This project focuses on mobile sensing for health applications such as monitoring of sleep, stress and social routines. Our work is developing a new approach called non-intrusive health monitoring, which emphasizes passive sensing of user behavior in a privacy-preserving and non-intrusive manner. Our approaches combine mobile sensing, systems, and machine learning for continuous monitoring and to derive health insights. Ongoing work focuses on the following topics:
- Passive wifi sensing of sleep
- Privacy-preserving health monitoring
- Monitoring of group and social interactions
Representative Publications
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SleepLess: personalized sleep monitoring using smartphones and semi-supervised learning
Priyanka Mary Mammen, Camellia Zakaria, and Prashant Shenoy.
Springer-CSI Transactions on ICT, 2023.
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SleepMore: Inferring Sleep Duration at Scale with Multi-Device WiFi Sensing
Camellia Zakaria, Yilmaz Gizem, Priyanka Mammen, Michael Chee, Prashant Shenoy, and Rajesh Balan.
In Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), 2022.
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WiSleep: Scalable Sleep Monitoring and Analytics Using Passive WiFi Sensing
Priyanka Mary Mammen, Camellia Zakaria, Tergel Molom-Ochir, Amee Trivedi, Prashant J. Shenoy, and Rajesh Balan.
arXiv -
W4-Groups: Modeling the Who, What, When and Where of Group Behavior via Mobility Sensing
Akanksha Atrey, Camellia Zakaria, Prashant Shenoy, and Rajesh Balan.
In Proceedings of the ACM on Human-Computer Interaction (PACM HCI). Also Proc. ACM CSCW 2024.
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