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Array Designer: automated optimized array design for functional near-infrared spectroscopy.

Sabrina Brigadoi1,2, Domenico Salvagnin3, Matteo Fischetti3

  • 1University College London, Biomedical Optics Research Laboratory, Department of Medical Physics and Biomedical Engineering, London, United Kingdom.

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|September 22, 2018
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Summary
This summary is machine-generated.

Array Designer automates functional near-infrared spectroscopy (fNIRS) array design. This tool optimizes optode placement for specific brain regions, saving time and improving data quality.

Keywords:
array designfunctional near-infrared spectroscopyoptode placementprobe design

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Medical Imaging

Background:

  • Functional near-infrared spectroscopy (fNIRS) relies on precise source and detector (optode) placement for accurate cortical sensitivity.
  • Manual selection of optode locations is subjective, time-consuming, and prone to variability.
  • Optimizing optode placement is critical for reliable fNIRS data acquisition.

Purpose of the Study:

  • To introduce Array Designer, an automated tool for designing functional near-infrared spectroscopy (fNIRS) arrays.
  • To enable users to define a target cortical region-of-interest (ROI) for optimized optode placement.
  • To provide a generalizable solution applicable to various fNIRS devices and subject populations.

Main Methods:

  • Development of an algorithmic methodology for automated fNIRS array design.
  • Integration of user-defined ROIs and fNIRS device specifications into the design process.
  • Validation through simulations using a realistic anatomical model.

Main Results:

  • Demonstration of Array Designer's capability to automatically generate optimized fNIRS channel configurations.
  • Validation of the methodology through extensive simulations.
  • Potential for significant time savings and improved data quality in fNIRS research.

Conclusions:

  • Array Designer offers an automated, objective, and efficient alternative to manual fNIRS array design.
  • The tool has the potential to enhance fNIRS data quality and promote standardization across research.
  • This methodology is adaptable to diverse fNIRS experimental setups and subject groups.