Implementing a fuzzy inference system in a multi-objective EEG channel selection model for imagined speech classification
AA Torres-García, CA Reyes-García… - Expert Systems with …, 2016 - Elsevier
One of the main purposes of brain-computer interfaces (BCI) is to provide persons of an
alternative communication channel. This objective was firstly focused on handicapped …
alternative communication channel. This objective was firstly focused on handicapped …
PSO-based dimension reduction of EEG recordings: implications for subject transfer in BCI
Subject transfer is a growing area of research in EEG aiming to address the lack of having
enough EEG samples required for BCI by using samples originating from individuals or …
enough EEG samples required for BCI by using samples originating from individuals or …
Dimension reduction in EEG data using particle swarm optimization
EEG data contains high-dimensional data that requires considerable computational power
for distinguishing different classes. Dimension reduction is commonly used to reduces the …
for distinguishing different classes. Dimension reduction is commonly used to reduces the …
Dimension reduction using new bond graph algorithm and deep learning pooling on EEG signals for BCI
A Naebi, Z Feng, F Hosseinpour, G Abdollahi - Applied Sciences, 2021 - mdpi.com
One of the main challenges in studying brain signals is the large size of the data due to the
use of many electrodes and the time-consuming sampling. Choosing the right dimensional …
use of many electrodes and the time-consuming sampling. Choosing the right dimensional …
Channel selection using glow swarm optimization and its application in line of sight secure communication
A Franklin Alex Joseph, C Govindaraju - Cluster Computing, 2019 - Springer
The brain computer interfaces (BCI), that are also known as brain machine interfaces or
sometimes neural interface systems have a pathway of direct communication between a …
sometimes neural interface systems have a pathway of direct communication between a …
Evolutionary multitasking-based multiobjective optimization algorithm for channel selection in hybrid brain computer interfacing systems
T Liu, Z Xu, L Cao, G Tan - Frontiers in Neuroscience, 2021 - frontiersin.org
Hybrid-modality brain-computer Interfaces (BCIs), which combine motor imagery (MI) bio-
signals and steady-state visual evoked potentials (SSVEPs), has attracted wide attention in …
signals and steady-state visual evoked potentials (SSVEPs), has attracted wide attention in …
The impact of PSO based dimension reduction on EEG classification
The high dimensional nature of EEG data due to large electrode numbers and long task
periods is one of the main challenges of studying EEG. Evolutionary alternatives to …
periods is one of the main challenges of studying EEG. Evolutionary alternatives to …
Adapting subject-independent task-specific EEG feature masks using PSO
Dimension reduction is an important step toward asynchronous EEG based BCI systems,
with EA based Feature/Electrode Reduction (FR/ER) methods showing significant potential …
with EA based Feature/Electrode Reduction (FR/ER) methods showing significant potential …
Multi-objective optimisation of cancer chemotherapy using smart pso with decomposition
N Al Moubayed, A Petrovski… - 2011 IEEE Symposium on …, 2011 - ieeexplore.ieee.org
The paper presents a novel approach to optimising cancer chemotherapy with respect to
conflicting treatment objectives aimed at reducing the number of cancerous cells and at …
conflicting treatment objectives aimed at reducing the number of cancerous cells and at …
Optimizing the number of electrodes and spatial filters for Brain–Computer Interfaces by means of an evolutionary multi-objective approach
Obtaining high accuracy classification from Brain Computer Interfaces require to attach
many electrodes on the scalp of subjects. On the other hand, their placement on the scalp …
many electrodes on the scalp of subjects. On the other hand, their placement on the scalp …