal resolution and ability to capture neural activity in real time. However, manual inspection of long-duration EEG recordings is time-consuming and prone to human error. Automated seizure detection has therefore become an important research area in biomedical signal processing and artificial intelligence. Recent advances in deep learning enable models to automatically learn discriminative patterns from EEG signals without extensive handcrafted feature engineering. Architectures such as Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM) networks, hybrid CNN–LSTM models, attention mechanisms, and transformer-based approaches have demonstrated promising results in recent studies. This survey reviews recent deep learning approaches for EEG-based epileptic seizure detection published between 2022 and 2025, analyses commonly used datasets and evaluation metrics, and highlights research limitations such as partial dataset utilization and accuracy-centric evaluation. Finally, potential research directions are discussed for developing reliable and clinically deployable seizure detection systems. |
| AUTHOR | MANDHARE SANKET SUBHASH, V. A. DESHMUKH Student, Department of Computer Engineering, P. E. S. Modern College of Engineering (Affiliated to Savitribai Phule Pune University), Pune, India Assistant Professor, Department of Computer Engineering, P. E. S. Modern College of Engineering (Affiliated to Savitribai Phule Pune University), Pune, India |
| VOLUME | 183 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1404031 |
| pdf/31_A Survey on Epileptic Seizure Detection Using Deep Learning.pdf | |
| KEYWORDS | |
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