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Multivariate Kalman filter regression of confounding physiological signals for real-time classification of fNIRS data
Significance: Functional near-infrared spectroscopy (fNIRS) is a noninvasive technique for measuring hemodynamic changes in the human …
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Toward Neuroscience of the Everyday World (NEW) using functional near-infrared spectroscopy
Functional near-infrared spectroscopy (fNIRS) assesses human brain activity by noninvasively measuring changes of cerebral hemoglobin …
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Best practices for fNIRS publications
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Improved physiological noise regression in fNIRS: A multimodal extension of the General Linear Model using temporally embedded Canonical Correlation Analysis
For the robust estimation of evoked brain activity from functional Near-Infrared Spectroscopy (fNIRS) signals, it is crucial to reduce …
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Using the General Linear Model to Improve Performance in fNIRS Single Trial Analysis and Classification: A Perspective
Within a decade, single trial analysis of functional Near Infrared Spectroscopy (fNIRS) signals has gained significant momentum, and …
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M3BA: A Mobile, Modular, Multimodal Biosignal Acquisition Architecture for Miniaturized EEG-NIRS-Based Hybrid BCI and Monitoring
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