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 …
Human emotion recognition from EEG-based brain–computer interface using machine learning: a comprehensive review
EH Houssein, A Hammad, AA Ali - Neural Computing and Applications, 2022 - Springer
Affective computing, a subcategory of artificial intelligence, detects, processes, interprets,
and mimics human emotions. Thanks to the continued advancement of portable non …
and mimics human emotions. Thanks to the continued advancement of portable non …
Deep learning with convolutional neural networks for EEG decoding and visualization
RT Schirrmeister, JT Springenberg… - Human brain …, 2017 - Wiley Online Library
Deep learning with convolutional neural networks (deep ConvNets) has revolutionized
computer vision through end‐to‐end learning, that is, learning from the raw data. There is …
computer vision through end‐to‐end learning, that is, learning from the raw data. There is …
EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces
Objective. Brain–computer interfaces (BCI) enable direct communication with a computer,
using neural activity as the control signal. This neural signal is generally chosen from a …
using neural activity as the control signal. This neural signal is generally chosen from a …
Gradient boosting machines, a tutorial
A Natekin, A Knoll - Frontiers in neurorobotics, 2013 - frontiersin.org
Gradient boosting machines are a family of powerful machine-learning techniques that have
shown considerable success in a wide range of practical applications. They are highly …
shown considerable success in a wide range of practical applications. They are highly …
A comprehensive review of EEG-based brain–computer interface paradigms
Advances in brain science and computer technology in the past decade have led to exciting
developments in brain–computer interface (BCI), thereby making BCI a top research area in …
developments in brain–computer interface (BCI), thereby making BCI a top research area in …
A survey on measuring cognitive workload in human-computer interaction
The ever-increasing number of computing devices around us results in more and more
systems competing for our attention, making cognitive workload a crucial factor for the user …
systems competing for our attention, making cognitive workload a crucial factor for the user …
[HTML][HTML] Brain computer interfaces, a review
LF Nicolas-Alonso, J Gomez-Gil - sensors, 2012 - mdpi.com
A brain-computer interface (BCI) is a hardware and software communications system that
permits cerebral activity alone to control computers or external devices. The immediate goal …
permits cerebral activity alone to control computers or external devices. The immediate goal …
Current status, challenges, and possible solutions of EEG-based brain-computer interface: a comprehensive review
Brain-Computer Interface (BCI), in essence, aims at controlling different assistive devices
through the utilization of brain waves. It is worth noting that the application of BCI is not …
through the utilization of brain waves. It is worth noting that the application of BCI is not …
Learning representations from EEG with deep recurrent-convolutional neural networks
One of the challenges in modeling cognitive events from electroencephalogram (EEG) data
is finding representations that are invariant to inter-and intra-subject differences, as well as …
is finding representations that are invariant to inter-and intra-subject differences, as well as …