Context – Aware Multi – Modal Notification for Wearable Computing
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We propose to use context information obtained from body–worn sensors to mediate notifications for a wearable computer. In particular we introduce a model which uses two axes, namely personal and social interruptability of the user in order to decide both whether or not to notify the user and to decide which notification modality to use. Rather than to model and recognize the complete context of the user we argue that personal and social interruptability can be derived directly from various sensors by the combination of tendencies. First experimental results show the feasability of the approach using acceleration, audio, and location sensors. The investigation of user interface issues are the immediate next steps in our work. 1 Background of the Author Nicky Kern is a PhD student since October 2001 in the Perceptual Computing and Computer Vision Group (PCCV) at ETH Zurich. His work is supervised by Prof. Bernt Schiele. His research focuses on using non–trivial context information obtained from body–worn sensors for context– aware applications (see [2]). In his current work he tries to use context information to mediate notifications from various sources to the user of the wearable computer.
[1] Albrecht Schmidt,et al. Multi-sensor Activity Context Detection for Wearable Computing , 2003, EUSAI.
[2] Christopher G. Atkeson,et al. Predicting human interruptibility with sensors: a Wizard of Oz feasibility study , 2003, CHI '03.