ArticleJournal of biomedical optics2015
Comparison of motion correction techniques applied to functional near-infrared spectroscopy data from children.
Article in Journal of biomedical optics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 32 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
32 citing papers in PubMed.
- Sex-differences in resting state dorsolateral prefrontal cortex: comparing motion correction methods in resting state functional near-infrared spectroscopy (fNIRS).Brain structure & function · 2026Article
- Interpolation and Imputation Strategies for Missing Segments in Continuous Pressure-Flow Cerebral Bio-Signals: A Systematic Scoping Review.Sensors (Basel, Switzerland) · 2026Article
- Considerations for conducting developmental neuroimaging research on mental health topics.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026Review
- The effects of protocol factors and participant characteristics on functional near-infrared spectroscopy data quality after stroke.Neuroimage. Reports · 2025Article
- Cerebral Haemodynamic Assessment Following Sport-related Concussion (Mild Traumatic Brain Injury) in Youth and Amateur Rugby Union Players.Sports medicine - open · 2025Article
- Time-Normalization Approach for fNIRS Data During Tasks with High Variability in Duration.Sensors (Basel, Switzerland) · 2025Article
- Disentangling the impact of motion artifact correction algorithms on functional near-infrared spectroscopy-based brain network analysis.Neurophotonics · 2024Article
- Comparing different motion correction approaches for resting-state functional connectivity analysis with functional near-infrared spectroscopy data.Neurophotonics · 2024Article
- Cortical activity during online motor control in children with and without developmental coordination disorder: a cross-sectional functional near-infrared spectroscopy study.Journal of neuroengineering and rehabilitation · 2024Article
- Real-time motion artifact suppression using convolution neural networks with penalty in fNIRS.Frontiers in neuroscience · 2024Article
- Mental workload classification using convolutional neural networks based on fNIRS-derived prefrontal activity.BMC neurology · 2023Article
- Improved Motion Artifact Correction in fNIRS Data by Combining Wavelet and Correlation-Based Signal Improvement.Sensors (Basel, Switzerland) · 2023Article
- Can the fNIRS-derived neural biomarker better discriminate mild cognitive impairment than a neuropsychological screening test?Frontiers in aging neuroscience · 2023Article
- Motion artifact correction for resting-state neonatal functional near-infrared spectroscopy through adaptive estimation of physiological oscillation denoising.Neurophotonics · 2022Article
- Person-specific connectivity mapping uncovers differences of bilingual language experience on brain bases of attention in children.Brain and language · 2022Article
- Hybrid motion artifact detection and correction approach for functional near-infrared spectroscopy measurements.Journal of biomedical optics · 2022Article
- Motion artifacts removal and evaluation techniques for functional near-infrared spectroscopy signals: A review.Frontiers in neuroscience · 2022Review
- Review
- Comparing different pre-processing routines for infant fNIRS data.Developmental cognitive neuroscience · 2021Article
- More than meets the eye: The neural development of emotion face processing during infancy.Infant behavior & development · 2020Article
Corrections and comments
- Erratum issued
Authors and funding
8 authors.
Funding
Abstract
Motion artifacts are the most significant sources of noise in the context of pediatric brain imaging designs and data analyses, especially in applications of functional near-infrared spectroscopy (fNIRS), in which it can completely affect the quality of the data acquired. Different methods have been developed to correct motion artifacts in fNIRS data, but the relative effectiveness of these methods for data from child and infant subjects (which is often found to be significantly noisier than adult data) remains largely unexplored. The issue is further complicated by the heterogeneity of fNIRS data artifacts. We compared the efficacy of the six most prevalent motion artifact correction techniques with fNIRS data acquired from children participating in a language acquisition task, including wavelet, spline interpolation, principal component analysis, moving average (MA), correlation-based signal improvement, and combination of wavelet and MA. The evaluation of five predefined metrics suggests that the MA and wavelet methods yield the best outcomes. These findings elucidate the varied nature of fNIRS data artifacts and the efficacy of artifact correction methods with pediatric populations, as well as help inform both the theory and practice of optical brain imaging analysis.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.