Abstract. In this work, algorithms are developed and evaluated to detect physical activities from data acquired using five small biaxial accelerometers worn simultaneously on di...
We are developing a personal activity recognition system that is practical, reliable, and can be incorporated into a variety of health-care related applications ranging from person...
Jonathan Lester, Tanzeem Choudhury, Gaetano Borrie...
Abstract. This paper describes how we recognize activities of daily living (ADLs) with our designed sensor device, which is equipped with heterogeneous sensors such as a camera, a ...
Abstract. PersonisAD, is a framework for building context-aware, ubiquitous applications: its defining foundation is a consistent mechanism for scrutable modelling of people, sens...
Mark Assad, David J. Carmichael, Judy Kay, Bob Kum...
Preserving one's uniquely customized computing environment as one moves to different locations is an enduring challenge in mobile computing. We examine why this capability is...
Mahadev Satyanarayanan, Michael Kozuch, Casey Helf...