Stephen Intille
Professor, Interdisciplinary with Bouvé College of Health Sciences
Research interests
- Personal health informatics
- Interactive, mobile sensing
- Machine learning
- Behavioral theory and measurement
Education
- PhD in Media Arts and Sciences, Massachusetts Institute of Technology
- SM in Media Arts and Sciences, Massachusetts Institute of Technology
- BSE in Computer Science and Engineering, University of Pennsylvania
Biography
Stephen Intille is a professor in the Khoury College of Computer Sciences and the Bouvé College of Health Sciences at Northeastern University, based in Boston.
Intille's research focuses on the development of novel health care technologies that incorporate ideas from ubiquitous computing, user-interface design, pattern recognition, behavioral science, and preventive medicine. He is interested in human–computer interface technologies that measure and motivate health-related behaviors, and especially how algorithms that recognize everyday activity can drive the development of interactive technologies that support healthy aging and well-being. Intille also analyzes mobile technologies that permit longitudinal measurement of health behaviors and areas of human activity.
Intille has published research on computational stereo depth recovery, real-time and multi-agent tracking, activity recognition, perceptually-based interactive environments, and technology for health care. He has been the principal investigator on sensor-enabled health technology grants from the NSF, the NIH, private foundations, and industry.
In 1999, Intille received his PhD from MIT, where he worked on computational vision at the MIT Media Lab for five years. After 10 years as technology director of the House_n Consortium at MIT, Intille joined Northeastern in 2010 to establish a new interdisciplinary PhD program in personal health informatics.
Labs and groups
Recent publications
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Collecting Self-reported Physical Activity and Posture Data Using Audio-based Ecological Momentary Assessment
Citation: Ha Le, Rithika Lakshminarayanan, Jixin Li, Varun Mishra , Stephen S. Intille. (2024). Collecting Self-reported Physical Activity and Posture Data Using Audio-based Ecological Momentary Assessment Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 8, 111:1-111:35. https://doi.org/10.1145/3678584 -
Talk2Care: An LLM-based Voice Assistant for Communication between Healthcare Providers and Older Adults
Citation: Ziqi Yang, Xuhai Xu, Bingsheng Yao, Ethan Rogers, Shao Zhang, Stephen S. Intille, Nawar Shara, Guodong Gordon Gao, Dakuo Wang. (2024). Talk2Care: An LLM-based Voice Assistant for Communication between Healthcare Providers and Older Adults Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 8, 73:1-73:35. https://doi.org/10.1145/3659625 -
Exploring Opportunities to Improve Physical Activity in Individuals with Spinal Cord Injury Using Context-Aware Messaging
Citation: Rithika Lakshminarayanan, Alexandra Canori, Aditya Ponnada, Melissa Nunn, Mary Schmidt Read, Shivayogi V. Hiremath, Stephen S. Intille. (2022). Exploring Opportunities to Improve Physical Activity in Individuals with Spinal Cord Injury Using Context-Aware Messaging Proc. ACM Hum. Comput. Interact., 6, 1-27. https://doi.org/10.1145/3555628 -
Grand Challenges
Citation: Sarah Clinch, Stephen S. Intille. (2022). Grand Challenges IEEE Pervasive Comput., 21, 7-8. https://doi.org/10.1109/MPRV.2022.3198813 -
Contextual Biases in Microinteraction Ecological Momentary Assessment (μEMA) Non-response
Citation: Aditya Ponnada, Jixin Li, Shirlene Wang, Wei-Lin Wang, Bridgette Do, Genevieve F. Dunton, Stephen S. Intille. (2022). Contextual Biases in Microinteraction Ecological Momentary Assessment (μEMA) Non-response Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 6, 26:1-26:24. https://doi.org/10.1145/3517259 -
Techno-Spiritual Engagement: Mechanisms for Improving Uptake of mHealth Apps Designed for Church Members 130-138
Citation: Hye Sun Yun, Shou Zhou, Everlyne Kimani, Stefan Olafsson, Teresa K. O'Leary, Dhaval Parmar, Jessica A. Hoffman, Stephen S. Intille, Michael K. Paasche-Orlow, Timothy W. Bickmore. (2022). Techno-Spiritual Engagement: Mechanisms for Improving Uptake of mHealth Apps Designed for Church Members 130-138 IUI Workshops, 130-138. http://ceur-ws.org/Vol-3124/paper13.pdf -
Signaligner Pro: A Tool to Explore and Annotate Multi-day Raw Accelerometer Data
Citation: A. Ponnada et al., "Signaligner Pro: A Tool to Explore and Annotate Multi-day Raw Accelerometer Data," 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), 2021, pp. 475-480, doi: 10.1109/PerComWorkshops51409.2021.9431110. -
Classifier personalization for activity recognition using wrist accelerometers
Citation: A. Mannini and S. S. Intille, "Classifier Personalization for Activity Recognition Using Wrist Accelerometers," in IEEE Journal of Biomedical and Health Informatics, vol. 23, no. 4, pp. 1585-1594, July 2019. -
The Association Between Engagement and Weight Loss Through Personal Coaching and Cell Phone Interventions in Young Adults: Randomized Controlled Trial
Citation: P.-H. Lin, S. Grambow, S. Intille, J. Gallis, T. Lazenka, H. Bosworth, C. Voils, G. Bennett, B. Batch, J. Allen, L. Corsino, C. Tyson, and L. Svetkey, "The association between engagement and weight loss through personal coaching and cell phone interventions in young adults: Randomized controlled trial," JMIR mHealth and uHealth, vol. 6, p. e10471, 2018. -
Microinteraction ecological momentary assessment response rates: Effect of microinteractions or the smartwatch?
Citation: A. Ponnada, C. Haynes, D. Maniar, J. Manjourides, and S. Intille, "Microinteraction ecological momentary assessment response rates: Effect of microinteractions or the smartwatch?," Proc. of the ACM Journal on Interactive, Mobile, Wearable, and Ubiquitous Technology vol. 1, 2017 -
Activity recognition in youth using single accelerometer placed at wrist or ankle
Citation: A. Mannini, M. Rosenberger, W. L. Haskell, A. M. Sabatini, and S. S. Intille
Related News
Current PhD Students
Previous PhD Students
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Aditya Ponnada
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Qu Tang