March 2012
Intermediate to advanced
120 pages
3h 5m
English
Content preview from Enabling Programmable Self with HealthVaultBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Chapter 4. Using the HealthVault Data Ecosystem for Self-Tracking
“Data is a precious thing and will last longer than the systems themselves.”
—
The Quantified Self (http://quantifiedself.com/about/) community enables self-knowledge through self-tracking. Self-tracking, when powered by appropriate data analysis, has been proven to trigger behavioral change. The act of self-tracking creates awareness and feedback. The hunger for, and success of, self-knowledge is evident from the growing number of self-quantifiers (currently 6,000+ in 41 cities and 14 countries).
Self-knowledge is possible only with a substantial collection of data about oneself. HealthVault provides more than 80 granular data types that enable tracking data regarding everything from daily exercise to genome sequences. In this chapter, we will build upon the understanding of the HealthVault API covered in Chapter 3 and extend it to develop a data-intensive self-quantifying application. Through the Quantified Self application, we will gain an understanding of HealthVault data types and application development.
A Self-Experimentation Application
In Chapter 1 we analyzed weight data, and in Chapter 2 we worked with sleep information and correlated it with exercise. HealthVault offers a data type for tracking emotional state and daily dietary intake as well. Let’s consider building a simple Quantified Self utility that helps a user keep track of his emotional state, daily dietary intake, weight, sleep, and exercise. ...
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