Investigation of appropriate fNIRS feature to evaluate cognitive load

Abstract

Functional near-infrared spectroscopy (fNIRS) allows researchers to noninvasively monitor cortical activity in a naturalistic environment, which is an advantage in a field of human well-being research to measure cognitive load in a daily-life situation. We investigated the appropriate features of fNIRS signals that best indicates the amount of cognitive load required for performing the multisensory-motor cognitive task. The features tested were (1) maximum amplitude relative to the baseline (MAX) and (2) cumulated amplitude (area under the curve (AUC)) of the normalized average fNIRS signals, and (3) beta value obtained by generalized linear modelling of the raw fNIRS signal using a block design (beta). Oxy-hemoglobin fNIRS features of AUC and beta showed better correspondence to the behavioral measure of cognitive load relative to that of MAX, suggesting that these two indices could be the suitable measure to evaluate cognitive load from fNIRS signals.