• DocumentCode
    1553990
  • Title

    Wearable Computing

  • Author

    Roggen, Daniel ; Magnenat, Stephane ; Waibel, Markus ; Troster, G.

  • Author_Institution
    Wearable Comput. Lab., Swiss Fed. Inst. of Technol., Zürich, Switzerland
  • Volume
    18
  • Issue
    2
  • fYear
    2011
  • fDate
    6/1/2011 12:00:00 AM
  • Firstpage
    83
  • Lastpage
    95
  • Abstract
    Driven by the rapid progress in mobile sensing and computing, wearable computing has developed powerful methods for the automatic recognition, categorization, and labeling of human actions and behaviors from sensor data. Because of the stringent requirements dictated by user acceptance, these methods are typically robust to human variability and hardware-dependent factors, including variability in sensor type and placement. This makes them a potentially useful tool for the automatic recognition and labeling of robot behaviors and may lead to new opportunities for research in robotics. We detail three domains in which the methods of activity recognition can play a role in robotics.
  • Keywords
    Internet; gesture recognition; human-robot interaction; mobile computing; unsupervised learning; wearable computers; World Wide Web; activity recognition; hardware-dependent factors; human action categorization; human action labeling; human action recognition; human behavior; human variability; human-robot interaction; large-scale activity data set annotation; mobile computing; mobile sensing; robot behaviors; robot self-learning; robotics; sensor data; user acceptance; wearable computing; Data systems; Human factors; Robot kinematics; Robot sensing systems; Sensor phenomena and characterization; Wearable computers;
  • fLanguage
    English
  • Journal_Title
    Robotics & Automation Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9932
  • Type

    jour

  • DOI
    10.1109/MRA.2011.940992
  • Filename
    5876217