Context-Aware Experience Sampling for the Design and Study of Ubiquitous Technologies
John Rondoni · 2003
As computer systems become ubiquitously embedded in our environment, computer applications must be increasingly aware of user context. In order for these systems to interact with users in a meaningful and unobtrusive way, such as delivering important reminders at an appropriate time, their interfaces must be contextually-aware. This vision of future computer systems and the insight that the implementation of contextually-aware systems requires contextually-aware analysis and development tools has motivated the two primary contributions of this work. First, a Context-Aware Experience Sampling Tool has been designed, implemented, and tested. Second, this tool has been used to develop an algorithm that can detect transitions between human activities in office-like environments from planar accelerometer and heart rate data. The Context-Aware Experience Sampling Tool (CAES) is a program for Microsoft Pocket PC devices capable of gathering qualitative data, in the form of an electronic questionnaire, and quantitative data, in the form of sensor readings, from subjects. This system enables contextually-aware user interactions via real-time modification of the electronic questionnaire based on sensor readings. CAES is publicly available to researchers and is actively being used and evaluated in several studies at MIT. The algorithm capable of detecting transitions between human activities was evaluated on a data set collected from nineteen subjects with CAES and successfully differentiated continuous activities from activity transitions with 93.5% accuracy. This detector could be used to improve CAES and to develop applications capable of proactively presenting users with information at appropriate times. Thesis Supervisor: Stephen Intille Title: Changing Places / House n Technology Director MIT Department of Architecture