Quantified Self: R tools for the analysis of personal data to improve health

JP Snow will be presenting.

Abstract

"Quantified Self" involves tracking personal data to improve fitness,
health and personal performance. The data and analytic packages available
in R make personal quantification even more valuable. Participants in this
session will learn how to create a personal dashboard and see how how
machine learning can be used to determine optimal sleep factors, all via R.
Other concepts to be covered will include:

• Flexdashboard package for dashboard development
• ggplot techniques, including ggplotly for more interactivity
• Accessing personal data directly from R into Fitbit’s web API
• Using scatter charts, box plots and decision tree methods for analysis

JP Snow has been involved in analytics roles in financial services
throughout his twenty-year career. He currently leads Institutional
Analytics & Client Loyalty at Charles Schwab. A few years ago he started
tracking fitness metrics and realized R had substantial advantages over
Excel. He also leads the Denver Quantified Self Meet-Up group.