Closing the Sensing-to-Intervention Loop for Behavioral Health

Abstract

Mobile and ubiquitous computing research has led to new techniques for cheaply, accurately, and continuously collecting data on human behavior that include detailed measurements of physical activities, mobility, social interactions, mood, sleep quality and more. Continuous and unobtrusive sensing of behaviors has tremendous potential to support the lifelong management of mental health by: (1) acting as an early warning system to detect changes in mental well-being, (2) delivering personalized interventions to patients when and where they need them, and (3) significantly accelerating patient and physician understanding of changes in mental health in real-time. In this talk, I will give an overview of our work on turning sensor-enabled mobile devices into well-being monitors and instruments for administering real-time/real-place interventions.