The benefits of early detection and classification of epileptic seizures in analysis, monitoring
and diagnosis for the realization and actualization of computer-aided devices and recent …

Correctly interpreting an Electroencephalography (EEG) signal with high accuracy is a
tedious and time-consuming task that may take several years of manual training due to its …

Epilepsy is a complex disease, difficult to detect and common among neurological diseases.
The separation of epileptic and non-epileptic activity and the identification of the form of the …

The Human Activity Recognition (HAR) system is the hottest research area in clinical
research. The HAR plays a vital role in learning about a patient's abnormal activities; based …

Early detection and proper treatment of epilepsy seizure is essential and meaningful to
those who suffer from this disease. Symptoms of seizures are confusion, abnormal gazing …

Focal and non-focal Electroencephalogram (EEG) signals have proved to be effective
techniques for identifying areas in the brain that are affected by epileptic seizures, known as …

Epilepsy is a disease with various forms. However, limited dataset has confined
classification studies of epilepsy into binary classes only. This study sort to achieve …

Epilepsy is a neurological illness that causes seizures in the brain and affects a huge
number of people worldwide. Electroencephalography (EEG) is the most commonly used …

This study investigates the effect of data decomposition to improve the performance of
artificial neural networks (ANNs), widely used in wind speed forecasting in the wind energy …

The control of intelligent peripheral devices such as robot arm and mouse movement
through brain-computer interface needs to be based on accurate feature extraction and …