Physical principles of brain–computer interfaces and their applications for rehabilitation, robotics and control of human brain states
Brain–computer interfaces (BCIs) development is closely related to physics. In this paper, we
review the physical principles of BCIs, and underlying novel approaches for registration …
review the physical principles of BCIs, and underlying novel approaches for registration …
[HTML][HTML] fNIRS-based brain-computer interfaces: a review
A brain-computer interface (BCI) is a communication system that allows the use of brain
activity to control computers or other external devices. It can, by bypassing the peripheral …
activity to control computers or other external devices. It can, by bypassing the peripheral …
A deep transfer convolutional neural network framework for EEG signal classification
Nowadays, motor imagery (MI) electroencephalogram (EEG) signal classification has
become a hotspot in the research field of brain computer interface (BCI). More recently, deep …
become a hotspot in the research field of brain computer interface (BCI). More recently, deep …
[HTML][HTML] Sleep stage classification using EEG signal analysis: a comprehensive survey and new investigation
Sleep specialists often conduct manual sleep stage scoring by visually inspecting the
patient's neurophysiological signals collected at sleep labs. This is, generally, a very difficult …
patient's neurophysiological signals collected at sleep labs. This is, generally, a very difficult …
[HTML][HTML] Feature extraction and classification methods for hybrid fNIRS-EEG brain-computer interfaces
In this study, a brain-computer interface (BCI) framework for hybrid functional near-infrared
spectroscopy (fNIRS) and electroencephalography (EEG) for locked-in syndrome (LIS) …
spectroscopy (fNIRS) and electroencephalography (EEG) for locked-in syndrome (LIS) …
[HTML][HTML] Hybrid brain–computer interface techniques for improved classification accuracy and increased number of commands: a review
In this paper, hybrid brain-computer interface (hBCI) technologies for improving
classification accuracy and increasing the number of commands are reviewed. Hybridization …
classification accuracy and increasing the number of commands are reviewed. Hybridization …
[HTML][HTML] Measuring mental workload with EEG+ fNIRS
We studied the capability of a Hybrid functional neuroimaging technique to quantify human
mental workload (MWL). We have used electroencephalography (EEG) and functional near …
mental workload (MWL). We have used electroencephalography (EEG) and functional near …
[HTML][HTML] Hybrid EEG–fNIRS-based eight-command decoding for BCI: application to quadcopter control
In this paper, a hybrid electroencephalography–functional near-infrared spectroscopy (EEG–
fNIRS) scheme to decode eight active brain commands from the frontal brain region for brain …
fNIRS) scheme to decode eight active brain commands from the frontal brain region for brain …
Classification of prefrontal and motor cortex signals for three-class fNIRS–BCI
Functional near-infrared spectroscopy (fNIRS) is an optical imaging method that can be
used for a brain-computer interface (BCI). In the present study, we concurrently measure and …
used for a brain-computer interface (BCI). In the present study, we concurrently measure and …
[HTML][HTML] Decoding of four movement directions using hybrid NIRS-EEG brain-computer interface
The hybrid brain-computer interface (BCI)'s multimodal technology enables precision brain-
signal classification that can be used in the formulation of control commands. In the present …
signal classification that can be used in the formulation of control commands. In the present …