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The Beginner’s Guide to Self-Tracking & Analysis

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‘An investment in knowledge pays the best interest.’ – Ben Franklin

Self-tracking – or personal analytics as some call it – is a relatively new phenomenon brought about by the ubiquity of cheap sensor technology and the internet.  It’s a space that’s just now coming into its own thanks to the tech getting cheaper and lots of interested, data-driven geeks finding each other on the net and exchanging ideas.

The potential impact of self-tracking on personal health and overall well being could someday rival the discovery of penicillin – seriously – and we’re just at the beginning of what’s going to be a huge wave of self-improvement and individualized health care based on self-tracking and analysis.

I’ve recently entered the world of self-tracking… and there’s no going back.  My weight, body fat percentage, running speed and distance, calories burned, sleep patterns, investments, genetic predispositions, daily routines, mood, and even commute times are tracked and analyzed.  Sound a little excessive?  Maybe.  But only because it’s still not 100% automatic.  But it’s really, really close to being “set it and forget it”, and for me, the benefits far outweigh the few minutes I spend each day tracking things.

What is Self-Tracking?

The basic concept behind self-tracking is simple: our ability to determine cause and effect through our memory or experience alone is inherently faulty.  It’s tough enough for most of us to remember a birthday or anniversary.  Ask us to calculate how many calories we burned yesterday and how that affected our sleep last night and our blood pressure will rise – and we won’t even be able to detect that in order to prevent it from happening in the future! 

Our minds play games with us… they trick us into seeing and believing things that aren’t there in order to "protect us".  We can rationalize most anything we do or say (science shows this) which means deciding not to exercise because we’re busy or just don’t feel like it is easy to justify.  Of course, machines aren’t as easily tricked.

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