Deep learning techniques for classification of electroencephalogram (EEG) motor imagery (MI) signals: A review
The brain–computer interface (BCI) is an emerging technology that has the potential to
revolutionize the world, with numerous applications ranging from healthcare to human …
revolutionize the world, with numerous applications ranging from healthcare to human …
A comprehensive review of endogenous EEG-based BCIs for dynamic device control
Electroencephalogram (EEG)-based brain–computer interfaces (BCIs) provide a novel
approach for controlling external devices. BCI technologies can be important enabling …
approach for controlling external devices. BCI technologies can be important enabling …
[HTML][HTML] A survey on robots controlled by motor imagery brain-computer interfaces
J Zhang, M Wang - Cognitive Robotics, 2021 - Elsevier
A brain-computer interface (BCI) can provide a communication approach conveying brain
information to the outside. Especially, the BCIs based on motor imagery play the important …
information to the outside. Especially, the BCIs based on motor imagery play the important …
VME-DWT: An efficient algorithm for detection and elimination of eye blink from short segments of single EEG channel
Objective: Recent advances in development of low-cost single-channel
electroencephalography (EEG) headbands have opened new possibilities for applications …
electroencephalography (EEG) headbands have opened new possibilities for applications …
Robot motion control via an EEG-based brain–computer interface by using neural networks and alpha brainwaves
Modern achievements accomplished in both cognitive neuroscience and human–machine
interaction technologies have enhanced the ability to control devices with the human brain …
interaction technologies have enhanced the ability to control devices with the human brain …
Electroencephalogram based brain-computer interface: Applications, challenges, and opportunities
Abstract Brain-Computer Interfaces (BCI) is an exciting and emerging research area for
researchers and scientists. It is a suitable combination of software and hardware to operate …
researchers and scientists. It is a suitable combination of software and hardware to operate …
Benefits of deep learning classification of continuous noninvasive brain–computer interface control
JR Stieger, SA Engel, D Suma… - Journal of neural …, 2021 - iopscience.iop.org
Objective. Noninvasive brain–computer interfaces (BCIs) assist paralyzed patients by
providing access to the world without requiring surgical intervention. Prior work has …
providing access to the world without requiring surgical intervention. Prior work has …
ICA With CWT and k-means for Eye-Blink Artifact Removal From Fewer Channel EEG
AK Maddirala, KC Veluvolu - IEEE Transactions on Neural …, 2022 - ieeexplore.ieee.org
In recent years, there has been an increase in the usage of consumer based EEG devices
with fewer channel configuration. Although independent component analysis has been a …
with fewer channel configuration. Although independent component analysis has been a …
A hybrid end-to-end spatio-temporal attention neural network with graph-smooth signals for EEG emotion recognition
S Sartipi, M Torkamani-Azar… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Recently, physiological data such as electroencephalography (EEG) signals have attracted
significant attention in affective computing. In this context, the main goal is to design an …
significant attention in affective computing. In this context, the main goal is to design an …
Probability mapping based artifact detection and removal from single-channel EEG signals for brain–computer interface applications
Background Different types of artifacts in the electroencephalogram (EEG) signals can
considerably reduce the performance of the later-stage EEG analysis algorithms for making …
considerably reduce the performance of the later-stage EEG analysis algorithms for making …