EEG-Based Motor BCIs for Upper Limb Movement: Current Techniques and Future Insights

J Wang, L Bi, W Fei - IEEE Transactions on Neural Systems and …, 2023 - ieeexplore.ieee.org
Motor brain-computer interface (BCI) refers to the BCI that decodes voluntary motion
intentions from brain signals directly and outputs corresponding control commands without …

Motor imagery hand movement direction decoding using brain computer interface to aid stroke recovery and rehabilitation

VK Benzy, AP Vinod, R Subasree… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Motor Imagery (MI)-based Brain Computer Interface (BCI) system is a potential technology
for active neurorehabilitation of stroke patients by complementing the conventional passive …

Decoding single-hand and both-hand movement directions from noninvasive neural signals

J Wang, L Bi, W Fei, C Guan - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Decoding human movement parameters from electroencephalograms (EEG) signals is of
great value for human-machine collaboration. However, existing studies on hand movement …

State-based decoding of continuous hand movements using EEG signals

SM Hosseini, V Shalchyan - IEEE Access, 2023 - ieeexplore.ieee.org
Recently, the advent of the non-invasive brain-computer interface (BCI) for continuous
decoding of upper limb motions opens a new horizon for motor-disabled people. However …

High accuracy decoding of motor imagery directions from EEG-based brain computer interface using filter bank spatially regularised common spatial pattern method

P Rithwik, VK Benzy, AP Vinod - Biomedical Signal Processing and Control, 2022 - Elsevier
One of the important requirements of a practical Brain Computer Interface (BCI) system is the
ability to establish multiple control commands corresponding to different kinematics of motor …

EEG-based continuous hand movement decoding using improved center-out paradigm

J Wang, L Bi, W Fei, K Tian - IEEE Transactions on Neural …, 2022 - ieeexplore.ieee.org
The continuous decoding of human movement intention based on electroencephalogram
(EEG) signals is valuable for developing a more natural motor augmented or assistive …

Investigating the application of graph theory features in hand movement directions decoding using EEG signals

SM Hosseini, AH Aminitabar, V Shalchyan - Neuroscience Research, 2023 - Elsevier
In recent years, functional analysis of brain networks based on graph theory properties has
attracted considerable attention. This approach has usually been exploited for structural and …

Decoding coordinated directions of bimanual movements from EEG signals

M Zhang, J Wu, J Song, R Fu, R Ma… - … on Neural Systems …, 2022 - ieeexplore.ieee.org
Bimanual coordination is common in human daily life, whereas current research focused
mainly on decoding unimanual movement from electroencephalogram (EEG) signals. Here …

Decoding multi-class EEG signals of hand movement using multivariate empirical mode decomposition and convolutional neural network

Y Tao, W Xu, G Wang, Z Yuan, M Wang… - … on Neural Systems …, 2022 - ieeexplore.ieee.org
Brain-computer interface (BCI) is a technology that connects the human brain and external
devices. Many studies have shown the possibility of using it to restore motor control in stroke …

Subject-independent trajectory prediction using pre-movement EEG during grasp and lift task

A Jain, L Kumar - Biomedical Signal Processing and Control, 2023 - Elsevier
Electroencephalogram (EEG) based motor trajectory decoding for efficient control of brain–
computer interface (BCI) systems has been an active area of research. The systems include …