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ABSTRACT
Fitness monitoring is a fundamental service in pervasive healthcare, but finding a balance between usability and privacy is a hard challenge. To lessen users' anxieties in privacy concerns, we propose a new way of identification by only utilizing imprecise biometrics and existing information. Our solution is "hassle free" because it maintains the devices' original user interface without adding additional sensors and sacrificing user privacy. We demonstrate this idea with a fitness monitoring system for the healthy individuals in a workplace. The system uses collected physiological information (weight, blood pressure and heart rate) and context information (computer network activity) to identify a user. Our experiments show that we can achieve a correct user identification of up to 87%. We believe that our solution can serve as an easy addition to the simple interfaces of current technology by enhancing them with smart algorithms.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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CITED BY 3
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Yi Wang , Jialiu Lin , Murali Annavaram , Quinn A. Jacobson , Jason Hong , Bhaskar Krishnamachari , Norman Sadeh, A framework of energy efficient mobile sensing for automatic user state recognition, Proceedings of the 7th international conference on Mobile systems, applications, and services, June 22-25, 2009, Kraków, Poland
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Janani C. Sriram , Minho Shin , Tanzeem Choudhury , David Kotz, Activity-aware ECG-based patient authentication for remote health monitoring, Proceedings of the 2009 international conference on Multimodal interfaces, November 02-04, 2009, Cambridge, Massachusetts, USA
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