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Assessment of Surgical Tasks Using Neuroimaging Dataset (ASTaUND)

  • Anil Kamat
  • , Condell Eastmond
  • , Yuanyuan Gao
  • , Arun Nemani
  • , Erim Yanik
  • , Lora Cavuoto
  • , Matthew Hackett
  • , Jack Norfleet
  • , Steven Schwaitzberg
  • , Suvranu De
  • , Xavier Intes
  • Rensselaer Polytechnic Institute
  • Boston University
  • Florida State University
  • SUNY Buffalo

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Functional near-infrared spectroscopy (fNIRS) is a neuroimaging tool for studying brain activity in mobile subjects. Open-access fNIRS datasets are limited to simple and/or motion-restricted tasks. Here, we report a fNIRS dataset acquired on mobile subjects performing Fundamentals of Laparoscopic Surgery (FLS) tasks in a laboratory environment. Demonstrating competency in the FLS tasks is a prerequisite for board certification in general surgery in the United States. The ASTaUND data set was acquired over four different studies. We provide the relevant information about the hardware, FLS task execution protocols, and subject demographics to facilitate the use of this open-access data set. We also provide the concurrent FLS scores, a quantitative metric for surgical skill assessment developed by the FLS committee. This data set is expected to support the growing field of assessing surgical skills via neuroimaging data and provide an example of data processing pipeline for use in realistic, non-restrictive environments.

Original languageEnglish
Article number699
JournalScientific Data
Volume10
Issue number1
DOIs
StatePublished - Dec 2023

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