Epilepsy is the only neurological condition for which electroencephalography (EEG) is the
primary diagnostic and important prognostic clinical tool. However, the manual inspection of …

Many deep-learning-based seizure detection algorithms have achieved good classification,
which usually outperformed traditional machine-learning-based algorithms. However, the …

Epilepsy is a chronic brain disease, and identifying seizures based on
electroencephalogram (EEG) signals would be conducive to implement interventions to help …

Epilepsy is a prevalent neurological disorder with considerable risks, including physical
impairment and irreversible brain damage from seizures. Given these challenges, the …

k-NN, as one of the well-employed classification algorithms, severely suffers from a
computationally intensive nature. This paper exploits the parallelism and digit level …

Numerous machine learning methods depend on distance measures. In both supervised
and unsupervised learning, these distance measures are primarily employed to assess the …

Epilepsy is a common neurological disorder that occurs at all ages. Epilepsy not only brings
physical pain to patients, but also brings a huge burden to the lives of patients and their …

This paper provides a review of machine learning-based approaches to
electroencephalogram (EEG) data classification. Machine learning algorithms are used to …

The diagnosis and treatment of brain diseases represent the forefront of brain science
research, with EEG-related research occupying a uniquely significant position. In recent …

The classification of EEG (Electroencephalogram) signals requires design of multidomain
modules, including signal pre-processing, filtering, segmentation, extraction of features from …