Cortical brain imaging by adaptive filtering of NIRS signals

• Published in: Neuroscience letters 2012-04, Vol.514 (1), p.35-41
• Main Authors: Aqil, Muhammad, Hong, Keum-Shik, Jeong, Myung-Yung, Ge, Shuzhi Sam
• Format: Article
• Language: English
• Subjects: Brain Mapping - methods; Cerebral Cortex - physiology; Functional near-infrared spectroscopy; Functional Neuroimaging - methods; General linear model; Humans; Image Processing, Computer-Assisted; Models, Neurological; Optical brain imaging; Real-time mapping; Recursive least square estimation; Reproducibility of Results; Software; Spectroscopy, Near-Infrared; Statistical parametric mapping
• ISSN: 0304-3940; 1872-7972
• DOI: 10.1016/j.neulet.2012.02.048

► Run-time (real-time) brain imaging framework. ► Robust-adaptive RLSE-based spatial filter besides estimator. ► Robust treatment of each measuring channel unanimously as per the requirement. ► Applicable for online medical diagnostics and therapeutic studies. 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.