A unified analytical framework with multiple fNIRS features for mental workload assessment in the prefrontal cortex
Knowing the actual level of mental workload is important to ensure the efficacy of brain-
computer interface (BCI) based cognitive training. Extracting signals from limited area of a …
computer interface (BCI) based cognitive training. Extracting signals from limited area of a …
[HTML][HTML] Statistical valuation of cognitive load level hemodynamics from functional near-infrared spectroscopy signals
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 …
imaging. This work aims to study different cognitive load levels statistically from brain …
[HTML][HTML] Optimized electroencephalogram and functional near-infrared spectroscopy-based mental workload detection method for practical applications
H Chu, Y Cao, J Jiang, J Yang, M Huang, Q Li… - BioMedical Engineering …, 2022 - Springer
Background Mental workload is a critical consideration in complex man–machine systems
design. Among various mental workload detection techniques, multimodal detection …
design. Among various mental workload detection techniques, multimodal detection …
[HTML][HTML] Enhanced accuracy for multiclass mental workload detection using long short-term memory for brain–computer interface
Cognitive workload is one of the widely invoked human factors in the areas of human–
machine interaction (HMI) and neuroergonomics. The precise assessment of cognitive and …
machine interaction (HMI) and neuroergonomics. The precise assessment of cognitive and …
Classification of cognitive load based on neurophysiological features from functional near-infrared spectroscopy and electrocardiography signals on n-back task
Cognitive load can be estimated using individuals' task performance, their subjective
measures, and neurophysiological measures. Neurophysiological measures, which among …
measures, and neurophysiological measures. Neurophysiological measures, which among …
Discrimination of mental workload levels from multi-channel fNIRS using deep leaning-based approaches
Functional near-infrared spectroscopy (fNIRS), known as a non-invasive optical
neuroimaging technique, is currently used to assess brain dynamics during the performance …
neuroimaging technique, is currently used to assess brain dynamics during the performance …
[HTML][HTML] Enhancing classification performance of fNIRS-BCI by identifying cortically active channels using the z-score method
A state-of-the-art brain–computer interface (BCI) system includes brain signal acquisition,
noise removal, channel selection, feature extraction, classification, and an application …
noise removal, channel selection, feature extraction, classification, and an application …
Deep leaning-based approach for mental workload discrimination from multi-channel fNIRS
As a non-invasive optical neuroimaging technique, functional near infrared spectroscopy
(fNIRS) is currently used to assess brain dynamics during the performance of complex works …
(fNIRS) is currently used to assess brain dynamics during the performance of complex works …
Assessment and classification of mental workload in the prefrontal cortex (PFC) using fixed-value modified beer-lambert law
Optical-neuro-imaging based functional Near-Infrared Spectroscopy (fNIRS) has been in
use for several years in the fields of brain research to measure the functional response of …
use for several years in the fields of brain research to measure the functional response of …
Measuring Cognitive Load: Leveraging fNIRS and Machine Learning for Classification of Workload Levels
Measuring cognitive load, a subjective construct that reflects the mental effort required for a
given task, remains a challenging endeavor. While Functional Near-Infrared Spectroscopy …
given task, remains a challenging endeavor. While Functional Near-Infrared Spectroscopy …