Lifestreams: a modular sense-making toolset for identifying important patterns from everyday life

Abstract

Smartphones can capture diverse spatio-temporal data about an individual; including both intermittent self-report, and continuous passive data collection from onboard sensors and applications. The resulting <b>personal data streams</b> can support powerful inference about the user's state, behavior, well-being and environment. However making sense and… (More)
DOI: 10.1145/2517351.2517368

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Cite this paper

@inproceedings{Hsieh2013LifestreamsAM, title={Lifestreams: a modular sense-making toolset for identifying important patterns from everyday life}, author={Cheng-Kang Hsieh and Hongsuda Tangmunarunkit and Faisal Alquaddoomi and John Jenkins and Jinha Kang and Cameron Ketcham and Brent Longstaff and Joshua Selsky and Betta Dawson and Dallas Swendeman and Deborah Estrin and Nithya Ramanathan}, booktitle={SenSys}, year={2013} }