Results 21 to 30 of about 1,737,485 (397)
Diagnostics, 2022 Electroencephalography-based motor imagery (EEG-MI) classification is a critical component of the brain-computer interface (BCI), which enables people with physical limitations to communicate with the outside world via assistive technology.
G. Altuwaijri +3 more
semanticscholar +1 more source
A Sliding Window Common Spatial Pattern for Enhancing Motor Imagery Classification in EEG-BCI
IEEE Transactions on Instrumentation and Measurement, 2021 Accurate binary classification of electroencephalography (EEG) signals is a challenging task for the development of motor imagery (MI) brain–computer interface (BCI) systems. In this study, two sliding window techniques are proposed to enhance the binary
Pramod Gaur +5 more
semanticscholar +1 more source
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
doaj +1 more source
Relationship between Corticospinal Excitability While Gazing at the Mirror and Motor Imagery Ability
Brain Sciences, 2023 Mirror therapy (MT) helps stroke survivors recover motor function. Previous studies have reported that an individual’s motor imagery ability is related to the areas of brain activity during motor imagery and the effectiveness of motor imagery training ...
Jun Iwanami +4 more
doaj +1 more source
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
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
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
Stabilometric Correlates of Motor and Motor Imagery Expertise [PDF]
Frontiers in Human Neuroscience, 2022 Motor Imagery (MI) reproduces cognitive operations associated with the actual motor preparation and execution. Postural recordings during MI reflect somatic motor commands targeting peripheral effectors involved in balance control. However, how these relate to the actual motor expertise and may vary along with the MI modality remains debated.
Franck Di Rienzo +7 more
openaire +3 more sources
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