Cited 4 time in webofscience Cited 3 time in scopus

Classification of brain hemodynamic signals arising from visual action observation tasks for brain-computer interfaces: A functional near-infrared spectroscopy study

Title
Classification of brain hemodynamic signals arising from visual action observation tasks for brain-computer interfaces: A functional near-infrared spectroscopy study
Authors
Abibullaev, B[Abibullaev, Berdakh]An, J[An, Jinung]Jin, SH[Jin, Sang-Hyeon]Moon, JI[Moon, Jeon Il]
DGIST Authors
Abibullaev, B[Abibullaev, Berdakh]; An, J[An, Jinung]; Jin, SH[Jin, Sang-Hyeon]; Moon, JI[Moon, Jeon Il]
Issue Date
2014-03
Citation
Measurement: Journal of the International Measurement Confederation, 49, 320-328
Type
Article
Article Type
Article
Keywords
Action Observation TasksBrainBrain-Computer InterfacesBrain Computer InterfaceBrain Hemodynamic SignalsFunctional Near-Infrared SpectroscopiesFunctional Near-Infrared Spectroscopy (FNIRS)Functional NeuroimagingHemodynamic SignalsHemodynamicsInterfaces (Computer)Near-Infrared SpectroscopyNeurophysiologyPCASVM
ISSN
0263-2241
Abstract
A brain-computer interface (BCI) is a way of translating an individuals' thoughts to control a computer or an external mechanical device. Studying brain activities in a reproducible manner, this study explores the possibility of using real-time functional-near infrared spectroscopy (fNIRS) to detect brain hemodynamic features for BCI commands. Sixteen channel brain activities associated with two distinct mental tasks were measured from seven healthy subjects. The tasks represented neural activities arising from a visual observation of a motor action related to hand movements of the subjects. Sensitive signatures of task relevant neural activities were further extracted from hemodynamic signals in the prefrontal cortex of the brain, and subsequently were translated into pre-determined computer commands using a set of algorithms. The decoded commands allowed volunteer subjects to control an external device in real-time through their mental intentions. The obtained results demonstrate the potential of the current study as an alternative fNIRS-BCI paradigm. © 2013 Elsevier Ltd. All rights reserved.
URI
http://hdl.handle.net/20.500.11750/1590
DOI
10.1016/j.measurement.2013.11.044
Publisher
Elsevier Ltd
Related Researcher
Files:
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Collection:
ETCETC
Division of IoT∙Robotics Convergence Research1. Journal Articles
ETC1. Journal Articles


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