ArticleThe international journal of medical robotics + computer assisted surgery : MRCAS2022
Analysis of executional and procedural errors in dry-lab robotic surgery experiments.
Article in The international journal of medical robotics + computer assisted surgery : MRCAS, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 0 citations in OpenAlex.
- Evaluation of objective tools and artificial intelligence in robotic surgery technical skills assessment: a systematic review.The British journal of surgery · 2024Pooled it
- MiDAS: A Multimodal Data Acquisition System and Dataset for Robot-Assisted Minimally Invasive Surgery.The international journal of medical robotics + computer assisted surgery : MRCAS · 2026Article
- Ambiguity in robotic surgical instruction: lessons from remote and in-person simulation.Advances in health sciences education : theory and practice · 2025Article
- Analysis of executional and procedural errors in dry-lab robotic surgery experiments.The international journal of medical robotics + computer assisted surgery : MRCAS · 2022Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
backgroundAnalysing kinematic and video data can help identify potentially erroneous motions that lead to sub-optimal surgeon performance and safety-critical events in robot-assisted surgery.
methodsWe develop a rubric for identifying task and gesture-specific executional and procedural errors and evaluate dry-lab demonstrations of suturing and needle passing tasks from the JIGSAWS dataset. We characterise erroneous parts of demonstrations by labelling video data, and use distribution similarity analysis and trajectory averaging on kinematic data to identify parameters that distinguish erroneous gestures.
resultsExecutional error frequency varies by task and gesture, and correlates with skill level. Some predominant error modes in each gesture are distinguishable by analysing error-specific kinematic parameters. Procedural errors could lead to lower performance scores and increased demonstration times but also depend on surgical style.
conclusionsThis study provides insights into context-dependent errors that can be used to design automated error detection mechanisms and improve training and skill assessment.
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Registered trials
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