IEEE Systems, Man and Cybernetics Magazine - July 2020 - 29

SPECIAL SECTION
B R A I N - M AC H I N E I N T E R FAC E S Y S T E M S

Modern
Machine-Learning
Algorithms

©ISTOCKPHOTO.COM/JUST_SUPER

For Classifying Cognitive and Affective States
From Electroencephalography Signals

by Aurelien Appriou, Andrzej Cichocki,
and Fabien Lotte

Digital Object Identifier 10.1109/MSMC.2020.2968638
Date of current version: 15 July 2020

2333-942X/20©2020IEEE

E

stimating cognitive or affective states from
brain signals is a key but challenging step in creating passive brain-computer interface (BCI)
applications. So far, estimating mental workloads or emotions from electroencephalogram
(EEG) signals is only feasible with modest classification
accuracies, which thus lead to unreliable neuroadaptive
applications. However, recent machine-learning algorithms,
Ju ly 2020

IEEE SYSTEMS, MAN, & CYBERNETICS MAGAZINE

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IEEE Systems, Man and Cybernetics Magazine - July 2020

Table of Contents for the Digital Edition of IEEE Systems, Man and Cybernetics Magazine - July 2020

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IEEE Systems, Man and Cybernetics Magazine - July 2020 - Cover1
IEEE Systems, Man and Cybernetics Magazine - July 2020 - Cover2
IEEE Systems, Man and Cybernetics Magazine - July 2020 - Contents
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IEEE Systems, Man and Cybernetics Magazine - July 2020 - Cover3
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