Physical principles of brain–computer interfaces and their applications for rehabilitation, robotics and control of human brain states

AE Hramov, VA Maksimenko, AN Pisarchik - Physics Reports, 2021 - Elsevier
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 …

[HTML][HTML] fNIRS-based brain-computer interfaces: a review

N Naseer, KS Hong - Frontiers in human neuroscience, 2015 - frontiersin.org
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 …

[HTML][HTML] Feature extraction and classification methods for hybrid fNIRS-EEG brain-computer interfaces

KS Hong, MJ Khan, MJ Hong - Frontiers in human neuroscience, 2018 - frontiersin.org
In this study, a brain-computer interface (BCI) framework for hybrid functional near-infrared
spectroscopy (fNIRS) and electroencephalography (EEG) for locked-in syndrome (LIS) …

Mental stress assessment using simultaneous measurement of EEG and fNIRS

F Al-Shargie, M Kiguchi, N Badruddin… - Biomedical optics …, 2016 - opg.optica.org
Previous studies reported mental stress as one of the major contributing factors leading to
various diseases such as heart attack, depression and stroke. An accurate stress …

Classification of prefrontal and motor cortex signals for three-class fNIRS–BCI

KS Hong, N Naseer, YH Kim - Neuroscience letters, 2015 - Elsevier
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 …

[HTML][HTML] Decoding of four movement directions using hybrid NIRS-EEG brain-computer interface

MJ Khan, MJ Hong, KS Hong - Frontiers in human neuroscience, 2014 - frontiersin.org
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 …

Classification of functional near-infrared spectroscopy signals corresponding to the right-and left-wrist motor imagery for development of a brain–computer interface

N Naseer, KS Hong - Neuroscience letters, 2013 - Elsevier
This paper presents a study on functional near-infrared spectroscopy (fNIRS) indicating that
the hemodynamic responses of the right-and left-wrist motor imageries have distinct patterns …

Open access dataset for EEG+ NIRS single-trial classification

J Shin, A von Lühmann, B Blankertz… - … on Neural Systems …, 2016 - ieeexplore.ieee.org
We provide an open access dataset for hybrid brain-computer interfaces (BCIs) using
electroencephalography (EEG) and near-infrared spectroscopy (NIRS). For this, we …

[HTML][HTML] Enhanced accuracy for multiclass mental workload detection using long short-term memory for brain–computer interface

U Asgher, K Khalil, MJ Khan, R Ahmad, SI Butt… - Frontiers in …, 2020 - frontiersin.org
Cognitive workload is one of the widely invoked human factors in the areas of human–
machine interaction (HMI) and neuroergonomics. The precise assessment of cognitive and …

[HTML][HTML] Determining optimal feature-combination for LDA classification of functional near-infrared spectroscopy signals in brain-computer interface application

N Naseer, FM Noori, NK Qureshi… - Frontiers in human …, 2016 - frontiersin.org
In this study, we determine the optimal feature-combination for classification of functional
near-infrared spectroscopy (fNIRS) signals with the best accuracies for development of a two …