Cross-Subject EEG-Based Emotion Recognition via Semisupervised Multisource Joint Distribution Adaptation

Most emotion recognition systems still present limited applicability to new users due to the intersubject variability of electroencephalogram (EEG) signals. Although domain adaptation methods have been adopted to tackle this problem, most methodologies deal with unlabeled data from a target subject....

Full description

Bibliographic Details

Published in:	IEEE transactions on instrumentation and measurement Vol. 72; pp. 1 - 11
Main Authors:	Jimenez-Guarneros, Magdiel, Fuentes-Pineda, Gibran
Format:	Journal Article
Language:	English
Published:	New York IEEE 2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Adaptation Alignment Deep learning electroencephalogram Electroencephalography Emotion recognition Emotions Feature extraction Knowledge management Knowledge transfer multisource domain adaptation (MSDA) Physiology Proposals semisupervised domain adaptation (SSDA) Target recognition
ISSN:	0018-9456, 1557-9662
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!