Interface, interaction, and intelligence in generalized brain–computer interfaces

X Gao, Y Wang, X Chen, S Gao - Trends in cognitive sciences, 2021 - cell.com
A brain–computer interface (BCI) establishes a direct communication channel between a
brain and an external device. With recent advances in neurotechnology and artificial …

Recognition of human emotions using EEG signals: A review

MM Rahman, AK Sarkar, MA Hossain… - Computers in biology …, 2021 - Elsevier
Assessment of the cognitive functions and state of clinical subjects is an important aspect of
e-health care delivery, and in the development of novel human-machine interfaces. A …

EEG-based BCI emotion recognition: A survey

EP Torres, EA Torres, M Hernández-Álvarez, SG Yoo - Sensors, 2020 - mdpi.com
Affecting computing is an artificial intelligence area of study that recognizes, interprets,
processes, and simulates human affects. The user's emotional states can be sensed through …

Emotionmeter: A multimodal framework for recognizing human emotions

WL Zheng, W Liu, Y Lu, BL Lu… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
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 …

Transfer learning for EEG-based brain–computer interfaces: A review of progress made since 2016

D Wu, Y Xu, BL Lu - IEEE Transactions on Cognitive and …, 2020 - ieeexplore.ieee.org
A brain–computer interface (BCI) enables a user to communicate with a computer directly
using brain signals. The most common noninvasive BCI modality, electroencephalogram …

Identifying stable patterns over time for emotion recognition from EEG

WL Zheng, JY Zhu, BL Lu - IEEE transactions on affective …, 2017 - ieeexplore.ieee.org
In this paper, we investigate stable patterns of electroencephalogram (EEG) over time for
emotion recognition using a machine learning approach. Up to now, various findings of …

Multisource transfer learning for cross-subject EEG emotion recognition

J Li, S Qiu, YY Shen, CL Liu… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
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 …

Contrastive learning of subject-invariant EEG representations for cross-subject emotion recognition

X Shen, X Liu, X Hu, D Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
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 …

EEG-based emotion recognition using 4D convolutional recurrent neural network

F Shen, G Dai, G Lin, J Zhang, W Kong… - Cognitive …, 2020 - Springer
In this paper, we present a novel method, called four-dimensional convolutional recurrent
neural network, which integrating frequency, spatial and temporal information of …

Domain adaptation techniques for EEG-based emotion recognition: a comparative study on two public datasets

Z Lan, O Sourina, L Wang, R Scherer… - … on Cognitive and …, 2018 - ieeexplore.ieee.org
Affective brain-computer interface (aBCI) introduces personal affective factors to human-
computer interaction. The state-of-the-art aBCI tailors its classifier to each individual user to …