• DocumentCode
    496160
  • Title

    Recognising activities of daily life through the usage of everyday objects around the home

  • Author

    Naeem, Usman ; Bigham, John

  • Author_Institution
    Sch. of Electron. Eng. & Comput. Sci., Queen Mary Univ. of London, London, UK
  • fYear
    2009
  • fDate
    1-3 April 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The integration of RFID sensors into everyday products has become a widespread solution for increasing efficiency in supply chain management. This has also led to a way of being able to monitor everyday activities in the home based on when and how these products are used, which is less intrusive than other monitoring approaches such as visual based systems. Monitoring activities in a home environment can be seen as a good way of analyzing behavior and tracking functional decline among elderly people. This paper describes a hierarchal approach for activity recognition using object usage data generated by everyday products used around the home. The motivation of this work is to allow people with early Alzheimer´s disease to have additional years of independent living before the disease reaches a stage where the person is fully dependable on someone else.
  • Keywords
    geriatrics; handicapped aids; health care; patient care; pattern recognition; radiofrequency identification; Alzheimer disease; RFID sensor; activity recognition; daily life; everyday object; everyday product; home environment; object usage data; supply chain management; visual based system; Alzheimer´s disease; Computer science; Computer vision; Costs; Monitoring; Object detection; Radiofrequency identification; Senior citizens; Transponders; Wearable sensors; Alzheimer´s Disease; Hierarchal Activities of Daily Life; Object Usage; Task Sequences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pervasive Computing Technologies for Healthcare, 2009. PervasiveHealth 2009. 3rd International Conference on
  • Conference_Location
    London
  • Print_ISBN
    978-963-9799-42-4
  • Electronic_ISBN
    978-963-9799-30-1
  • Type

    conf

  • DOI
    10.4108/ICST.PERVASIVEHEALTH2009.6059
  • Filename
    5191150