The unpredictability of epileptic seizures is one of the most problematic aspects of the field of
epilepsy. Methods or devices capable of detecting seizures minutes before they occur may …

Epilepsy is a neurological disorder that causes unusual behavior, sensations, and, in some
cases, loss of awareness. It is accompanied by seizures, which are intervals of unusual …

We present an end-to-end deep learning model that can automatically detect epileptic
seizures in multichannel electroencephalography (EEG) recordings. Our model combines a …

Epilepsy is a common neurological disorder affecting both children and adults. It can trigger
seizures without any stimuli. An accurate diagnosis of epilepsy is essential to the treatment …

This paper presents a trainable hybrid approach involving a shallow autoencoder (AE) and
a conventional classifier for epileptic seizure detection. The signal segments of a channel of …

Epilepsy is a neurological disease caused by ab-normal neural electrical discharges.
Electroencephalography (EEG) is a powerful tool to measure the brain electrical activity and …

The efficient compression and classification of medical signals, particularly
electroencephalography (EEG) and electrocardiography (ECG) signals in wireless body …

Stroke patients are prone to fatigue during the EEG acquisition procedure, and experiments
have high requirements on cognition and physical limitations of subjects. Therefore, how to …

Seizures significantly reduce the quality of life for epilepsy patients. Short detection latency
allows the implementation of a fast response algorithm that can be used for real-time …

Automated epileptic seizure detection has been an active area of research for the last two
decades. Yet few, if any, of these methods are used in clinical practice because they fail to …