Abstract
Embedded assessment leverages the capabilities of pervasive computing to advance early detection of health conditions. In this approach, technologies embedded in the home setting are used to establish personalized baselines against which later indices of health status can be compared. Our ethnographic and concept feedback studies suggest that adoption of such health technologies among end users will be increased if monitoring is woven into preventive and compensatory health applications, such that the integrated system provides value beyond assessment. We review health technology advances in the three areas of monitoring, compensation, and prevention. We then define embedded assessment in terms of these three components. The validation of pervasive computing systems for early detection involves unique challenges due to conflicts between the exploratory nature of these systems and the validation criteria of medical research audiences. We discuss an approach for demonstrating value that incorporates ethnographic observation and new ubiquitous computing tools for behavioral observation in naturalistic settings such as the home.
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Morris, M., Intille, S.S., Beaudin, J.S. (2005). Embedded Assessment: Overcoming Barriers to Early Detection with Pervasive Computing. In: Gellersen, H.W., Want, R., Schmidt, A. (eds) Pervasive Computing. Pervasive 2005. Lecture Notes in Computer Science, vol 3468. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11428572_20
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DOI: https://doi.org/10.1007/11428572_20
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