[HTML][HTML] Human emotion recognition: Review of sensors and methods
Automated emotion recognition (AEE) is an important issue in various fields of activities
which use human emotional reactions as a signal for marketing, technical equipment, or …
which use human emotional reactions as a signal for marketing, technical equipment, or …
[HTML][HTML] A systematic survey on multimodal emotion recognition using learning algorithms
Emotion recognition is the process to detect, evaluate, interpret, and respond to people's
emotional states and emotions, ranging from happiness to fear to humiliation. The COVID-19 …
emotional states and emotions, ranging from happiness to fear to humiliation. The COVID-19 …
[HTML][HTML] Affective computing in virtual reality: emotion recognition from brain and heartbeat dynamics using wearable sensors
Affective Computing has emerged as an important field of study that aims to develop
systems that can automatically recognize emotions. Up to the present, elicitation has been …
systems that can automatically recognize emotions. Up to the present, elicitation has been …
Making sense of spatio-temporal preserving representations for EEG-based human intention recognition
Brain-computer interface (BCI) is a system empowering humans to communicate with or
control the outside world with exclusively brain intentions. Electroencephalography (EEG) …
control the outside world with exclusively brain intentions. Electroencephalography (EEG) …
Emotion recognition from EEG signal focusing on deep learning and shallow learning techniques
Recently, electroencephalogram-based emotion recognition has become crucial in enabling
the Human-Computer Interaction (HCI) system to become more intelligent. Due to the …
the Human-Computer Interaction (HCI) system to become more intelligent. Due to the …
[HTML][HTML] Emotion recognition based on EEG feature maps through deep learning network
A Topic, M Russo - Engineering Science and Technology, an International …, 2021 - Elsevier
Emotion recognition using electroencephalogram (EEG) signals is getting more and more
attention in recent years. Since the EEG signals are noisy, non-linear and have non …
attention in recent years. Since the EEG signals are noisy, non-linear and have non …
Driver stress detection via multimodal fusion using attention-based CNN-LSTM
Stress has been identified as one of major contributing factors in car crashes due to its
negative impact on driving performance. It is in urgent need that the stress levels of drivers …
negative impact on driving performance. It is in urgent need that the stress levels of drivers …
A comprehensive survey on emotion recognition based on electroencephalograph (EEG) signals
K Kamble, J Sengupta - Multimedia Tools and Applications, 2023 - Springer
Emotion recognition using electroencephalography (EEG) is becoming an interesting topic
among researchers. It has made a remarkable entry in the domain of biomedical, smart …
among researchers. It has made a remarkable entry in the domain of biomedical, smart …
Automated accurate emotion recognition system using rhythm-specific deep convolutional neural network technique with multi-channel EEG signals
Emotion is interpreted as a psycho-physiological process, and it is associated with
personality, behavior, motivation, and character of a person. The objective of affective …
personality, behavior, motivation, and character of a person. The objective of affective …
Automated emotion recognition based on higher order statistics and deep learning algorithm
The objective of this paper is online recognition of human emotions based on
electroencephalogram (EEG) signals. The emotions are originated from the central and …
electroencephalogram (EEG) signals. The emotions are originated from the central and …