EEG emotion recognition using dynamical graph convolutional neural networks
In this paper, a multichannel EEG emotion recognition method based on a novel dynamical
graph convolutional neural networks (DGCNN) is proposed. The basic idea of the proposed …
graph convolutional neural networks (DGCNN) is proposed. The basic idea of the proposed …
Emotionmeter: A multimodal framework for recognizing human emotions
In this paper, we present a multimodal emotion recognition framework called EmotionMeter
that combines brain waves and eye movements. To increase the feasibility and wearability …
that combines brain waves and eye movements. To increase the feasibility and wearability …
EEG channel correlation based model for emotion recognition
Abstract Emotion recognition using Artificial Intelligence (AI) is a fundamental prerequisite to
improve Human-Computer Interaction (HCI). Recognizing emotion from …
improve Human-Computer Interaction (HCI). Recognizing emotion from …
An efficient LSTM network for emotion recognition from multichannel EEG signals
Most previous EEG-based emotion recognition methods studied hand-crafted EEG features
extracted from different electrodes. In this article, we study the relation among different EEG …
extracted from different electrodes. In this article, we study the relation among different EEG …
Transfer learning for EEG-based brain–computer interfaces: A review of progress made since 2016
A brain–computer interface (BCI) enables a user to communicate with a computer directly
using brain signals. The most common noninvasive BCI modality, electroencephalogram …
using brain signals. The most common noninvasive BCI modality, electroencephalogram …
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 …
Emotion recognition for human-robot interaction: Recent advances and future perspectives
A fascinating challenge in the field of human–robot interaction is the possibility to endow
robots with emotional intelligence in order to make the interaction more intuitive, genuine …
robots with emotional intelligence in order to make the interaction more intuitive, genuine …
Multisource transfer learning for cross-subject EEG emotion recognition
Electroencephalogram (EEG) has been widely used in emotion recognition due to its high
temporal resolution and reliability. Since the individual differences of EEG are large, the …
temporal resolution and reliability. Since the individual differences of EEG are large, the …
Contrastive learning of subject-invariant EEG representations for cross-subject emotion recognition
EEG signals have been reported to be informative and reliable for emotion recognition in
recent years. However, the inter-subject variability of emotion-related EEG signals still poses …
recent years. However, the inter-subject variability of emotion-related EEG signals still poses …
Emotion recognition from multi-channel EEG through parallel convolutional recurrent neural network
Y Yang, Q Wu, M Qiu, Y Wang… - 2018 international joint …, 2018 - ieeexplore.ieee.org
As a challenging pattern recognition task, automatic real-time emotion recognition based on
multi-channel EEG signals is becoming an important computer-aided method for emotion …
multi-channel EEG signals is becoming an important computer-aided method for emotion …