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Selective Detrending using Baseline Drift Detection Index for Task-dependant fNIRS Signal

Title
Selective Detrending using Baseline Drift Detection Index for Task-dependant fNIRS Signal
Authors
An, Jin UngLee, GihyounLee, Seung HyunJin, Sang Hyeon
DGIST Authors
An, Jin Ung; Lee, Gihyoun; Lee, Seung Hyun; Jin, Sang Hyeon
Issue Date
2017
Citation
Advances in Science, Technology and Engineering Systems, 2(3), 1147-1151
Type
Article
Article Type
Article
ISSN
2415-6698
Abstract
A functional near-infrared spectroscopy (fNIRS) can be employed to investigate brain activation by measuring the absorption of near-infrared light through the intact skull. The general linear model (GLM) as a standard model for fMRI analysis has been applied to functional near-infrared spectroscopic (fNIRS) imaging analysis as well. The GLM has drawback of failure in fNIRS signals, when they have drift globally. Wavelet based detrending technique is very popular to correct the baseline drift (BD) in fNIRS. However, this method globally distorted the total multi-channel signals even if just one channel’s signal was locally drifted. This paper suggests the selective detrending method using BD detection index to indicate BD as an objective index. The experiments show the performance of the proposed method as graphic results and objective evaluation index with current detrending algorithms. © 2017 ASTES Publishers. All rights reserved.
URI
http://hdl.handle.net/20.500.11750/6554
DOI
10.25046/aj0203144
Publisher
Advances in Science, Technology and Engineering Systems Journal (ASTESJ)
Related Researcher
  • Author An, Jinung Brain Robot Augmented InteractioN(BRAIN) Laboratory
  • Research Interests
Files:
There are no files associated with this item.
Collection:
Division of Intelligent RobotBrain Robot Augmented InteractioN(BRAIN) Laboratory1. Journal Articles
Convergence Research Center for Wellness1. Journal Articles
Division of Intelligent Robot1. Journal Articles


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