Review of machine learning techniques for EEG based brain computer interface
S Aggarwal, N Chugh - Archives of Computational Methods in …, 2022 - Springer
A brain computer interface (BCI) framework uses computer algorithms to detect mental
activity patterns and manipulate external devices. Because of its simplicity and non …
activity patterns and manipulate external devices. Because of its simplicity and non …
Brain-computer interface speller system for alternative communication: a review
Brain-computer interface (BCI) speller is a system that provides an alternative
communication for the disable people. The brain wave is translated into machine command …
communication for the disable people. The brain wave is translated into machine command …
Deep learning in EEG: Advance of the last ten-year critical period
Deep learning has achieved excellent performance in a wide range of domains, especially
in speech recognition and computer vision. Relatively less work has been done for …
in speech recognition and computer vision. Relatively less work has been done for …
Stacking-based multi-objective evolutionary ensemble framework for prediction of diabetes mellitus
Diabetes mellitus (DM) is a combination of metabolic disorders characterized by elevated
blood glucose levels over a prolonged duration. Undiagnosed DM can give rise to a host of …
blood glucose levels over a prolonged duration. Undiagnosed DM can give rise to a host of …
MsCNN: A deep learning framework for P300-based brain–computer interface speller
In this paper, a novel multiscale convolutional neural network (MsCNN) architecture is
proposed for P300 based BCI speller. Major limitation of BCI system is that it requires a large …
proposed for P300 based BCI speller. Major limitation of BCI system is that it requires a large …
Ensemble support vector recurrent neural network for brain signal detection
Z Zhang, G Chen, S Yang - IEEE Transactions on Neural …, 2021 - ieeexplore.ieee.org
The brain–computer interface (BCI) P300 speller analyzes the P300 signals from the brain to
achieve direct communication between humans and machines, which can assist patients …
achieve direct communication between humans and machines, which can assist patients …
How Visual Stimuli Evoked P300 is Transforming the Brain–Computer Interface Landscape: A PRISMA Compliant Systematic Review
J Kalra, P Mittal, N Mittal, A Arora… - … on Neural Systems …, 2023 - ieeexplore.ieee.org
Non-invasive Visual Stimuli evoked-EEG-based P300 BCIs have gained immense attention
in recent years due to their ability to help patients with disability using BCI-controlled …
in recent years due to their ability to help patients with disability using BCI-controlled …
An interpretable convolutional neural network for P300 detection: Analysis of time frequency features for limited data
In this study, a new deep learning-based methodology is developed for P300 detection in
brain computer interface (BCI) systems based on time-frequency (TF) features of EEG …
brain computer interface (BCI) systems based on time-frequency (TF) features of EEG …
Semi-supervised learning for auditory event-related potential-based brain–computer interface
M Ogino, S Kanoga, SI Ito, Y Mitsukura - IEEE Access, 2021 - ieeexplore.ieee.org
A brain-computer interface (BCI) is a communication tool that analyzes neural activity and
relays the translated commands to carry out actions. In recent years, semi-supervised …
relays the translated commands to carry out actions. In recent years, semi-supervised …
Fusion of convolutional neural networks for P300 based character recognition
One of the most popular brain-computer interface (BCI) system is P300 speller, which is
used for character recognition. For real-time application, the improved character recognition …
used for character recognition. For real-time application, the improved character recognition …