Shedding light on neuroscience: Two decades of functional near‐infrared spectroscopy applications and advances from a bibliometric perspective

MÂM Devezas - Journal of Neuroimaging, 2021 - Wiley Online Library
Functional near‐infrared spectroscopy (fNIRS) is a noninvasive optical brain‐imaging
technique that detects changes in hemoglobin concentration in the cerebral cortex. fNIRS …

[HTML][HTML] Emotion recognition from EEG-based relative power spectral topography using convolutional neural network

MA Rahman, A Anjum, MMH Milu, F Khanam… - Array, 2021 - Elsevier
Emotion recognition, a challenging computational issue, finds interesting applications in
diverse fields. Usually, feature-based machine-learning methods have been used for …

The potential role of fNIRS in evaluating levels of consciousness

A Abdalmalak, D Milej, L Norton, DB Debicki… - Frontiers in Human …, 2021 - frontiersin.org
Over the last few decades, neuroimaging techniques have transformed our understanding of
the brain and the effect of neurological conditions on brain function. More recently, light …

Improvement of classification accuracy of four-class voluntary-imagery fNIRS signals using convolutional neural networks

MMH Milu, MA Rahman, MA Rashid, A Kuwana… - … , Technology & Applied …, 2023 - etasr.com
Abstract Multiclass functional Near-Infrared Spectroscopy (fNIRS) signal classification has
become a convenient way for optical brain-computer interface. fNIRS signal classification …

Electroencephalogram-based cognitive load level classification using wavelet decomposition and support vector machine

F Khanam, ABMA Hossain, M Ahmad - Brain-Computer Interfaces, 2023 - Taylor & Francis
Cognitive load level identification is an interesting challenge in the field of brain-computer-
interface. The sole objective of this work is to classify different cognitive load levels from …

[HTML][HTML] Statistical valuation of cognitive load level hemodynamics from functional near-infrared spectroscopy signals

F Khanam, ABMA Hossain, M Ahmad - Neuroscience Informatics, 2022 - Elsevier
Human cognitive load level assessment is a challenging issue in the field of functional brain
imaging. This work aims to study different cognitive load levels statistically from brain …

Optimized localization learning algorithm for indoor and outdoor localization system in WSNs

P Yadav, SC Sharma, O Singh, V Rishiwal - Wireless Personal …, 2023 - Springer
The localization problem in wireless sensor networks (WSN) has recently received justifiable
interest from researchers. Various optimization/learning algorithms are used to determine …

Q-Learning based optimized localization in WSN

P Yadav, SC Sharma - 2023 6th International Conference on …, 2023 - ieeexplore.ieee.org
Localization is an critical issue to solve because, in some instances, it is crucial to identify
the pinpoint location of the nodes due to unfavorable circumstances. Various optimization …

Assessment of cognitive workload using simultaneous EEG and fNIRS: A comparison of feature combinations

A Ghasimi, S Shamekhi - Computers and Electrical Engineering, 2024 - Elsevier
The assessment of cognitive workload is a critical component in evaluating mental activity. It
is essential in psychology, especially in professions with heightened cognitive demands …

The effects of a virtual reality rehabilitation task on elderly subjects: An experimental study using multimodal data

J Qu, L Cui, W Guo, X Ren, L Bu - IEEE Transactions on Neural …, 2022 - ieeexplore.ieee.org
Ageing populations are becoming a global issue. Against this background, the assessment
and treatment of geriatric conditions have become increasingly important. This study draws …