Intra-and inter-subject variability in EEG-based sensorimotor brain computer interface: a review
Brain computer interfaces (BCI) for the rehabilitation of motor impairments exploit
sensorimotor rhythms (SMR) in the electroencephalogram (EEG). However, the …
sensorimotor rhythms (SMR) in the electroencephalogram (EEG). However, the …
Strategies for interface issues and challenges of neural electrodes
C Liang, Y Liu, W Lu, G Tian, Q Zhao, D Yang, J Sun… - Nanoscale, 2022 - pubs.rsc.org
Neural electrodes, as a bridge for bidirectional communication between the body and
external devices, are crucial means for detecting and controlling nerve activity. The …
external devices, are crucial means for detecting and controlling nerve activity. The …
Golden subject is everyone: A subject transfer neural network for motor imagery-based brain computer interfaces
Electroencephalographic measurement of cortical activity subserving motor behavior varies
among different individuals, restricting the potential of brain computer interfaces (BCIs) …
among different individuals, restricting the potential of brain computer interfaces (BCIs) …
Differentiation of schizophrenia by combining the spatial EEG brain network patterns of rest and task P300
The P300 is regarded as a psychosis endophenotype of schizophrenia and a putative
biomarker of risk for schizophrenia. However, the brain activity (ie, P300 amplitude) during …
biomarker of risk for schizophrenia. However, the brain activity (ie, P300 amplitude) during …
Hybrid EEG-fNIRS brain computer interface based on common spatial pattern by using EEG-informed general linear model
Hybrid brain–computer interfaces (BCI) utilizing the high temporal resolution of
electroencephalography (EEG) and the high spatial resolution of functional near-infrared …
electroencephalography (EEG) and the high spatial resolution of functional near-infrared …
The dynamic brain networks of motor imagery: time-varying causality analysis of scalp EEG
Motor imagery (MI) requires subjects to visualize the requested motor behaviors, which
involves a large-scale network that spans multiple brain areas. The corresponding cortical …
involves a large-scale network that spans multiple brain areas. The corresponding cortical …
Improving performance in motor imagery BCI-based control applications via virtually embodied feedback
JW Choi, S Huh, S Jo - Computers in Biology and Medicine, 2020 - Elsevier
Abstract Objective Brain-computer interfaces (BCIs) based on motor imagery (MI) are
commonly used for control applications. However, these applications require strong and …
commonly used for control applications. However, these applications require strong and …
[HTML][HTML] Predicting individual decision-making responses based on single-trial EEG
Decision-making plays an essential role in the interpersonal interactions and cognitive
processing of individuals. There has been increasing interest in being able to predict an …
processing of individuals. There has been increasing interest in being able to predict an …
Predicting motor imagery performance from resting-state EEG using dynamic causal modeling
M Lee, JG Yoon, SW Lee - Frontiers in human neuroscience, 2020 - frontiersin.org
Motor imagery-based brain–computer interfaces (MI-BCIs) send commands to a computer
using the brain activity registered when a subject imagines—but does not perform—a given …
using the brain activity registered when a subject imagines—but does not perform—a given …
[HTML][HTML] Inter-subject P300 variability relates to the efficiency of brain networks reconfigured from resting-to task-state: evidence from a simultaneous event-related …
The P300 event-related potential (ERP) varies across individuals, and exploring this
variability deepens our knowledge of the event, and scope for its potential applications …
variability deepens our knowledge of the event, and scope for its potential applications …