EEG-Based Motor BCIs for Upper Limb Movement: Current Techniques and Future Insights
Motor brain-computer interface (BCI) refers to the BCI that decodes voluntary motion
intentions from brain signals directly and outputs corresponding control commands without …
intentions from brain signals directly and outputs corresponding control commands without …
A comprehensive review on motion trajectory reconstruction for EEG-based brain-computer interface
The advance in neuroscience and computer technology over the past decades have made
brain-computer interface (BCI) a most promising area of neurorehabilitation and …
brain-computer interface (BCI) a most promising area of neurorehabilitation and …
Source aware deep learning framework for hand kinematic reconstruction using EEG signal
The ability to reconstruct the kinematic parameters of hand movement using noninvasive
electroencephalography (EEG) is essential for strength and endurance augmentation using …
electroencephalography (EEG) is essential for strength and endurance augmentation using …
Decoding imagined 3D hand movement trajectories from EEG: evidence to support the use of mu, beta, and low gamma oscillations
Objective: To date, motion trajectory prediction (MTP) of a limb from non-invasive
electroencephalography (EEG) has relied, primarily, on band-pass filtered samples of EEG …
electroencephalography (EEG) has relied, primarily, on band-pass filtered samples of EEG …
Distance-and speed-informed kinematics decoding improves M/EEG based upper-limb movement decoder accuracy
Objective. One of the main goals in brain–computer interface (BCI) research is the
replacement or restoration of lost function in individuals with paralysis. One line of research …
replacement or restoration of lost function in individuals with paralysis. One line of research …
Decoding lower-limb kinematic parameters during pedaling tasks using deep learning approaches and EEG
CF Blanco-Diaz, CD Guerrero-Mendez… - Medical & Biological …, 2024 - Springer
Stroke is a neurological condition that usually results in the loss of voluntary control of body
movements, making it difficult for individuals to perform activities of daily living (ADLs). Brain …
movements, making it difficult for individuals to perform activities of daily living (ADLs). Brain …
Masked and unmasked error-related potentials during continuous control and feedback
C Lopes Dias, AI Sburlea… - Journal of neural …, 2018 - iopscience.iop.org
The detection of error-related potentials (ErrPs) in tasks with discrete feedback is well
established in the brain–computer interface (BCI) field. However, the decoding of ErrPs in …
established in the brain–computer interface (BCI) field. However, the decoding of ErrPs in …
EEG-based continuous hand movement decoding using improved center-out paradigm
The continuous decoding of human movement intention based on electroencephalogram
(EEG) signals is valuable for developing a more natural motor augmented or assistive …
(EEG) signals is valuable for developing a more natural motor augmented or assistive …
Subject-independent trajectory prediction using pre-movement EEG during grasp and lift task
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 …
computer interface (BCI) systems has been an active area of research. The systems include …
Use of mobile EEG in decoding hand movement speed and position
N Robinson, TWJ Chester… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
With the majority of brain–computer interface (BCI) research currently restricted to the
controlled settings in labs, there is a growing interest to study the feasibility of BCI …
controlled settings in labs, there is a growing interest to study the feasibility of BCI …