Metaheuristic Optimization-Based Feature Selection for Imagery and Arithmetic Tasks: An fNIRS Study

In recent decades, the brain–computer interface (BCI) has emerged as a leading area of research. The feature selection is vital to reduce the dataset’s dimensionality, increase the computing effectiveness, and enhance the BCI’s performance. Using activity-related features leads to a high classificat...

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Bibliographic Details
Published in:	Sensors (Basel, Switzerland) Vol. 23; no. 7; p. 3714
Main Authors:	Zafar, Amad, Hussain, Shaik Javeed, Ali, Muhammad Umair, Lee, Seung Won
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 03.04.2023 MDPI
Subjects:	Algorithms Brain research Brain-Computer Interfaces brain–computer interface (BCI) Classification Datasets Electroencephalography Electroencephalography - methods Feature selection fNIRS Imagery, Psychotherapy Imagination Infrared spectroscopy Mathematical optimization mental arithmetic motor imagery optimization Optimization algorithms Physiology Spectroscopy, Near-Infrared - methods United States Massachusetts brain–computer interface (BCI) motor imagery fNIRS optimization mental arithmetic feature selection
ISSN:	1424-8220, 1424-8220
Online Access:	Get full text
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