Automatic identification of negative stress is an unresolved challenge that has received
great attention in the last few years. Many studies have analyzed electroencephalographic …

Negative stress, also named distress, is nowadays one of the most studied emotional states
due to its high impact on advanced societies. Its automatic identification from physiological …

Recognition of emotions is still an unresolved challenge, which could be helpful to improve
current human-machine interfaces. Recently, nonlinear analysis of some physiological …

Distress is a critical problem in developed societies given its long-term negative effects on
physical and mental health. The interest in studying this emotion has notably increased …

The electroencephalogram (EEG) is the most common tool used to study mental disorders.
In the last years, the use of this recording for recognition of negative stress has been …

A multivariate sample entropy metric of signal complexity is applied to EEG data recorded
when subjects were viewing four prior-labeled emotion-inducing video clips from a …

Negative stress, or distress, represents a serious problem in advanced societies given its
adverse consequences for health. Many studies have focused on the detection of distress …

Recently, the recognition of emotions with electroencephalographic (EEG) signals has
received increasing attention. Furthermore, the nonstationarity of brain has intensified the …

This paper introduces new methods to extract stress features from electroencephalogram
(EEG) signals during two cognitive states; Closed-Eyes (CE) and Open-Eyes (OE) using …

The present study aims to apply multiscale entropy (MSE) to analyse brain activity in terms of
brain complexity levels and to use simultaneous electroencephalogram and functional near …