Automatic gesture recognition and evaluation in peg transfer tasks of laparoscopic surgery training.

Journal: Surgical endoscopy
Published Date: May 2, 2025

Abstract

BACKGROUND: Laparoscopic surgery training is gaining increasing importance. To release doctors from the burden of manually annotating videos, we proposed an automatic surgical gesture recognition model based on the Fundamentals of Laparoscopic Surgery (FLS) and the Chinese Laparoscopic Skills Testing and Assessment (CLSTA) tools. Furthermore, statistical analysis was conducted based on a gesture vocabulary that had been designed to examine differences between groups at different levels.

Authors

  • Shujun Ju
    West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
  • Penglin Jiang
    Department of Industrial Engineering, Sichuan University, Chengdu, China.
  • Yutong Jin
    Department of Industrial Engineering, Sichuan University, Chengdu, China.
  • Yaoyu Fu
    West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
  • Xiandi Wang
    West China Medical Simulation Center, West China Hospital, Chengdu, China.
  • Xiaomei Tan
    Department of Industrial Engineering, Sichuan University, Chengdu, China.
  • Ying Han
    Department of Neurology, XuanWu Hospital of Capital Medical University, Beijing, China.
  • Rong Yin
    West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China. rong.yin@scupi.cn.
  • Dan Pu
    West China Medical Simulation Center, West China Hospital, Chengdu, China.
  • Kang Li
    Department of Otolaryngology, Longgang Otolaryngology hospital & Shenzhen Key Laboratory of Otolaryngology, Shenzhen Institute of Otolaryngology, Shenzhen, Guangdong, China.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals