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Automated Processing of fNIRS Data-A Visual Guide to the Pitfalls and Consequences.

Lia M HockeIbukunoluwa K OniChris C DuszynskiAlex V CorriganBlaise deB FrederickJeffrey F Dunn
Published in: Algorithms (2018)
With the rapid increase in new fNIRS users employing commercial software, there is a concern that many studies are biased by suboptimal processing methods. The purpose of this study is to provide a visual reference showing the effects of different processing methods, to help inform researchers in setting up and evaluating a processing pipeline. We show the significant impact of pre- and post-processing choices and stress again how important it is to combine data from both hemoglobin species in order to make accurate inferences about the activation site.
Keyphrases
  • electronic health record
  • machine learning
  • big data
  • high throughput
  • high resolution
  • mass spectrometry
  • heat stress
  • artificial intelligence
  • sensitive detection