Application of continuous wavelet transform and convolutional neural network in decoding motor imagery brain-computer interface
HK Lee, YS Choi - Entropy, 2019 - mdpi.com
The motor imagery-based brain-computer interface (BCI) using electroencephalography
(EEG) has been receiving attention from neural engineering researchers and is being …
(EEG) has been receiving attention from neural engineering researchers and is being …
[HTML][HTML] EEG decoding method based on multi-feature information fusion for spinal cord injury
F Xu, J Li, G Dong, J Li, X Chen, J Zhu, J Hu, Y Zhang… - Neural Networks, 2022 - Elsevier
To develop an efficient brain–computer interface (BCI) system, electroencephalography
(EEG) measures neuronal activities in different brain regions through electrodes. Many EEG …
(EEG) measures neuronal activities in different brain regions through electrodes. Many EEG …
A systematic rank of smart training environment applications with motor imagery brain-computer interface
Abstract Brain-Computer Interface (BCI) research is considered one of the significant
interdisciplinary fields. It assists people with severe motor disabilities to recover and improve …
interdisciplinary fields. It assists people with severe motor disabilities to recover and improve …
Multiclass classification of spatially filtered motor imagery EEG signals using convolutional neural network for BCI based applications
N Shajil, S Mohan, P Srinivasan… - Journal of Medical and …, 2020 - Springer
Abstract Purpose Brain–Computer Interface (BCI) system offers a new means of
communication for those with paralysis or severe neuromuscular disorders. BCI systems …
communication for those with paralysis or severe neuromuscular disorders. BCI systems …
An automatic channel selection method based on the standard deviation of wavelet coefficients for motor imagery based brain–computer interfacing
The redundant data in multichannel electroencephalogram (EEG) signals significantly
reduces the performance of brain–computer interface (BCI) systems. By removing redundant …
reduces the performance of brain–computer interface (BCI) systems. By removing redundant …
Motor memory in HCI
There is mounting evidence acknowledging that embodiment is foundational to cognition. In
HCI, this understanding has been incorporated in concepts like embodied interaction, bodily …
HCI, this understanding has been incorporated in concepts like embodied interaction, bodily …
EEG signal processing in MI-BCI applications with improved covariance matrix estimators
In brain–computer interfaces (BCIs), the typical models of the EEG observations usually lead
to a poor estimation of the trial covariance matrices, given the high non-stationarity of the …
to a poor estimation of the trial covariance matrices, given the high non-stationarity of the …
[HTML][HTML] Meta-eeg: Meta-learning-based class-relevant eeg representation learning for zero-calibration brain–computer interfaces
Transfer learning for motor imagery-based brain–computer interfaces (MI-BCIs) struggles
with inter-subject variability, hindering its generalization to new users. This paper proposes …
with inter-subject variability, hindering its generalization to new users. This paper proposes …
Channel selection based similarity measurement for motor imagery classification
S Chen, Y Sun, H Wang, Z Pang - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
Because of the redundant information contained in the EEG signals, the classification
accuracy of motor imagery may be greatly reduced. The channel selection method helps to …
accuracy of motor imagery may be greatly reduced. The channel selection method helps to …
Surface electromyography and electroencephalogram-based gait phase recognition and correlations between cortical and locomotor muscle in the seven gait phases
P Wei, J Zhang, B Wang, J Hong - Frontiers in Neuroscience, 2021 - frontiersin.org
The classification of gait phases based on surface electromyography (sEMG) and
electroencephalogram (EEG) can be used to the control systems of lower limb exoskeletons …
electroencephalogram (EEG) can be used to the control systems of lower limb exoskeletons …