• DocumentCode
    539887
  • Title

    Movement recognition using the accelerometer in smartphones

  • Author

    Lau, Sian Lun ; David, Klaus

  • Author_Institution
    Dept. of Commun. Technol., Univ. of Kassel, Kassel, Germany
  • fYear
    2010
  • fDate
    16-18 June 2010
  • Firstpage
    1
  • Lastpage
    9
  • Abstract
    The area of activity recognition is essential for context-aware systems. Previous and current investigations demonstrate that the accelerometer is suitable for accurate movement and activity recognition. Since smartphones are used by people in their daily lives, they can be seen as an attractive sensor device for the purpose of activity recognition. In our work, experiments have been carried out to investigate the suitability of the built-in accelerometer by comparing the influences of classification algorithms, features and the combination of sampling rates and window sizes for features extraction have on the classification accuracy. Obtained results indicate that smartphones similar to the test device provide good accuracy in recognizing common movements.
  • Keywords
    accelerometers; feature extraction; gesture recognition; mobile radio; ubiquitous computing; accurate movement; activity recognition; attractive sensor device; built-in accelerometer; classification accuracy; classification algorithms; context-aware systems; features extraction; movement recognition; sampling rates; smartphones; Accelerometers; Accuracy; Classification algorithms; Context; Legged locomotion; Smart phones; activity recognition; classification; context-awareness; smartphone;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Future Network and Mobile Summit, 2010
  • Conference_Location
    Florence
  • Print_ISBN
    978-1-905824-16-8
  • Type

    conf

  • Filename
    5722356