MURAL - Maynooth University Research Archive Library

    A vision-based system for automatic hand washing quality assessment

    Llorca, David Fernández and Parra, Ignacio and Sotelo, Miguel Ángel and Lacey, Gerard (2011) A vision-based system for automatic hand washing quality assessment. Machine Vision and Applications, 22 (2). pp. 219-234. ISSN 0932-8092

    Download (1MB) | Preview

    Share your research

    Twitter Facebook LinkedIn GooglePlus Email more...

    Add this article to your Mendeley library


    Hand washing is a critical activity in preventing the spread of infection in health-care environments and food preparation areas. Several guidelines recommended a hand washing protocol consisting of six steps that ensure that all areas of the hands are thoroughly cleaned. In this paper, we describe a novel approach that uses a computer vision system to measure the user’s hands motions to ensure that the hand washing guidelines are followed. A hand washing quality assessment system needs to know if the hands are joined or separated and it has to be robust to different lighting conditions, occlusions, reflections and changes in the color of the sink surface. This work presents three main contributions: a description of a system which delivers robust hands segmentation using a combination of color and motion analysis, a single multi-modal particle filter (PF) in combination with a k-means-based clustering technique to track both hands/arms, and the implementation of a multi-class classification of hand gestures using a support vector machine ensemble. PF performance is discussed and compared with a standard Kalman filter estimator. Finally, the global performance of the system is analyzed and compared with human performance, showing an accuracy close to that of human experts.

    Item Type: Article
    Keywords: Hand washing; Bi-manual gesture recognition; Kalman filter; Particle filter; Skin detection; Tracking; Multi-class SVM;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 16896
    Identification Number:
    Depositing User: Gerard Lacey
    Date Deposited: 30 Jan 2023 15:48
    Journal or Publication Title: Machine Vision and Applications
    Publisher: Springer Verlag
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

    Repository Staff Only(login required)

    View Item Item control page


    Downloads per month over past year

    Origin of downloads