Open AccessSignal quality index: an algorithm for quantitative assessment of functional near infrared spectroscopy signal quality
Author(s) -
María Sofía Sappia,
Naser Hakimi,
Willy N.J.M. Colier,
Jörn M. Horschig
Publication year - 2020
Publication title -
biomedical optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.362
H-Index - 86
ISSN - 2156-7085
DOI - 10.1364/boe.409317
Subject(s) - functional near infrared spectroscopy , preprocessor , computer science , signal (programming language) , quality (philosophy) , artificial intelligence , signal processing , algorithm , pattern recognition (psychology) , digital signal processing , medicine , physics , cognition , quantum mechanics , psychiatry , computer hardware , programming language , prefrontal cortex
We propose the signal quality index (SQI) algorithm as a novel tool for quantitatively assessing the functional near infrared spectroscopy (fNIRS) signal quality in a numeric scale from 1 (very low quality) to 5 (very high quality). The algorithm comprises two preprocessing steps followed by three consecutive rating stages. The results on a dataset annotated by independent fNIRS experts showed SQI performed significantly better (p<0.05) than PHOEBE (placing headgear optodes efficiently before experimentation) and SCI (scalp coupling index), two existing algorithms, in both quantitatively rating and binary classifying the fNIRS signal quality. Employment of the proposed algorithm to estimate the signal quality before processing the fNIRS signals increases certainty in the interpretations.