Hand-Washing Video Dataset Annotated According to the World Health Organization’s Hand-Washing Guidelines

Martins Lulla, Aleksejs Rutkovskis, Andreta Slavinska, Aija Vilde, Anastasija Gromova, Maksims Ivanovs, Ansis Skadins, Roberts Kadikis, Atis Elsts (Coresponding Author)

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)
5 Downloads (Pure)


Washing hands is one of the most important ways to prevent infectious diseases, including COVID-19. The World Health Organization (WHO) has published hand-washing guidelines. This paper presents a large real-world dataset with videos recording medical staff washing their hands as part of their normal job duties in the Pauls Stradins Clinical University Hospital. There are 3185 hand-washing episodes in total, each of which is annotated by up to seven different persons. The annotations classify the washing movements according to the WHO guidelines by marking each frame in each video with a certain movement code. The intention of this “in-the-wild” dataset is two-fold: to serve as a basis for training machine-learning classifiers for automated hand-washing movement recognition and quality control, and to allow to investigation of the real-world quality of washing performed by working medical staff. We demonstrate how the data can be used to train a machine-learning classifier that achieves classification accuracy of 0.7511 on a test dataset.
Original languageEnglish
Article number38
Number of pages6
Issue number4
Publication statusPublished - 7 Apr 2021


  • hand-washing
  • hands
  • hand movement
  • video dataset
  • neural network

Field of Science*

  • 1.2 Computer and information sciences
  • 2.6 Medical engineering
  • 3.3 Health sciences

Publication Type*

  • 1.1. Scientific article indexed in Web of Science and/or Scopus database


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