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A model for human interruptability: experimental evaluation and automatic estimation from wearable sensors

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons84420

Schwaninger,  A
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Kern, N., Antifakos S, Schiele, B., & Schwaninger, A. (2004). A model for human interruptability: experimental evaluation and automatic estimation from wearable sensors. In Eighth IEEE International Symposium on Wearable Computers (ISWC '04) (pp. 158-165). Los Alamitos, CA, USA: IEEE Computer Society.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-D767-6
Zusammenfassung
For the estimation of user interruptability in wearable and mobile settings, we propose in [Context-aware notfication for wearable computing] 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.