Deep learning in fNIRS: a review
Significance: Optical neuroimaging has become a well-established clinical and research
tool to monitor cortical activations in the human brain. It is notable that outcomes of …
tool to monitor cortical activations in the human brain. It is notable that outcomes of …
A systematic review on hybrid EEG/fNIRS in brain-computer interface
As a relatively new field of neurology and computer science, brain computer interface (BCI)
has many established and burgeoning applications across scientific disciplines. Many …
has many established and burgeoning applications across scientific disciplines. Many …
[HTML][HTML] An Evaluation of the EEG alpha-to-theta and theta-to-alpha band Ratios as Indexes of Mental Workload
Many research works indicate that EEG bands, specifically the alpha and theta bands, have
been potentially helpful cognitive load indicators. However, minimal research exists to …
been potentially helpful cognitive load indicators. However, minimal research exists to …
[HTML][HTML] Analyzing classification performance of fNIRS-BCI for gait rehabilitation using deep neural networks
This research presents a brain-computer interface (BCI) framework for brain signal
classification using deep learning (DL) and machine learning (ML) approaches on functional …
classification using deep learning (DL) and machine learning (ML) approaches on functional …
[HTML][HTML] Implementation of artificial intelligence and machine learning-based methods in brain–computer interaction
Brain–computer interfaces are used for direct two-way communication between the human
brain and the computer. Brain signals contain valuable information about the mental state …
brain and the computer. Brain signals contain valuable information about the mental state …
[HTML][HTML] Brain augmentation and neuroscience technologies: current applications, challenges, ethics and future prospects
NS Jangwan, GM Ashraf, V Ram, V Singh… - Frontiers in Systems …, 2022 - frontiersin.org
Ever since the dawn of antiquity, people have strived to improve their cognitive abilities.
From the advent of the wheel to the development of artificial intelligence, technology has …
From the advent of the wheel to the development of artificial intelligence, technology has …
Basic of machine learning and deep learning in imaging for medical physicists
L Manco, N Maffei, S Strolin, S Vichi, L Bottazzi… - Physica Medica, 2021 - Elsevier
The manuscript aims at providing an overview of the published algorithms/automation tool
for artificial intelligence applied to imaging for Healthcare. A PubMed search was performed …
for artificial intelligence applied to imaging for Healthcare. A PubMed search was performed …
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 …
fNIRS classification problem has always been the focus of the brain-computer interface …
[HTML][HTML] EEG-fNIRS-based hybrid image construction and classification using CNN-LSTM
The constantly evolving human–machine interaction and advancement in sociotechnical
systems have made it essential to analyze vital human factors such as mental workload …
systems have made it essential to analyze vital human factors such as mental workload …
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 …
for monitoring cerebral hemodynamic responses. Enhancing fNIRS classification can …