Results 21 to 30 of about 1,732,367 (353)
Evaluation of EEG oscillatory patterns and cognitive process during simple and compound limb motor imagery. [PDF]
PLoS ONE, 2014 Motor imagery (MI), sharing similar neural representations to motor execution, is regarded as a window to investigate the cognitive motor processes. However, in comparison to simple limb motor imagery, significantly less work has been reported on brain ...
Weibo Yi +7 more
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A large EEG dataset for studying cross-session variability in motor imagery brain-computer interface
Scientific Data, 2022 In building a practical and robust brain-computer interface (BCI), the classification of motor imagery (MI) from electroencephalography (EEG) across multiple days is a long-standing challenge due to the large variability of the EEG signals.
Jun Ma +5 more
semanticscholar +1 more source
Italian National Conference on Sensors, 2021 Motor imagery (MI) based brain–computer interface (BCI) aims to provide a means of communication through the utilization of neural activity generated due to kinesthetic imagination of limbs.
Amardeep Singh +3 more
semanticscholar +1 more source
EEG-TCNet: An Accurate Temporal Convolutional Network for Embedded Motor-Imagery Brain–Machine Interfaces [PDF]
IEEE International Conference on Systems, Man and Cybernetics, 2020 In recent years, deep learning (DL) has contributed significantly to the improvement of motor-imagery brain–machine interfaces (MI-BMIs) based on electroencephalography (EEG).
T. Ingolfsson +5 more
semanticscholar +1 more source
Motor experience with a sport-specific implement affects motor imagery [PDF]
PeerJ, 2018 The present study tested whether sport-specific implements facilitate motor imagery, whereas nonspecific implements disrupt motor imagery. We asked a group of basketball players (experts) and a group of healthy controls (novices) to physically perform ...
Lanlan Zhang +5 more
doaj +2 more sources
Questioning the transfer effect of motor imagery benefits: The neglected variable of interest
Asian Journal of Sport and Exercise Psychology, 2022 Over the last three decades, a large amount of experimental research aimed at determining the optimal motor imagery practice guidelines, and provided a comprehensive overview of the main recommendations to develop effective interventions.
Aymeric Guillot +3 more
doaj +1 more source
Advanced TSGL-EEGNet for Motor Imagery EEG-Based Brain-Computer Interfaces
IEEE Access, 2021 Deep learning technology is rapidly spreading in recent years and has been extensive attempts in the field of Brain-Computer Interface (BCI). Though the accuracy of Motor Imagery (MI) BCI systems based on the deep learning have been greatly improved ...
Xin Deng +4 more
semanticscholar +1 more source
Learning Common Time-Frequency-Spatial Patterns for Motor Imagery Classification
IEEE transactions on neural systems and rehabilitation engineering, 2021 The common spatial patterns (CSP) algorithm is the most popular spatial filtering method applied to extract electroencephalogram (EEG) features for motor imagery (MI) based brain-computer interface (BCI) systems.
Yangyang Miao +6 more
semanticscholar +1 more source
Multiattention Adaptation Network for Motor Imagery Recognition
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022 Brain–computer interface (BCI) based on motor imagery electroencephalogram (EEG) has been widely used in various applications. Despite the previous efforts, the remained major challenges are effective feature extraction and the time-consuming calibration
Peiyin Chen +5 more
semanticscholar +1 more source
Selective effect of physical fatigue on motor imagery accuracy. [PDF]
PLoS ONE, 2012 While the use of motor imagery (the mental representation of an action without overt execution) during actual training sessions is usually recommended, experimental studies examining the effect of physical fatigue on subsequent motor imagery performance ...
Franck Di Rienzo +3 more
doaj +1 more source