Analysis of different classification techniques for two‐class functional near‐infrared spectroscopy‐based brain‐computer interface

N Naseer, NK Qureshi, FM Noori… - Computational …, 2016 - Wiley Online Library
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 …

Determining optimal feature-combination for LDA classification of functional near-infrared spectroscopy signals in brain-computer interface application

N Naseer, FM Noori, NK Qureshi… - Frontiers in human …, 2016 - frontiersin.org
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 …

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 …

Optimal feature selection from fNIRS signals using genetic algorithms for BCI

FM Noori, N Naseer, NK Qureshi, H Nazeer… - Neuroscience letters, 2017 - Elsevier
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 …

Classification of prefrontal and motor cortex signals for three-class fNIRS–BCI

KS Hong, N Naseer, YH Kim - Neuroscience letters, 2015 - Elsevier
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 …

[PDF][PDF] Functional near infrared spectroscope for cognition brain tasks by wavelets analysis and neural networks

TQD Khoa, M Nakagawa - International Journal of Psychological and …, 2008 - Citeseer
Brain Computer Interface (BCI) has been recently increased in research. Functional Near
Infrared Spectroscope (fNIRs) is one the latest technologies which utilize light in the near …

Online binary decision decoding using functional near-infrared spectroscopy for the development of brain–computer interface

N Naseer, MJ Hong, KS Hong - Experimental brain research, 2014 - Springer
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 …

Enhancing classification accuracy of fNIRS-BCI using features acquired from vector-based phase analysis

H Nazeer, N Naseer, RA Khan, FM Noori… - Journal of Neural …, 2020 - iopscience.iop.org
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 …

Single trial classification of fNIRS-based brain-computer interface mental arithmetic data: a comparison between different classifiers

G Bauernfeind, D Steyrl, C Brunner… - 2014 36th Annual …, 2014 - ieeexplore.ieee.org
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 …

Improving classification performance of four class FNIRS-BCI using Mel Frequency Cepstral Coefficients (MFCC)

MSBA Ghaffar, US Khan, J Iqbal, N Rashid… - Infrared Physics & …, 2021 - Elsevier
Experimentation and analysis of Functional near-infrared spectroscopy (fNIRS) in Brain-
Computer Interface (BCI) has increasingly been studied as a communication possibility for …