Multimodal fusion framework: A multiresolution approach for emotion classification and recognition from physiological signals
The purpose of this paper is twofold:(i) to investigate the emotion representation models and
find out the possibility of a model with minimum number of continuous dimensions and (ii) to …
find out the possibility of a model with minimum number of continuous dimensions and (ii) to …
[HTML][HTML] Survey of emotion recognition methods using EEG information
C Yu, M Wang - Cognitive Robotics, 2022 - Elsevier
Emotion is an indispensable part of human emotion, which affects human normal
physiological activities and daily life decisions. Human emotion recognition is a critical …
physiological activities and daily life decisions. Human emotion recognition is a critical …
Real-time EEG-based emotion monitoring using stable features
In human–computer interaction (HCI), electroencephalogram (EEG) signals can be added
as an additional input to computer. An integration of real-time EEG-based human emotion …
as an additional input to computer. An integration of real-time EEG-based human emotion …
Real-time EEG-based emotion recognition and its applications
Y Liu, O Sourina, MK Nguyen - … Science XII: Special Issue on Cyberworlds, 2011 - Springer
Since emotions play an important role in the daily life of human beings, the need and
importance of automatic emotion recognition has grown with increasing role of human …
importance of automatic emotion recognition has grown with increasing role of human …
Real-time EEG-based human emotion recognition and visualization
Y Liu, O Sourina, MK Nguyen - 2010 international conference …, 2010 - ieeexplore.ieee.org
Emotions accompany everyone in the daily life, playing a key role in non-verbal
communication, and they are essential to the understanding of human behavior. Emotion …
communication, and they are essential to the understanding of human behavior. Emotion …
EEG-based emotion estimation using Bayesian weighted-log-posterior function and perceptron convergence algorithm
This paper addresses the emotion recognition problem from electroencephalogram signals,
in which emotions are represented on the valence and arousal dimensions. Fast Fourier …
in which emotions are represented on the valence and arousal dimensions. Fast Fourier …
[PDF][PDF] A fractal-based algorithm of emotion recognition from EEG using arousal-valence model.
O Sourina, Y Liu - Biosignals, 2011 - scitepress.org
Emotion recognition from EEG could be used in many applications as it allows us to know
the “inner” emotion regardless of the human facial expression, behaviour, or verbal …
the “inner” emotion regardless of the human facial expression, behaviour, or verbal …
Evaluating classifiers for emotion recognition using EEG
AT Sohaib, S Qureshi, J Hagelbäck, O Hilborn… - … AC 2013, Held as Part of …, 2013 - Springer
There are several ways of recording psychophysiology data from humans, for example
Galvanic Skin Response (GSR), Electromyography (EMG), Electrocardiogram (ECG) and …
Galvanic Skin Response (GSR), Electromyography (EMG), Electrocardiogram (ECG) and …
Fear level classification based on emotional dimensions and machine learning techniques
There has been steady progress in the field of affective computing over the last two decades
that has integrated artificial intelligence techniques in the construction of computational …
that has integrated artificial intelligence techniques in the construction of computational …
Real-time EEG-based emotion recognition for music therapy
O Sourina, Y Liu, MK Nguyen - Journal on Multimodal User Interfaces, 2012 - Springer
Music could change our emotions, could have an influence on our mood, and finally could
affect our health. Music therapy is one of the oldest methods used for treating some …
affect our health. Music therapy is one of the oldest methods used for treating some …