Using electroencephalogram for emotion recognition based on filter-bank long short-term memory networks / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 447-454, 2021.
Article
in Chinese
| WPRIM
| ID: wpr-888200
ABSTRACT
Emotion plays an important role in people's cognition and communication. By analyzing electroencephalogram (EEG) signals to identify internal emotions and feedback emotional information in an active or passive way, affective brain-computer interactions can effectively promote human-computer interaction. This paper focuses on emotion recognition using EEG. We systematically evaluate the performance of state-of-the-art feature extraction and classification methods with a public-available dataset for emotion analysis using physiological signals (DEAP). The common random split method will lead to high correlation between training and testing samples. Thus, we use block-wise
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Arousal
/
Neural Networks, Computer
/
Electroencephalography
/
Emotions
/
Memory, Short-Term
Limits:
Humans
Language:
Chinese
Journal:
Journal of Biomedical Engineering
Year:
2021
Type:
Article
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