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 …
Analysis of different classification techniques for two‐class functional near‐infrared spectroscopy‐based brain‐computer interface
We analyse and compare the classification accuracies of six different classifiers for a two‐
class mental task (mental arithmetic and rest) using functional near‐infrared spectroscopy …
class mental task (mental arithmetic and rest) using functional near‐infrared spectroscopy …
Online binary decision decoding using functional near-infrared spectroscopy for the development of brain–computer interface
In this paper, a functional near-infrared spectroscopy (fNIRS)-based online binary decision
decoding framework is developed. Fourteen healthy subjects are asked to mentally make …
decoding framework is developed. Fourteen healthy subjects are asked to mentally make …
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 …
Single-trial classification of antagonistic oxyhemoglobin responses during mental arithmetic
Near-infrared spectroscopy (NIRS) is a non-invasive optical technique that can be used for
brain–computer interfaces (BCIs) systems. A common challenge for BCIs is a stable and …
brain–computer interfaces (BCIs) systems. A common challenge for BCIs is a stable and …
Classification of frontal cortex haemodynamic responses during cognitive tasks using wavelet transforms and machine learning algorithms
B Abibullaev, J An - Medical engineering & physics, 2012 - Elsevier
Recent advances in neuroimaging demonstrate the potential of functional near-infrared
spectroscopy (fNIRS) for use in brain–computer interfaces (BCIs). fNIRS uses light in the …
spectroscopy (fNIRS) for use in brain–computer interfaces (BCIs). fNIRS uses light in the …
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 …
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 …
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 …
Single trial classification of fNIRS-based brain-computer interface mental arithmetic data: a comparison between different classifiers
Functional near infrared spectroscopy (fNIRS) is an emerging technique for the in-vivo
assessment of functional activity of the cerebral cortex as well as in the field of brain …
assessment of functional activity of the cerebral cortex as well as in the field of brain …
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