The Wearable Computing Laboratory at the ETH in Zürich, Switzerland, led by Prof. G. Tröster is a large interdisciplinary research laboratory with about 15 PhD students and two post-docs and additional technical staff, with background in computer science, electrical engineering, signal processing, physics and textile engineering.

Our expertise in technology, algorithms and modelling allow us to define, design, implement and test state-of-the-art context-aware wearable and AmI environments. We capitalize on our expertise in the modelling of complex multi-modal AmI systems to design low-power context aware systems with adjustable power-accuracy tradeoffs in single sensor systems as well as in (wireless) sensor networks. Our expertise in technology allows us to devise systems for longterm recording of multi-modal contextual data (physical activity, context, and physiological parameters).

The group is involved in many internationally funded projects, covering topics such as context recognition comprising the design of body-worn sensor networks, reconfigurable wearable computing platform, gesture recognition using miniaturized camera and on-body sensors, focus-free retinal displays, low-power signal processing, context-recognition and processing in sensor networks, smart-textile engineering, with applications in industrial field, medical domain, well-being/comfort and fundamental research.

The laboratory has a large experience of EU research projects. In AMON we developed a health monitoring device worn at the hand joint. In MyHeart we develop sensors and methods to detect of nutrition phases to support healthy lifestyle. In DAPHNet we develop a context-aware platform for long-term recording of physical and physiological signals. In SEAT we develop a smart seat capable of improving passenger comfort by sensing and biofeedback. In WearIT@Work we develop wearable context-aware computer systems to empower workers in industrial manufacturing environments. In e-Sense and SENSEI we develop a framework for context recognition in dynamic and heterogeneous wireless sensors networks.