Advances in Multimodal Emotion Recognition Based on Brain–Computer Interfaces
With the continuous development of portable noninvasive human sensor technologies such as brain–computer interfaces (BCI), multimodal emotion recognition has attracted increasing attention in the area of affective computing. This paper primarily discusses the progress of research into multimodal emo...
Main Authors: | Zhipeng He, Zina Li, Fuzhou Yang, Lei Wang, Jingcong Li, Chengju Zhou, Jiahui Pan |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-09-01
|
Series: | Brain Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3425/10/10/687 |
Similar Items
-
Enhancing BCI-Based Emotion Recognition Using an Improved Particle Swarm Optimization for Feature Selection
by: Zina Li, et al.
Published: (2020-05-01) -
Deep Multimodal Emotion Recognition on Human Speech: A Review
by: Panagiotis Koromilas, et al.
Published: (2021-08-01) -
Nuclear Norm Regularized Deep Neural Network for EEG-Based Emotion Recognition
by: Shuang Liang, et al.
Published: (2022-06-01) -
Using Noninvasive Wearable Computers to Recognize Human Emotions from Physiological Signals
by: Nasoz Fatma, et al.
Published: (2004-01-01) -
A Framework to Evaluate Fusion Methods for Multimodal Emotion Recognition
by: Diego Pena, et al.
Published: (2023-01-01)