A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update

F Lotte, L Bougrain, A Cichocki, M Clerc… - Journal of neural …, 2018 - iopscience.iop.org
Objective. Most current electroencephalography (EEG)-based brain–computer interfaces
(BCIs) are based on machine learning algorithms. There is a large diversity of classifier …

Affective brain–computer interfaces (abcis): A tutorial

D Wu, BL Lu, B Hu, Z Zeng - Proceedings of the IEEE, 2023 - ieeexplore.ieee.org
A brain–computer interface (BCI) enables a user to communicate directly with a computer
using only the central nervous system. An affective BCI (aBCI) monitors and/or regulates the …

Pain and stress detection using wearable sensors and devices—A review

J Chen, M Abbod, JS Shieh - Sensors, 2021 - mdpi.com
Pain is a subjective feeling; it is a sensation that every human being must have experienced
all their life. Yet, its mechanism and the way to immune to it is still a question to be …

Consumer grade EEG measuring sensors as research tools: A review

P Sawangjai, S Hompoonsup… - IEEE Sensors …, 2019 - ieeexplore.ieee.org
Since the launch of the first consumer grade EEG measuring sensorsNeuroSky Mindset'in
2007, the market has witnessed an introduction of at least one new product every year by …

Cognitive workload recognition using EEG signals and machine learning: A review

Y Zhou, S Huang, Z Xu, P Wang, X Wu… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Machine learning and its subfield deep learning techniques provide opportunities for the
development of operator mental state monitoring, especially for cognitive workload …

Riemannian approaches in brain-computer interfaces: a review

F Yger, M Berar, F Lotte - IEEE Transactions on Neural …, 2016 - ieeexplore.ieee.org
Although promising from numerous applications, current brain-computer interfaces (BCIs)
still suffer from a number of limitations. In particular, they are sensitive to noise, outliers and …

[HTML][HTML] Implementation of artificial intelligence and machine learning-based methods in brain–computer interaction

K Barnova, M Mikolasova, RV Kahankova… - Computers in biology …, 2023 - Elsevier
Brain–computer interfaces are used for direct two-way communication between the human
brain and the computer. Brain signals contain valuable information about the mental state …

Review and classification of emotion recognition based on EEG brain-computer interface system research: a systematic review

A Al-Nafjan, M Hosny, Y Al-Ohali, A Al-Wabil - Applied Sciences, 2017 - mdpi.com
Recent developments and studies in brain-computer interface (BCI) technologies have
facilitated emotion detection and classification. Many BCI studies have sought to investigate …

A multimodal approach to estimating vigilance using EEG and forehead EOG

WL Zheng, BL Lu - Journal of neural engineering, 2017 - iopscience.iop.org
Objective. Covert aspects of ongoing user mental states provide key context information for
user-aware human computer interactions. In this paper, we focus on the problem of …

[KNJIGA][B] Brain–computer interfaces handbook: technological and theoretical advances

CS Nam, A Nijholt, F Lotte - 2018 - books.google.com
Brain–Computer Interfaces Handbook: Technological and Theoretical Advances provides a
tutorial and an overview of the rich and multi-faceted world of Brain–Computer Interfaces …