Stephen Intille, Ph.D.
Professor (Khoury & Bouvé)
Lab/Research Center Affiliation: mHealth Research Group
Description of Subject Interest and Expertise: I am exploring the development and evaluation of personal, behavioral health informatics – how sensor data acquired throughout everyday life from smartwatches, smartphones, wearable monitors, and in-home sensors might be used to improve wellness via novel human-computer interfaces. This research involves merging ideas from the computer science subfields of human-computer interaction, applied pattern recognition and machine learning, and computational sensing and artificial intelligence with ideas from behavioral science, behavioral medicine, social psychology, and preventive medicine. I am particularly interested in how algorithms that reliably recognize everyday activities and habits can drive the development of interactive preventive health tools that could ultimately be applied at the population scale in a cost-effect manner. Within computer science, this requires developing new user-driven activity detection algorithms that use context and common-sense information, without requiring large training sets; a focus is on person-in-the-loop interactive, explanatory behavior recognition interfaces. Within preventive medicine, this requires building and deploying pilot systems and demonstrating that the technology has a meaningful impact on health outcomes; a focus is on demonstrating that technology can support long-term engagement with behavior change and maintenance. As part of this work, my research group has worked to create new tools that can be used to both measure and motivate behavior change using novel sensor-based technologies. I have a somewhat related interest in facilitating active transportation via bicycling. This is an interdisciplinary project that has components connected to mobile technology, transportation, behavior change, physical activity and health, and public policy and law.
Description of Current Project/Scholarly Endeavor: Our research group works on a variety of projects related to detecting human behavior and habits from smartphone and smartwatch data using algorithms, and motivating behavior change with novel human-computer interfaces.
Profile of Student Researcher: Students who wish to work on sensing projects should have significant coding and/or user interface design experience, with an interest in health. Students who wish to work on the active transportation via bicycling project should be passionate about health bicycling, but otherwise could have interdisciplinary experience ranging from computer science to public health to public policy and law.
Email: s.intille@northeastern.edu