Janani Sriram and Minho Shin and David Kotz and Anand Rajan and Manoj Sastry and Mark Yarvis. Challenges in Data Quality Assurance in Pervasive Health Monitoring Systems. In Trusted Computing 2008, July, 2008. Accepted for publication.

Abstract: Wearable, portable, and implantable medical sensors have ushered in a new healthcare paradigm in which patients can take greater responsibility and caregivers can make well-informed, timely decisions. Health-monitoring systems built on sensors have a huge potential benefit to the quality of healthcare and quality of life for many people: patients with chronic medical conditions (e.g., diabetes), people seeking to change unhealthy behavior (e.g., losing weight or quitting smoking), or athletes wishing to track conditioning and performance. To be effective, however, these systems must provide assurances of sensor data quality. While no system can guarantee data quality, it is valuable for a system to annotate data with a measure of confidence. In this paper, we take a deeper look at potential health-monitoring usage scenarios and provide a holistic examination of the research challenges required to assess the quality of sensor data in health-monitoring systems.

Keywords: pervasive computing, healthcare, medical, sensors, sensor network, security, privacy, integrity, data assurance

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Copyright © 2008 by the authors.