The Rise of Fitness Tracking Software

For the longest time, I’ve been a huge fan of Anand Sharmas website, April Zero.

He’s created a beautiful app that logs all aspects of his life, including:

  • Sleep
  • Heart rate
  • Exercise
  • Steps and fitness
  • Places he’s visited
  • Age

Honestly, the website is a genius idea.

This has got me thinking a little bit more about the rise of fitness tracking software and how it could be used to create a complete history of my health and fitness.

How awesome would it be to have years and years worth of health data – once enough data has been acquired, we could then theoretically use machine learning to predict when we’re going to get sick, spot warning signs of imminent weight gain, track stress levels so we know when to chill and let us know when we’re most active.

The possibilities are endless.

For example, I know that I don’t sleep well when I’ve had a few beers.

My wife tells me that I’m always restless and I always en up waking early and sitting around all day watching junk food. With proper tracking, I could see how this affects me in the following days.

Again, another easy example would be to track my TSS (training stress score) from my cycling with sleep so I can make time to get an early night and eat more protein when I’m in a particularly tricky phase of training.

It’s really an interesting time to be alive.

One thing I’ve noticed is that over the last few years, the products recommended on the list of best sports watch for running by Women’s Running magazine – the cost has continued to fall while the technology has drastically improved meaning a real-time life monitor is available for everyone.

Again, thanks to API’s and software such as IFTTT and zappier, I can upload 1 file and have it pulled into multiple systems. Then using my own code, I can analyse my real time data to see what’s happening.

Python might be particularly useful for this…

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