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Signal quality index: an algorithm for quantitative assessment of functional near infrared spectroscopy signal quality

M. Sofía Sappia, Naser Hakimi, Willy N. J. M. Colier, Jörn M. Horschig

2020Biomedical Optics Express47 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

Functional near-infrared spectroscopyPreprocessorSIGNAL (programming language)Computer scienceQuality (philosophy)Artificial intelligenceSignal processingAlgorithmPattern recognition (psychology)Digital signal processingPhysicsMedicineCognitionComputer hardwarePrefrontal cortexQuantum mechanicsPsychiatryProgramming languageOptical Imaging and Spectroscopy TechniquesNon-Invasive Vital Sign MonitoringHemodynamic Monitoring and Therapy
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