• DocumentCode
    3684885
  • Title

    Clustering-based limb identification for pressure ulcer risk assessment

  • Author

    M. Baran Pouyan;M. Nourani;M. Pompeo

  • Author_Institution
    Quality of Life Technology Laboratory, The University of Texas at Dallas, Richardson, 75080, USA
  • fYear
    2015
  • Firstpage
    4230
  • Lastpage
    4233
  • Abstract
    Bedridden patients have a high risk of developing pressure ulcers. Risk assessment for pressure ulceration is critical for preventive care. For a reliable assessment, we need to identify and track the limbs continuously and accurately. In this paper, we propose a method to identify body limbs using a pressure mat. Three prevalent sleep postures (supine, left and right postures) are considered. Then, predefined number of limbs (body parts) are identified by applying Fuzzy C-Means (FCM) clustering on key attributes. We collected data from 10 adult subjects and achieved average accuracy of 93.2% for 10 limbs in supine and 7 limbs in left/right postures.
  • Keywords
    "Accuracy","Risk management","Conferences","Clustering algorithms","Pressure sensors","Head","Wounds"
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE
  • ISSN
    1094-687X
  • Electronic_ISBN
    1558-4615
  • Type

    conf

  • DOI
    10.1109/EMBC.2015.7319328
  • Filename
    7319328