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Author Kay, Matthew
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Abstract Increasingly, personal health data can be tracked and integrated from numerous streams quickly and easily, but our feedback lingers in the land of "show the user a graph and hope." How can we help people make sense of personal health data?
Description Affiliation: University of Washington (Kay, Matthew)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2015-12-30
Publisher Place New York
Journal XRDS: Crossroads, The ACM Magazine for Students (XRDS)
Volume Number 21
Issue Number 2
Page Count 6
Starting Page 32
Ending Page 37


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Source: ACM Digital Library