A general and scalable vision framework for functional near-infrared spectroscopy classification

Z Wang, J Zhang, Y Xia, P Chen… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Functional near-infrared spectroscopy (fNIRS), a non-invasive optical technique, is widely
used to monitor brain activities for disease diagnosis and brain-computer interfaces (BCIs) …

Transformer model for functional near-infrared spectroscopy classification

Z Wang, J Zhang, X Zhang, P Chen… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Functional near-infrared spectroscopy (fNIRS) is a promising neuroimaging technology. The
fNIRS classification problem has always been the focus of the brain-computer interface …

Rethinking delayed hemodynamic responses for fNIRS classification

Z Wang, J Fang, J Zhang - IEEE Transactions on Neural …, 2023 - ieeexplore.ieee.org
Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging technology
for monitoring cerebral hemodynamic responses. Enhancing fNIRS classification can …

[HTML][HTML] Combining robust level extraction and unsupervised adaptive classification for high-accuracy fNIRS-BCI: An evidence on single-trial differentiation between …

Y Zhang, D Liu, P Zhang, T Li, Z Li, F Gao - Frontiers in neuroscience, 2022 - frontiersin.org
Functional near-infrared spectroscopy (fNIRS) is a safe and non-invasive optical imaging
technique that is being increasingly used in brain-computer interfaces (BCIs) to recognize …

Improving fNIRS-BCI accuracy using GAN-based data augmentation

T Nagasawa, T Sato, I Nambu… - 2019 9th International …, 2019 - ieeexplore.ieee.org
Functional near-infrared spectroscopy (fNIRS) is expected to be applied to the brain-
computer interface (BCI). Since a lengthy fNIRS measurement is uncomfortable for the …

Classification algorithm for fNIRS-based brain signals using convolutional neural network with spatiotemporal feature extraction mechanism

Y Qin, B Li, W Wang, X Shi, C Peng, Y Lu - Neuroscience, 2024 - Elsevier
Abstract Brain Computer Interface (BCI) is a highly promising human–computer interaction
method that can utilize brain signals to control external devices. BCI based on functional …

[HTML][HTML] Subject-independent functional near-infrared spectroscopy-based brain–computer interfaces based on convolutional neural networks

J Kwon, CH Im - Frontiers in human neuroscience, 2021 - frontiersin.org
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 …

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] Explainable artificial intelligence model to predict brain states from fNIRS signals

CJ Shibu, S Sreedharan, KM Arun… - Frontiers in Human …, 2023 - frontiersin.org
Objective: Most Deep Learning (DL) methods for the classification of functional Near-Infrared
Spectroscopy (fNIRS) signals do so without explaining which features contribute to the …

Classification of fNIRS data under uncertainty: A Bayesian neural network approach

T Siddique, MS Mahmud - 2020 IEEE International Conference …, 2021 - ieeexplore.ieee.org
Functional Near-Infrared Spectroscopy (fNIRS) is a non-invasive form of Brain-Computer
Interface (BCI). It is used for the imaging of brain hemodynamics and has gained popularity …