• DocumentCode
    2445496
  • Title

    Estimating Personal Energy expenditure with location data

  • Author

    Hay, Simon ; Rassia, Stamatina Th ; Beresford, Alastair R.

  • Author_Institution
    Comput. Lab., Univ. of Cambridge, Cambridge, UK
  • fYear
    2010
  • fDate
    March 29 2010-April 2 2010
  • Firstpage
    304
  • Lastpage
    309
  • Abstract
    Human inactivity has been associated with the incidence of a number of health conditions and chronic diseases, while our increasing energy consumption is a well-documented problem. A Personal Energy Meter might help identify areas for improvement in our lifestyles that would benefit both our personal health and the global environment. As one strand of this, we explore the possibility of estimating our own energy expenditure from movement traces provided by location systems. This technique offers a number of advantages over accepted accelerometer-based devices.We validate a model which we then apply to analyse the physical activity and working patterns of a total of 60 individuals spread across two separate offices.
  • Keywords
    accelerometers; diseases; health care; accelerometer-based devices; chronic diseases; energy consumption; health conditions; human inactivity; location data; movement traces; personal energy expenditure estimation; personal energy meter; personal health; physical activity; working patterns; Biomedical measurements; Diseases; Energy measurement; Extraterrestrial measurements; Humans; Laboratories; Medical services; Monitoring; Pervasive computing; Watthour meters; biomedical measurements; energy measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pervasive Computing and Communications Workshops (PERCOM Workshops), 2010 8th IEEE International Conference on
  • Conference_Location
    Mannheim
  • Print_ISBN
    978-1-4244-6605-4
  • Electronic_ISBN
    978-1-4244-6606-1
  • Type

    conf

  • DOI
    10.1109/PERCOMW.2010.5470650
  • Filename
    5470650