Epileptic Seizure Detection using Denoising Autoencoder

Abstract

Epileptic seizures are a common neurological disorder characterized by abnormal brain activity. Early and accurate detection of seizures plays a crucial role in effective treatment and improving the quality of life for individuals with epilepsy. This research paper proposes a innovative strategy for epileptic seizure detection utilizing a denoising autoencoder (DAE). The DAE is a feature extraction technique to enhance the discriminatory power of electroencephalogram (EEG) signals, commonly used for seizure detection. The suggested method's excellent sensitivity and specificity in correctly recognizing epileptic seizures is supported by the results of experiments.