2026/02/14 by Samuel Beaton, Borja Blanco, Chiara Bulgarelli +6 · 1 voice
Biochemistry, Genetics and Molecular Biology · Medicine · #Infrared Thermography in Medicine #Optical Imaging and Spectroscopy Techniques #Spectroscopy Techniques in Biomedical and Chemical Research
paper · doi:10.1117/1.nph.13.1.015011
openalex created_date 2026/02/14 · openalex publication_date 2026/02/14 · openalex updated_date 2026/06/11
Significance: Infant functional near-infrared spectroscopy (fNIRS) data are particularly vulnerable to noise; participant behavior can result in motion artifacts, and reduced set-up times can cause poor optode coupling. Accurate channel pruning is therefore essential, but approaches vary and often use adult-derived thresholds, risking unnecessary data loss. Aim: We systematically compared pruning approaches and parameter choices to evaluate their effects on data quality and retention in infant fNIRS. Approach: Data from 5 to 24-month-old infants were collected across two cohorts, using two paradigms. Channel pruning was performed using the coefficient of variation (CV) and the quality testing of near-infrared scans (QT-NIRS) tool, varying key thresholds. Multilevel models assessed the effects of pruning method, parameter choice, age, motion, and testing site on signal-to-noise ratio (SNR) and channels retained. Results: QT-NIRS produced significantly higher SNR than CV pruning across nearly all age, task, and cohort combinations when matched for data retention. Higher QT-NIRS thresholds improved quality but reduced retention. Motion prevalence strongly reduced both SNR and retention; testing site and age had smaller but notable effects. Conclusions: QT-NIRS offers a better balance of data quality and retention than CV pruning. Lower QT-NIRS thresholds than adult defaults are recommended for infant data. These findings provide practical guidance for preprocessing pipelines in developmental fNIRS research.