Machine Learning (ML) offers unique and powerful tools for mental health practitioners to
improve evidence-based psychological interventions and diagnoses. Indeed, by detecting …

One-fourths of the patients have medication-resistant seizures and require seizure detection
and treatment continuously to cope with sudden seizures. Seizures can be detected by …

Epileptic seizures are one of the most crucial neurological disorders, and their early
diagnosis will help the clinicians to provide accurate treatment for the patients. The …

Electroencephalogram (EEG) is widely used to monitor the brain activities. The manual
examination of these signals by experts is strenuous and time consuming. Hence, machine …

Epilepsy is a brain disorder disease that affects people's quality of life.
Electroencephalography (EEG) signals are used to diagnose epileptic seizures. This paper …

In this work, we conducted a literature review about deep learning (DNN, RNN, CNN, and so
on) for analyzing EEG data for decoding the activity of human's brain and diagnosing …

The epileptic seizure is a transient and abnormal discharge of nerve cells in the brain that
leads to a chronic disease of brain dysfunction. There are various features-based seizures …

Electroencephalography (EEG) is one of the most signals used for studying and
demonstrating the electrical activity of the brain due to the absence of side effects, its …

Based on the current research on EEG emotion recognition, there are some limitations, such
as hand-engineered features, redundant and meaningless signal frames and the loss of …

This paper proposes a new algorithm which combines the information in frequency domain
with the Information Gain (InfoGain) technique for the detection of epileptic seizures from …