A review on nonlinear methods using electroencephalographic recordings for emotion recognition
Electroencephalographic (EEG) recordings are receiving growing attention in the field of
emotion recognition, since they monitor the brain's first response to an external stimulus …
emotion recognition, since they monitor the brain's first response to an external stimulus …
Immersive media experience: a survey of existing methods and tools for human influential factors assessment
Virtual reality (VR) applications, especially those where the user is untethered to a computer,
are becoming more prevalent as new hardware is developed, computational power and …
are becoming more prevalent as new hardware is developed, computational power and …
Detection of epileptic seizure using pretrained deep convolutional neural network and transfer learning
Introduction: The diagnosis of epilepsy takes a certain process, depending entirely on the
attending physician. However, the human factor may cause erroneous diagnosis in the …
attending physician. However, the human factor may cause erroneous diagnosis in the …
Single-trial EEG emotion recognition using Granger Causality/Transfer Entropy analysis
Background Emotion recognition has been studied for decades, but the classification
accuracy needs to be improved. New method In this study, a novel emotional classification …
accuracy needs to be improved. New method In this study, a novel emotional classification …
A new dispersion entropy and fuzzy logic system methodology for automated classification of dementia stages using electroencephalograms
A new EEG-based methodology is presented for differential diagnosis of the Alzheimer's
disease (AD), Mild Cognitive Impairment (MCI), and healthy subjects employing the discrete …
disease (AD), Mild Cognitive Impairment (MCI), and healthy subjects employing the discrete …
Feature and channel selection for designing a regression-based continuous-variable emotion recognition system with two EEG channels
Objective: With deepened interactions between human and computer, the need for a reliable
and practical system for emotion recognition has become significant. The aim of this study is …
and practical system for emotion recognition has become significant. The aim of this study is …
Neural interface instrumented virtual reality headsets: Toward next-generation immersive applications
The last decade has seen a strong resurgence of virtual reality (VR) and augmented reality
(AR) applications, ranging from entertainment to neurorehabilitation. Users of VR headsets …
(AR) applications, ranging from entertainment to neurorehabilitation. Users of VR headsets …
Artificial neural networks to assess emotional states from brain-computer interface
Estimation of human emotions plays an important role in the development of modern brain-
computer interface devices like the Emotiv EPOC+ headset. In this paper, we present an …
computer interface devices like the Emotiv EPOC+ headset. In this paper, we present an …
Emotion classification from EEG with a low-cost BCI versus a high-end equipment
The assessment of physiological signals such as the electroencephalography (EEG) has
become a key point in the research area of emotion detection. This study compares the …
become a key point in the research area of emotion detection. This study compares the …
Deep support vector machines for the identification of stress condition from electrodermal activity
Early detection of stress condition is beneficial to prevent long-term mental illness like
depression and anxiety. This paper introduces an accurate identification of stress/calm …
depression and anxiety. This paper introduces an accurate identification of stress/calm …