• DocumentCode
    2771714
  • Title

    Cloud based activity monitoring system for health and sport

  • Author

    Rowlands, D.D. ; McNab, T. ; Laakso, L. ; James, Daniel A.

  • Author_Institution
    Centre for Wireless Monitoring & Applic., Griffith Univ., Brisbane, QLD, Australia
  • fYear
    2012
  • fDate
    10-15 June 2012
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper gives the concept, design, and implementation of an activity monitoring system that incorporates a database and a data analysis language as an integral part of the structure. The versatility of the design allows many different analysis techniques to be run on the extracted data. This forms the framework to allow different machine learning techniques to be applied to the data without the construction of separate dedicated systems. As an example application, this paper applies the system to determine some key features of a running based activity.
  • Keywords
    cloud computing; computerised monitoring; data analysis; data structures; database management systems; health care; learning (artificial intelligence); sport; cloud based activity monitoring system; data analysis language; database; health activity; machine learning techniques; running based activity; sport activity; Accelerometers; Data mining; Database systems; MATLAB; Machine learning; Monitoring; activity monitoring; database; health; inertial sensor; sport;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2012 International Joint Conference on
  • Conference_Location
    Brisbane, QLD
  • ISSN
    2161-4393
  • Print_ISBN
    978-1-4673-1488-6
  • Electronic_ISBN
    2161-4393
  • Type

    conf

  • DOI
    10.1109/IJCNN.2012.6252502
  • Filename
    6252502