Quantified self for sports performance

presentation for first SF quantified self meetup

Transcript

1. A quantitative approach to athletic performance Sebastian Ortiz
2. Overview • What I’ve been tracking and why – Weight (withings, DIY scale) – Calorie/food intake (fatsecret) – Experiments (meal timing, iso-caloric IF) • Some tools I have used along the way – Pandas,matplotlib – D3 – Numerous OAuth accessible APIs • Extras – Video tracking of skills – Devices for instantaneous feedback
3. Weight tracking (1st iteration) • DIY wireless scale – 24 bit AD7799 ADC – RN41 bluetooth serial module – At90usb162 microcontroller – Power switching logic (battery life 9-10 months)
4. DIY wireless scale
6. High-tech assembly techniques
7. Why measure? • Consciously/subconsciously change behavioral patterns • Discover long term trends • Quantify effectiveness of actions
8. Subconscious effects • Tracking weight even without consciously trying to alter it results in measurable change.
10. Long term trends
11. Experiment (meal timing)
12. pandas • Perfect for time series data • Aligns/resamples unequally sampled time series for comparison • Rolling window functions for visualizing trends • Nice similarities to R, dataframe,etc.
13. matplotlib • Easy to use, mature state of development • Integrates seamlessly with pandas
14. d3.js • Can produce pretty results • Simple compared to raw SVG, but still fairly involved compared to matplotlib
15. API hacking • Withings • Fatsecret • Fitbit • Instagram • Flickr • Python code available here: – https://github.com/trtg – Writeups (in progress) at my octopress blog here: • http://trtg.github.com/ • Older projects here: http://www.keyboardmods.com
16. Realtime feedback • http://www.keyboardmods.com/2012/01/gy mnastics-tap-swing-trainer.html
17. Questions?