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Evaluating Smoothness of Force for Surgical Skill Assessment
  • +3
  • Simar P. Singh,
  • Amir Mehdi Shayan,
  • Jianxin Gao,
  • Joe Bible,
  • Richard E Groff,
  • Ravikiran Singapogu
Simar P. Singh
Department of Bioengineering, Clemson University

Corresponding Author:[email protected]

Author Profile
Amir Mehdi Shayan
Department of Bioengineering, Clemson University
Jianxin Gao
Department of Electrical and Computer Engineering, Clemson University
Joe Bible
Department of Mathematical and Statistical Sciences, Clemson University
Richard E Groff
Department of Electrical and Computer Engineering, Clemson University
Ravikiran Singapogu
Department of Bioengineering, Clemson University

Abstract

This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.”  
The efficient execution of surgical operations plays a crucial role in optimizing patient outcomes, evidencing the need for effective training methods to improve surgical skills. The gaining traction of medical training simulators for automated skill assessment necessitates instrumented sensors and relevant metrics for targeted feedback on all aspects of a surgical procedure. Traditional metrics that capture a single instance of force, such as peak or range, lack the characterization of the entire force profile and lose subtleties that may limit accurate evaluation of the skilled application of force, a valuable aspect of assessment in surgery. This study introduces novel force metrics inspired by motion smoothness-based measures, analyzed on an extensive dataset of 97 subjects suturing on an open vascular suturing simulator. We validated the effectiveness of these metrics by comparing the metrics' ability to distinguish between subject skill levels. Our findings highlight the value of these advanced force metrics as robust indicators of suturing performance, demonstrating their valuable potential for more accurate and objective skill assessment in surgical training. Clinical Relevance-The force metrics presented in this study analyze the intricacies of the widespread category of assessment in surgery, "respect for tissue", greatly benefiting surgical education with an improved evaluation of this aspect of suturing skill.
20 Mar 2024Submitted to TechRxiv
29 Mar 2024Published in TechRxiv