Hybrid EEG-fNIRS brain computer interface based on common spatial pattern by using EEG-informed general linear model
Hybrid brain–computer interfaces (BCI) utilizing the high temporal resolution of
electroencephalography (EEG) and the high spatial resolution of functional near-infrared …
electroencephalography (EEG) and the high spatial resolution of functional near-infrared …
A brain-computer interface based on a few-channel EEG-fNIRS bimodal system
S Ge, Q Yang, R Wang, P Lin, J Gao, Y Leng… - IEEE …, 2017 - ieeexplore.ieee.org
With the development of the wearable brain-computer interface (BCI), a few-channel BCI
system is necessary for its application to daily life. In this paper, we proposed a bimodal BCI …
system is necessary for its application to daily life. In this paper, we proposed a bimodal BCI …
A Computationally Efficient Method for Hybrid EEG‐fNIRS BCI Based on the Pearson Correlation
A hybrid brain computer interface (BCI) system considered here is a combination of
electroencephalography (EEG) and functional near‐infrared spectroscopy (fNIRS). EEG …
electroencephalography (EEG) and functional near‐infrared spectroscopy (fNIRS). EEG …
[HTML][HTML] Enhancing performance of a hybrid EEG-fNIRS system using channel selection and early temporal features
Brain-Computer Interface (BCI) techniques hold a great promise for neuroprosthetic
applications. A desirable BCI system should be portable, minimally invasive, and feature …
applications. A desirable BCI system should be portable, minimally invasive, and feature …
[HTML][HTML] Improved classification performance of EEG-fNIRS multimodal brain-computer interface based on multi-domain features and multi-level progressive learning
Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) have
potentially complementary characteristics that reflect the electrical and hemodynamic …
potentially complementary characteristics that reflect the electrical and hemodynamic …
[HTML][HTML] Random subspace ensemble learning for functional near-infrared spectroscopy brain-computer interfaces
J Shin - Frontiers in human neuroscience, 2020 - frontiersin.org
The feasibility of the random subspace ensemble learning method was explored to improve
the performance of functional near-infrared spectroscopy-based brain-computer interfaces …
the performance of functional near-infrared spectroscopy-based brain-computer interfaces …
[HTML][HTML] Subject-independent functional near-infrared spectroscopy-based brain–computer interfaces based on convolutional neural networks
Functional near-infrared spectroscopy (fNIRS) has attracted increasing attention in the field
of brain–computer interfaces (BCIs) owing to their advantages such as non-invasiveness …
of brain–computer interfaces (BCIs) owing to their advantages such as non-invasiveness …
[HTML][HTML] Hybrid EEG-fNIRS brain-computer interface based on the non-linear features extraction and stacking ensemble learning
The Brain-computer interface (BCI) is used to enhance the human capabilities. The hybrid-
BCI (hBCI) is a novel concept for subtly hybridizing multiple monitoring schemes to …
BCI (hBCI) is a novel concept for subtly hybridizing multiple monitoring schemes to …
Correlation-filter-based channel and feature selection framework for hybrid EEG-fNIRS BCI applications
The proposed study is based on a feature and channel selection strategy that uses
correlation filters for brain–computer interface (BCI) applications using …
correlation filters for brain–computer interface (BCI) applications using …
[HTML][HTML] An effective classification framework for brain-computer interface system design based on combining of fNIRS and EEG signals
A Alhudhaif - PeerJ Computer Science, 2021 - peerj.com
Background The brain-computer interface (BCI) is a relatively new but highly promising
special field that is actively used in basic neuroscience. BCI includes interfaces for human …
special field that is actively used in basic neuroscience. BCI includes interfaces for human …
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