SoftwareApplication
name: patient-interaction-detection
description: Python code to detect interaction of medical personnel with the operating table from surveillance videos
description: 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.
code repository: https://data.4tu.nl/v3/datasets/e5a1880f-f153-4fd0-8335-db4df7e71d7f.git
author: https://orcid.org/0000-0002-3202-9401
keywords: Action recognition
keywords: Workflow analysis
keywords: Patient interaction
keywords: 2D human poses
keywords: Pose tracking
keywords: Operating table interaction
programming language: JSON
programming language: Markdown
programming language: Other
programming language: Python
programming language: large-text-file
license:
  creative work: creativeWork
    name: MIT
reference publication: s11548-025-03363-8

https://orcid.org/0000-0002-3202-9401
type: Person
given name: Rick
family name: Butler
name: Rick Butler

s11548-025-03363-8
type: ScholarlyArticle
name: Towards automatic quantification of operating table interaction in operating rooms
pagination: 1999-2010
url: https://doi.org/10.1007%2Fs11548-025-03363-8