Rapidly growing empirical evidence supports the hypothesis that the cortex operates near
criticality. Although the confirmation of this hypothesis would mark a significant advance in …

An immense body of research has focused on chaotic systems, mainly because of their
interesting applications in a wide variety of fields. A comprehensive understanding and …

Alzheimer's disease (AD) is the most common neurodegenerative disorder. Although a
definite diagnosis is only possible by necropsy, a differential diagnosis with other types of …

This paper presents a new approach called clustering technique-based least square support
vector machine (CT-LS-SVM) for the classification of EEG signals. Decision making is …

In this study, we investigate permutation entropy as a tool to predict the absence seizures of
genetic absence epilepsy rats from Strasbourg (GAERS) by using EEG recordings. The …

Background Motor imagery can elicit brain oscillations in Rolandic mu rhythm and central
beta rhythm, both originating in the sensorimotor cortex. In contrast with simple limb motor …

The electroencephalogram (EEG) signal plays a key role in the diagnosis of epilepsy.
Substantial data is generated by the EEG recordings of ambulatory recording systems, and …

Alzheimer's disease (AD) is the most prevalent form of dementia in the world, which is
characterised by the loss of neurones and the build-up of plaques in the brain, causing …

Background Approximate entropy (AE) has been proposed as a measure of anesthetic drug
effect in electroencephalographic data. Recently, a new method called permutation entropy …

In this paper, we propose to use permutation entropy to explore whether the changes in
electroencephalogram (EEG) data can effectively distinguish different phases in human …