A Model for Human Interruptability: Experimental Evaluation and Automatic Estimation from Wearable Sensors
Nicky Kern, Stavros Antifakos, Bernt Schiele, Adrian Schwaninger In 8th International Symposium on Wearable Computing (ISWC), Washington DC, USA, November 2004.

Abstract: For the estimation of user interruptability in wearable and mobile settings, we propose in in [8] to distinguish between the users' personal and social interruptability. In this paper, we verify this thesis with a user study on 24 subjects. Results show that there is a significant difference between social and personal interruptability. Further, we present a novel approach to estimate the social and personal interruptability of a user from wearable sensors. It is scalable for a large number of sensors, contexts, and situations and allows for online adaptation during run-time. We have developed a wearable platform, that allows to record and process the data from a microphone, 12 body-worn 3D acceleration sensors, and a location estimation. We have evaluated the approach on three different data sets, with a maximal length of two days.

Bibtex Record

@InProceedings{kern:iswc:04,
  author =       {N. Kern and S. Antifakos and B. Schiele and A. Schwaninger},
  title =        {A Model for Human Interruptability: Experimental Evaluation and 
                    Automatic Estimation from Wearable Sensors},
  booktitle =    {Proceedings of the 8th International Symposium on Wearable Computing (ISWC)},
  year =         {2004},
  address =      {Washington DC, USA},
  month =        {November}
}