Electroencephalography (EEG) has countless applications across many of fields. However,
EEG applications are limited by low signal-to-noise ratios. Multiple types of artifacts …

Electroencephalogram (EEG) is one of the electrophysiological tests commonly used to
record electrochemical reactions in neural network. In this process various electrodes are …

Although epilepsy is one of the most prevalent and ancient neurological disorder, but, still
difficult to identify the specific type of seizure, due to artefacts, noise, and other disturbances …

Deep learning network (DLN) is defined as the neural network characterized by complex
connected layers to handle a large volume of data, automatic extraction of features, and …

Deep learning (DL) architectures such as deep neural networks (DNN), deep belief
networks (DBN), recurrent neural networks (RNN) and convolutional neural networks (CNN) …

Detection of the Eye State can be helpful in several ways since it can be used as an
indication of mental disorders, energetics in aging, detection of alcoholism, and detection of …

Humans are highly intelligent species which is attributed to their complex brains. Trying to
understand or predict the brain's activities has been one of the greatest challenges of …

According to the World Health Organization (WHO), seventy million individuals worldwide
suffer from epilepsy, a neurological disorder. While electroencephalography (EEG) is crucial …

Lung diseases are the most common ailments seen among people with the history of
smoking. Prompt and timely recognition and diagnosis may help in saving many lives. In …

Background: Epileptic Seizure type diagnosis is done by clinician based on the symptoms
during the episode and the Electroencephalograph (EEG) recording taken during inter-ictal …