Activity Recognition for Everyday Life on Mobile Phones

  • Authors:

  • Gerald Bieber;Jörg Voskamp;Bodo Urban

  • Affiliations:

  • Fraunhofer-Institut fuer Graphische Datenverarbeitung, Rostock, Germany;Fraunhofer-Institut fuer Graphische Datenverarbeitung, Rostock, Germany;Fraunhofer-Institut fuer Graphische Datenverarbeitung, Rostock, Germany

  • Venue:
  • UAHCI '09 Proceedings of the 5th International on ConferenceUniversal Access in Human-Computer Interaction. Part II: Intelligent and Ubiquitous Interaction Environments
  • Year:
  • 2009

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Abstract

Mobile applications for activity monitoring are regarded as a high potential field for efficient improvement of health care solutions. The measurement of physical activity within every-day conditions should be as easy as using an automatic weighing machine. Up to now physical activity monitoring required special sensor devices and are not suitable for an every day usage. Movement pattern recognition based on acceleration data enables the usage of standard mobile phones for measurement of physical activity. Now, just by carrying a standard phone in a pocket, the device provides information about the type, intensity and duration of the performed activity. Within the project DiaTrace, we developed the method and algorithm to detect activities like walking, jumping, running, cycling or car driving. Based on activity measurement, this application also calculates the consumed calories over the day, shares activity progress with friends or family and might deliver details about different kinds of transportation during a business trip. The DiaTrace application can easily used today by standard phones which are already equipped with the required sensors.