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O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression
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The NIRS Analysis Package: noise reduction and statistical inference.

Tomer Fekete1, Denis Rubin, Joshua M Carlson

  • 1Department of Biomedical Engineering, State University of New York at Stony Brook, Stony Brook, New York, United States of America.

Plos One
|September 14, 2011
PubMed
Summary

This study introduces a new framework to improve statistical analysis for near-infrared spectroscopy (NIRS) brain imaging. The NIRS Analysis Package (NAP) toolbox enhances data reliability and detection power by addressing NIRS-specific noise.

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Area of Science:

  • Neuroimaging
  • Biomedical Optics
  • Signal Processing

Background:

  • Near-infrared spectroscopy (NIRS) measures cortical hemodynamic responses non-invasively.
  • NIRS data analysis often adapts functional magnetic resonance imaging (fMRI) methods, despite significant modality differences.
  • NIRS data are susceptible to unique noise sources, including physiological and motion-related artifacts.

Purpose of the Study:

  • To investigate the impact of NIRS-specific noise on statistical inference within the general linear model.
  • To develop and present a comprehensive framework for noise reduction and statistical inference tailored to NIRS.
  • To implement these methods in a publicly available MATLAB toolbox.

Main Methods:

  • Developed a custom framework for noise reduction and statistical inference specific to NIRS.
  • Implemented the framework in the NIRS Analysis Package (NAP) MATLAB toolbox.
  • Validated the NAP toolbox using both simulated and real NIRS data.

Main Results:

  • The proposed framework effectively addresses NIRS-specific noise characteristics.
  • The NAP toolbox demonstrates marked improvements in the detection power of NIRS data.
  • Enhanced reliability of statistical inference for NIRS measurements was observed.

Conclusions:

  • The developed framework and NAP toolbox offer a significant advancement for NIRS data analysis.
  • NAP improves the validity and power of statistical inference in NIRS studies.
  • This work provides a valuable resource for researchers utilizing NIRS for neuroimaging.