Algorithm contest of motor imagery BCI in the world robot contest 2022: a survey
J An, X Chen, D Wu - Brain Science Advances, 2023 - journals.sagepub.com
From August 19 to 21, 2022, the BCI Controlled Robot Contest finals in the World Robot
Contest 2022 were held in Beijing, China. Fifteen teams participated in the finals in the …
Contest 2022 were held in Beijing, China. Fifteen teams participated in the finals in the …
[HTML][HTML] Robustly effective approaches on motor imagery-based brain computer interfaces
SS Moumgiakmas, GA Papakostas - Computers, 2022 - mdpi.com
Motor Imagery Brain Computer Interfaces (MI-BCIs) are systems that receive the users' brain
activity as an input signal in order to communicate between the brain and the interface or an …
activity as an input signal in order to communicate between the brain and the interface or an …
[HTML][HTML] Decoding EEG rhythms offline and online during motor imagery for standing and sitting based on a brain-computer interface
N Triana-Guzman, AD Orjuela-Cañon… - Frontiers in …, 2022 - frontiersin.org
Motor imagery (MI)-based brain-computer interface (BCI) systems have shown promising
advances for lower limb motor rehabilitation. The purpose of this study was to develop an MI …
advances for lower limb motor rehabilitation. The purpose of this study was to develop an MI …
Brain-computer integration: A framework for the design of brain-computer interfaces from an integrations perspective
Brain-computer interface (BCI) systems hold the potential to foster human flourishing and
self-actualization. However, we believe contemporary BCI system design approaches …
self-actualization. However, we believe contemporary BCI system design approaches …
State-of-the-art versus deep learning: A comparative study of motor imagery decoding techniques
State-of-the-art techniques (SOTA) for motor imagery decoding have largely involved the
use of common spatial patterns (CSP) and power spectral density (PSD), for feature …
use of common spatial patterns (CSP) and power spectral density (PSD), for feature …
DSFE: Decoding EEG-based finger motor imagery using feature-dependent frequency, feature fusion and ensemble learning
Accurate decoding finger motor imagery is essential for fine motor control using EEG
signals. However, decoding finger motor imagery is particularly challenging compared with …
signals. However, decoding finger motor imagery is particularly challenging compared with …
Decoding Multi-Brain Motor Imagery From EEG Using Coupling Feature Extraction and Few-Shot Learning
Electroencephalography (EEG)-based motor imagery (MI) is one of brain computer interface
(BCI) paradigms, which aims to build a direct communication pathway between human brain …
(BCI) paradigms, which aims to build a direct communication pathway between human brain …
Improved Motor Imagery EEG Inter-device Decoding by Reweighting Multi-source Domain Samples
B Fu, F Li, Y Ji, Y Li, X Xie, X Li… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Electroencephalogram (EEG)-based motor imagery brain-computer interface (MI BCI) has
exciting prospects in applications. Multisource domain problem of MI EEG decoding needs …
exciting prospects in applications. Multisource domain problem of MI EEG decoding needs …
A Cloud-based IoT-enabled framework for BCI applications
The interplay of brain signals and the Internet of Things (IoT) is an emerging area. The
processing of electroencephalographic (EEG) signals is mainly divided into two …
processing of electroencephalographic (EEG) signals is mainly divided into two …
Improved motor imagery decoding using deep learning techniques
O George - 2021 - search.proquest.com
Motor imagery (MI) has been one of the most used paradigms for building brain-computer
interfaces (BCI), widely used in neurorehabilitation, for restoring functionality to damaged …
interfaces (BCI), widely used in neurorehabilitation, for restoring functionality to damaged …