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A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update
Objective. Most current electroencephalography (EEG)-based brain–computer interfaces
(BCIs) are based on machine learning algorithms. There is a large diversity of classifier …
(BCIs) are based on machine learning algorithms. There is a large diversity of classifier …
Affective brain–computer interfaces (abcis): A tutorial
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 …
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
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 …
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
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 …
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
Machine learning and its subfield deep learning techniques provide opportunities for the
development of operator mental state monitoring, especially for cognitive workload …
development of operator mental state monitoring, especially for cognitive workload …
Riemannian approaches in brain-computer interfaces: a review
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 …
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
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 …
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
Recent developments and studies in brain-computer interface (BCI) technologies have
facilitated emotion detection and classification. Many BCI studies have sought to investigate …
facilitated emotion detection and classification. Many BCI studies have sought to investigate …
A multimodal approach to estimating vigilance using EEG and forehead EOG
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 …
user-aware human computer interactions. In this paper, we focus on the problem of …
[KNJIGA][B] Brain–computer interfaces handbook: technological and theoretical advances
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 …
tutorial and an overview of the rich and multi-faceted world of Brain–Computer Interfaces …