The electroencephalogram (EEG) is a fundamental tool in the diagnosis and classification of
epilepsy. In particular, Interictal Epileptiform Discharges (IEDs) reflect an increased …

Neural network (NN) finds role in variety of applications due to combined effect of feature
extraction and classification availability in deep learning algorithms. In this paper, we have …

Over many decades, research is being attempted for the detection of epileptic seizure to
support for automatic diagnosis system to help clinicians from burdensome work. In this …

Sleep scoring is one of the most important diagnostic methods in psychiatry and neurology.
Sleep staging is a time consuming and difficult task undertaken by sleep experts. This study …

Epileptic patients suffer from an epileptic brain seizure caused by the temporary and
unpredicted electrical interruption. Conventionally, the electroencephalogram (EEG) signals …

Epilepsy is one of the most common neurological disorders–approximately one in every 100
people worldwide are suffering from it. The electroencephalogram (EEG) is the most …

Over several years, research had been conducted for the detection of epileptic seizures to
support an automatic diagnosis system to comfort the clinicians' encumbrance. In this …

In this paper we describe the effect of Multiscale Principal Component Analysis (MSPCA) de-
noising method in terms of epileptic seizure detection. In addition, we developed a patient …

Electroencephalogram (EEG) signal-processing techniques are the prominent role in the
detection and prediction of epileptic seizures. The detection of epileptic activity is …

Electroencephalogram (EEG) signal serves is a powerful tool in epilepsy detection. This
study decomposes intrinsic mode functions (IMFs) into amplitude envelope and frequency …