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Assessing bimanual motor skills with optical neuroimaging.

Arun NemaniMeryem A YücelUwe KrugerDenise W GeeClairice CooperSteven D SchwaitzbergSuvranu DeXavier Intes
Published in: Science advances (2018)
Measuring motor skill proficiency is critical for the certification of highly skilled individuals in numerous fields. However, conventional measures use subjective metrics that often cannot distinguish between expertise levels. We present an advanced optical neuroimaging methodology that can objectively and successfully classify subjects with different expertise levels associated with bimanual motor dexterity. The methodology was tested by assessing laparoscopic surgery skills within the framework of the fundamentals of a laparoscopic surgery program, which is a prerequisite for certification in general surgery. We demonstrate that optical-based metrics outperformed current metrics for surgical certification in classifying subjects with varying surgical expertise. Moreover, we report that optical neuroimaging allows for the successful classification of subjects during the acquisition of these skills.
Keyphrases
  • laparoscopic surgery
  • high resolution
  • high speed
  • machine learning
  • medical students
  • physical activity
  • deep learning
  • sleep quality