Quantification of motion during microvascular anastomosis simulation using machine learning hand detection.

Journal: Neurosurgical focus
Published Date: Jun 1, 2023

Abstract

OBJECTIVE: Microanastomosis is one of the most technically demanding and important microsurgical skills for a neurosurgeon. A hand motion detector based on machine learning tracking technology was developed and implemented for performance assessment during microvascular anastomosis simulation.

Authors

  • Nicolas I Gonzalez-Romo
  • Sahin Hanalioglu
    Department of Neurological Surgery, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin, United States.
  • Giancarlo Mignucci-JimĂ©nez
  • Grant Koskay
  • Irakliy Abramov
  • Yuan Xu
    Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, College of Life Sciences, Northwest University, Xi'an, China.
  • Wonhyoung Park
  • Michael T Lawton
    Department of Neurosurgery, c/o Neuroscience Publications, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, 350 West Thomas Road, Phoenix, AZ 85013, USA. Electronic address: Neuropub@barrowneuro.org.
  • Mark C Preul

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