A review of emotion recognition using physiological signals
Emotion recognition based on physiological signals has been a hot topic and applied in
many areas such as safe driving, health care and social security. In this paper, we present a …
many areas such as safe driving, health care and social security. In this paper, we present a …
Emotion recognition using eye-tracking: taxonomy, review and current challenges
JZ Lim, J Mountstephens, J Teo - Sensors, 2020 - mdpi.com
The ability to detect users' emotions for the purpose of emotion engineering is currently one
of the main endeavors of machine learning in affective computing. Among the more common …
of the main endeavors of machine learning in affective computing. Among the more common …
Emotion recognition based on multi-variant correlation of physiological signals
W Wen, G Liu, N Cheng, J Wei… - IEEE Transactions …, 2014 - ieeexplore.ieee.org
Emotion recognition based on affective physiological changes is a pattern recognition
problem, and selecting specific physiological signals is necessary and helpful to recognize …
problem, and selecting specific physiological signals is necessary and helpful to recognize …
Spatio-temporal representation of an electoencephalogram for emotion recognition using a three-dimensional convolutional neural network
Emotion recognition plays an important role in the field of human–computer interaction
(HCI). An electroencephalogram (EEG) is widely used to estimate human emotion owing to …
(HCI). An electroencephalogram (EEG) is widely used to estimate human emotion owing to …
Horizontal and vertical features fusion network based on different brain regions for emotion recognition
W Guo, G Xu, Y Wang - Knowledge-Based Systems, 2022 - Elsevier
Deep learning technology has been universally adopted in emotion recognition, which
becomes a promising method that has recently achieved good recognition performance …
becomes a promising method that has recently achieved good recognition performance …
Personalized models for facial emotion recognition through transfer learning
M Rescigno, M Spezialetti, S Rossi - Multimedia Tools and Applications, 2020 - Springer
Emotions represent a key aspect of human life and behavior. In recent years, automatic
recognition of emotions has become an important component in the fields of affective …
recognition of emotions has become an important component in the fields of affective …
Deep learning framework for subject-independent emotion detection using wireless signals
Emotion states recognition using wireless signals is an emerging area of research that has
an impact on neuroscientific studies of human behaviour and well-being monitoring …
an impact on neuroscientific studies of human behaviour and well-being monitoring …
A globally generalized emotion recognition system involving different physiological signals
Machine learning approaches for human emotion recognition have recently demonstrated
high performance. However, only/mostly for subject-dependent approaches, in a variety of …
high performance. However, only/mostly for subject-dependent approaches, in a variety of …
Hybrid mutimodal fusion for dimensional emotion recognition
In this paper, we extensively present our solutions for the MuSe-Stress sub-challenge and
the MuSe-Physio sub-challenge of Multimodal Sentiment Challenge (MuSe) 2021. The goal …
the MuSe-Physio sub-challenge of Multimodal Sentiment Challenge (MuSe) 2021. The goal …
EEG-based multimodal emotion recognition: a machine learning perspective
H Liu, T Lou, Y Zhang, Y Wu, Y Xiao… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Emotion, a fundamental trait of human beings, plays a pivotal role in shaping aspects of our
lives, including our cognitive and perceptual abilities. Hence, emotion recognition also is …
lives, including our cognitive and perceptual abilities. Hence, emotion recognition also is …