Subject-Specific feature selection for near infrared spectroscopy based brain-computer interfaces
EA Aydin - Computer Methods and Programs in Biomedicine, 2020 - Elsevier
Abstract Background and Objective Brain-computer interfaces (BCIs) enable people to
control an external device by analyzing the brain's neural activity. Functional near-infrared …
control an external device by analyzing the brain's neural activity. Functional near-infrared …
Optimal feature selection from fNIRS signals using genetic algorithms for BCI
In this paper, a novel technique for determination of the optimal feature combinations and,
thereby, acquisition of the maximum classification performance for a functional near-infrared …
thereby, acquisition of the maximum classification performance for a functional near-infrared …
Recent functional near infrared spectroscopy based brain computer interface systems: developments, applications and challenges
PV Zephaniah, JG Kim - Biomedical Engineering Letters, 2014 - Springer
Abstract Functional Near Infrared Spectroscopy (fNIRS) based Brain Computer Interface
(BCI) systems have grown in popularity in the last years, and has shown itself as a useful …
(BCI) systems have grown in popularity in the last years, and has shown itself as a useful …
Random subspace ensemble learning for functional near-infrared spectroscopy brain-computer interfaces
J Shin - Frontiers in human neuroscience, 2020 - frontiersin.org
The feasibility of the random subspace ensemble learning method was explored to improve
the performance of functional near-infrared spectroscopy-based brain-computer interfaces …
the performance of functional near-infrared spectroscopy-based brain-computer interfaces …
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 …
Enhancing classification performance of functional near-infrared spectroscopy-brain–computer interface using adaptive estimation of general linear model coefficients
In this paper, a novel methodology for enhanced classification of functional near-infrared
spectroscopy (fNIRS) signals utilizable in a two-class [motor imagery (MI) and rest; mental …
spectroscopy (fNIRS) signals utilizable in a two-class [motor imagery (MI) and rest; mental …
Enhancing classification accuracy of fNIRS-BCI using features acquired from vector-based phase analysis
Objective. In this paper, a novel methodology for feature extraction to enhance classification
accuracy of functional near-infrared spectroscopy (fNIRS)-based two-class and three-class …
accuracy of functional near-infrared spectroscopy (fNIRS)-based two-class and three-class …
Subject-independent functional near-infrared spectroscopy-based brain–computer interfaces based on convolutional neural networks
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 …
of brain–computer interfaces (BCIs) owing to their advantages such as non-invasiveness …
Classification of prefrontal and motor cortex signals for three-class fNIRS–BCI
Functional near-infrared spectroscopy (fNIRS) is an optical imaging method that can be
used for a brain-computer interface (BCI). In the present study, we concurrently measure and …
used for a brain-computer interface (BCI). In the present study, we concurrently measure and …
Determining optimal feature-combination for LDA classification of functional near-infrared spectroscopy signals in brain-computer interface application
In this study, we determine the optimal feature-combination for classification of functional
near-infrared spectroscopy (fNIRS) signals with the best accuracies for development of a two …
near-infrared spectroscopy (fNIRS) signals with the best accuracies for development of a two …
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