A variety of legacy and emerging health applications are designed to monitor sensed information about a person's physiological signals over time. Such applications include systems for tracking heart conditions that have been in use by cardiologists for decades to recent prototypes for monitoring elders in cognitive decline. This thesis focuses on addressing the challenges inherent in an interactive monitoring system - how and when to interact with a user. This research aims to improve these systems in two main ways: 1) explore how to interact through social-emotional, relational dialogue, and 2) explore when to interact by adjusting the timing of these interruptions. An interactive, health application has been developed for data collection, annotation, and feedback that is part of a longer-term research plan for gathering data to understand more about stress, the physiological signals involved in its expression, and the interplay between stress and interruptibility. The system has been developed on a mobile platform and uses affect and interruption-sensitive strategies to engage users and allow for real-time annotation of stress, activity and timing information through text and audio input. The platform supports continuous, wireless, and non-intrusive collection of heart signal data, accelerometer, and pedometer information, as well as automatic labeling of location information from context beacons. This system is the first of its kind to be affect and interruption-responsive - to use physiological data to adjust the timing of interruptions, as well as to adaptively respond with dialogue and relational strategies that specifically address the user's stress levels and the disruption the device may be incurring upon the user.
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