RLS estimation of fNIRS signal strength as GLM parameters, in the course of real-time brain activation detection*

This paper presents a recursive least square (RLS) estimation based technique to find the signal strength of the functional near infrared spectroscopy (fNIRS) as parameters of general linear model (GLM). The proposed method uses the sampled version of the neuron´s hemodynamic response (design matrix) of the specific experimental paradigm. The results verify the effectiveness of the proposed technique by providing the activity levels at the measuring channels simultaneously while performing the motor-task experiment. The real-time RLS based convergence of activity parameters effectively avoids the necessity of the long experiment as was required for the currently available off-line techniques. The effectiveness of RLS and GLM based method is also verified by obtaining the equally acceptable results with unfiltered data. The proposed method can be utilized for fNIRS based real-time brain imaging technology to cope the delay, inserted by the currently available off-line methods, in obtaining the medical diagnostic results.