Please use this identifier to cite or link to this item:
Title: Cortical brain imaging by adaptive filtering of NIRS signals
Authors: Aqil, M.
Hong, K.-S.
Jeong, M.-Y.
Ge, S.S. 
Keywords: Functional near-infrared spectroscopy
General linear model
Optical brain imaging
Real-time mapping
Recursive least square estimation
Statistical parametric mapping
Issue Date: 11-Apr-2012
Citation: Aqil, M., Hong, K.-S., Jeong, M.-Y., Ge, S.S. (2012-04-11). Cortical brain imaging by adaptive filtering of NIRS signals. Neuroscience Letters 514 (1) : 35-41. ScholarBank@NUS Repository.
Abstract: This paper presents an online brain imaging framework for cognitive tasks conducted with functional near-infrared spectroscopy (fNIRS). The measured signal at each channel is regarded as the output from a linear system with unknown coefficients. The unknown coefficients are estimated by using the recursive least squares estimation (RLSE) method. The validity of the estimated parameters is tested using the . t-statistics. Contrary to the classical approach that is offline and applies the same preprocessing scheme to all channels, the proposed RLSE method for a linear model formulation provides an independent robust adaptive process for individual channels. The experiments carried out with two fNIRS instruments (continuous-wave and frequency-domain) have verified the potential of the proposed methodology which can facilitate a prompt medical diagnostics by providing real-time brain activation maps. © 2012 Elsevier Ireland Ltd.
Source Title: Neuroscience Letters
ISSN: 03043940
DOI: 10.1016/j.neulet.2012.02.048
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.


checked on Feb 15, 2019


checked on Feb 6, 2019

Page view(s)

checked on Nov 3, 2018

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.