Functional near-infrared spectroscopy and its clinical application in the field of neuroscience: advances and future directions
WL Chen, J Wagner, N Heugel, J Sugar… - Frontiers in …, 2020 - frontiersin.org
Similar to functional magnetic resonance imaging (fMRI), functional near-infrared
spectroscopy (fNIRS) detects the changes of hemoglobin species inside the brain, but via …
spectroscopy (fNIRS) detects the changes of hemoglobin species inside the brain, but via …
Concurrent fNIRS and EEG for brain function investigation: a systematic, methodology-focused review
Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) stand as
state-of-the-art techniques for non-invasive functional neuroimaging. On a unimodal basis …
state-of-the-art techniques for non-invasive functional neuroimaging. On a unimodal basis …
Decoding covert speech from EEG-a comprehensive review
JT Panachakel, AG Ramakrishnan - Frontiers in Neuroscience, 2021 - frontiersin.org
Over the past decade, many researchers have come up with different implementations of
systems for decoding covert or imagined speech from EEG (electroencephalogram). They …
systems for decoding covert or imagined speech from EEG (electroencephalogram). They …
A dynamic optimal scheduling strategy for multi-charging scenarios of plug-in-electric vehicles over a smart grid
Green transportation has become our top priority due to the depletion of the earth's natural
resources and rising pollutant emission levels. Plug-in electric vehicles (PEVs) are seen as …
resources and rising pollutant emission levels. Plug-in electric vehicles (PEVs) are seen as …
Feature extraction and classification methods for hybrid fNIRS-EEG brain-computer interfaces
In this study, a brain-computer interface (BCI) framework for hybrid functional near-infrared
spectroscopy (fNIRS) and electroencephalography (EEG) for locked-in syndrome (LIS) …
spectroscopy (fNIRS) and electroencephalography (EEG) for locked-in syndrome (LIS) …
[HTML][HTML] Hybrid brain–computer interface techniques for improved classification accuracy and increased number of commands: a review
In this paper, hybrid brain-computer interface (hBCI) technologies for improving
classification accuracy and increasing the number of commands are reviewed. Hybridization …
classification accuracy and increasing the number of commands are reviewed. Hybridization …
Deep learning for hybrid EEG-fNIRS brain–computer interface: application to motor imagery classification
Objective. Brain–computer interface (BCI) refers to procedures that link the central nervous
system to a device. BCI was historically performed using electroencephalography (EEG). In …
system to a device. BCI was historically performed using electroencephalography (EEG). In …
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 …
Wearable, integrated eeg–fnirs technologies: A review
There has been considerable interest in applying electroencephalography (EEG) and
functional near-infrared spectroscopy (fNIRS) simultaneously for multimodal assessment of …
functional near-infrared spectroscopy (fNIRS) simultaneously for multimodal assessment of …
Evaluation of neural degeneration biomarkers in the prefrontal cortex for early identification of patients with mild cognitive impairment: an fNIRS study
Mild cognitive impairment (MCI), a condition characterizing poor cognition, is associated
with aging and depicts early symptoms of severe cognitive impairment, known as …
with aging and depicts early symptoms of severe cognitive impairment, known as …