Signal Acquisition by Functional Near Infrared Spectroscopy and Data Analysis for Mental Aptitude Tasks

Abstrak

General Linear Model is a statistical approach to enable an accurate analysis of NIRS signal. In this study. the fNIRS data are regressed using a linear combination of task-related regressors plus an error term. The mental tasks related regressors are obtained by convolving boxcar functions, that correspond to our experimental design with HRF. Experimentally the signal was acquired from a functional NIRS system during the brain activation from the participant while visual stimulation task. The block design for data acquisition consists of 40s rest and 60s task in repetition. From the measured data, oxy-hemoglobin was estimated and considered for parametric analysis. We observed a statistical significance of p<0.9 from our analysis.