Estimation of Skin Blood Flow Artefacts in NIRS Signals During a Verbal Fluency Task

The aim of this study was to clarify effects of skin (scalp) blood flow on functional near infrared spectroscopy (fNIRS) during a verbal fluency task. In the present study, to estimate the influence of skin blood flow on fNIRS signals, we conducted examinations on 19 healthy volunteers (39.9±13.1 years, 11 male and 8 female subjects). We simultaneously measured the fNIRS signals, skin blood flow (i.e., flow, velocity, and number of red blood cells [RBC]), and pulse wave rates using a multimodal fNIRS system. We found that the effects of skin blood flow, measured by the degree of interference of the flow, velocity, and number of RBCs, and pulse wave rates, on NIRS signals varied considerably across subjects. Further, by using the above physiological parameters, we evaluated application of the independent component analysis algorithm proposed by Molgedey and Schuster (MS-ICA) to remove skin blood flow artefacts from fNIRS signals.