کنفرانس مهندسی برق ایران

صفحه اصلی / سی و سومین کنفرانس بین المللی مهندسی برق

DWT-Based Epileptic Seizure Detection Using Fuzzy Logic Model with Entropy and Table Lookup Scheme

نویسندگان :

Alireza Mohammadi¹ Arvin Esfandyari² Ali Doustmohammadi³ Amir Abolfazl Suratgar⁴ Masoud Shafiee⁵

1- دانشگاه صنعتی امیرکبیر 2- دانشگاه صنعتی امیرکبیر 3- دانشگاه صنعتی امیرکبیر 4- دانشگاه صنعتی امیرکبیر 5- دانشگاه صنعتی امیرکبیر

کلمات کلیدی :

Epilepsy detection،EEG signals،DWT،Fuzzy Entropy،Look-up Table

چکیده :

Epilepsy is a complex neurological condition affecting over 65 million people worldwide. Effective detection of epileptic seizures is critical for appropriate management and treatment. This study introduces a novel approach for epilepsy detection by employing a fuzzy entropy-based method combined with a Discrete Wavelet Transform (DWT) and a Look-up Table framework. Utilizing the well-known Bonn EEG dataset, we restructured the data into two primary classes, representing signals from healthy individuals and patients experiencing different stages of epilepsy. Our model demonstrates significant enhancements in detecting epileptic seizures, achieving remarkable accuracy and robustness across two classification scenarios. We employed standard evaluation metrics such as accuracy, precision, recall, F1 score, and specificity to assess model performance. The results were compared with existing machine learning and deep learning methods, showcasing our approach's superior computational efficiency and interpretability.