• DocumentCode
    2278193
  • Title

    Improving the efficacy of motion analysis as a clinical tool through artificial intelligence techniques

  • Author

    Simon, S. ; Johnson, K.

  • Author_Institution
    Beth Israel Hosp., New York, NY, USA
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    23
  • Lastpage
    29
  • Abstract
    Technology supporting human motion analysis has advanced dramatically and yet its clinical application has not grown at the same pace. The issue of its clinical value is related to the length of time it takes to do an interpretation, the cost, and the quality of the interpretation. Techniques from artificial intelligence such as neural networks and knowledge-based systems can help overcome these limitations. Here, the authors give an overview of these techniques and describe current research efforts that apply these techniques in the field of human motion analysis
  • Keywords
    artificial intelligence; biomedical measurement; decision support systems; gait analysis; knowledge based systems; medical diagnostic computing; neural nets; paediatrics; reviews; artificial intelligence techniques; clinical application; clinical tool; cost; human motion analysis; interpretation quality; technology supporting human motion analysis; Anthropometry; Artificial intelligence; Artificial neural networks; Biomedical informatics; Costs; Hospitals; Humans; Knowledge based systems; Motion analysis; Orthopedic surgery;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pediatric Gait, 2000. A new Millennium in Clinical Care and Motion Analysis Technology
  • Conference_Location
    Chicago, IL
  • Print_ISBN
    0-7803-6469-4
  • Type

    conf

  • DOI
    10.1109/PG.2000.858871
  • Filename
    858871