The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/06d6bf50-4716-4c02-92fd-a75327ac03c5

Butler, Rick (2025): Python code to detect interaction of medical personnel with the operating table from surveillance videos. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/06d6bf50-4716-4c02-92fd-a75327ac03c5.v1

Categories

• Information Systems
• Computation Theory and Mathematics
• Information and Computing Sciences

Keywords

2D human poses Action recognition Operating table interaction Patient interaction Pose tracking Workflow analysis

Licence

MIT

Collection

• Video-based workflow monitoring for efficiency in the cardiac catheterization laboratory, an observational study

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by Rick Butler

Videos of about 40 gynaecological procedures were recorded from a distance in the Leiden University Medical Center.

The purpose was to identify differences in workflow between open, minimally invasive, and robot-assisted surgery.

This code repository was used to analyse human 2D poses extracted from the videos.

It looks at movement speed and position per individual to estimate whether they interact with the operating table or not.

Additionally, it contains code to measure interaction with the patient from Noldus annotation files.

History

• 2025-04-29 first online, published, posted

Publisher

4TU.ResearchData

Format

Settings/.ini, Settings/.json, Poses/.det2d.json, Requirements/.txt, Documentation/.md, Python/.py

Associated peer-reviewed publication

Towards automatic quantification of operating table interaction in operating rooms

Code hosting project url

https://gitlab.tudelft.nl/medical-process-engineering/patient-interaction-detection.git

Organizations

TU Delft, Faculty of Mechanical Engineering, Department of Biomechanical Engineering, Medical Process Engineering