An Innovative Comparative Analysis Approach for the Assessment of Laparoscopic Surgical Skills

Saiteja Malisetty, Hesham H. Ali, Elham Rastegari, Ka Chun Siu

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Over the past few decades, surgeon training has changed dramatically. Surgical skills are now taught in a surgical skills laboratory instead of the operating room. Simulation-based training helps medical students improve their skills, but it has not revolutionized clinical education. One critical barrier to reaching such a desired goal is the lack of reliable, robust, and objective methods for assessing the effectiveness of training sessions and the development of students. In this paper, we will develop a new comparative analysis approach that employs network models as the central concept in establishing a new assessment tool for the evaluation of the surgical skills of trainees as well as the training processes. The model is populated using participants electromyography data while performing a simulation task. Furthermore, using NASA Task Load Index score, participants’ subjective overload levels are analyzed to examine the impact of participants’ perception of their mental demand, physical demand, temporal demand, performance, effort, and frustration on how participants perform each simulation task. Obtained results indicate that the proposed approach enables us to extract useful information from the raw data and provides an objective method for assessment the of surgical simulation tasks and how the participants’ perception of task impacts their performance.

Original languageEnglish (US)
Pages (from-to)46-57
Number of pages12
JournalSurgeries (Switzerland)
Issue number1
StatePublished - Mar 2023


  • enrichment analysis
  • laparoscopic surgery
  • network models
  • simulation

ASJC Scopus subject areas

  • Surgery
  • Oral Surgery


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