CGAN-rIRN: a data-augmented deep learning approach to accurate classification of mental tasks for a fNIRS-based brain-computer interface

Y Zhang, D Liu, T Li, P Zhang, Z Li… - Biomedical optics express, 2023 - opg.optica.org
Functional near-infrared spectroscopy (fNIRS) is increasingly used to investigate different
mental tasks for brain-computer interface (BCI) control due to its excellent environmental …

Brain-computer interface using deep neural network and its application to mobile robot control

G Huve, K Takahashi… - 2018 IEEE 15th …, 2018 - ieeexplore.ieee.org
Functional near-infrared spectroscopic (fNIRS) systems have recently attracted considerable
attention for their potential in the domain of brain-computer interfaces (BCIs). This study …

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

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 …

Novel fNIRS study on homogeneous symmetric feature-based transfer learning for brain–computer interface

K Khalil, U Asgher, Y Ayaz - Scientific reports, 2022 - nature.com
The brain–computer interface (BCI) provides an alternate means of communication between
the brain and external devices by recognizing the brain activities and translating them into …

Enhancing Classification Accuracy with Integrated Contextual Gate Network: Deep Learning Approach for Functional Near-Infrared Spectroscopy Brain–Computer …

J Akhter, N Naseer, H Nazeer, H Khan, P Mirtaheri - Sensors, 2024 - mdpi.com
Brain–computer interface (BCI) systems include signal acquisition, preprocessing, feature
extraction, classification, and an application phase. In fNIRS-BCI systems, deep learning …

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 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 …

Comparison of machine learning approaches for motor imagery based optical brain computer interface

L Wang, A Curtin, H Ayaz - … and Cognitive Engineering: Proceedings of the …, 2019 - Springer
Abstract A Brain-computer Interface (BCI) is a system that interprets specific patterns in
human brain activity, such as the intention to perform motor functions, in order to generate a …

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 …

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 …