Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.neulet.2012.02.048
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
Source: 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. https://doi.org/10.1016/j.neulet.2012.02.048
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
URI: http://scholarbank.nus.edu.sg/handle/10635/55460
ISSN: 03043940
DOI: 10.1016/j.neulet.2012.02.048
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