Data is intersting, at least in my eyes. All the more if its data about myself. As a result i was quite interested in all the fittness-trakers that recently came to market. But there was one other point that held me back. In my opinion private data, among whom i include movement and sleeping data, should not float around in ”the cloud”. Cause “(t)here is no cloud – just other people’s computers”. Further more i don’t like to have an other device that needs to charge every night. It just sucks, and too often I already forget to charge my phone.
By accident I ended up with an Garmin vivofit, that luckily could meet all of my requirements in the end. But first things first, the Garmin vivofit is a bracelet that tracks movements. It distincts between steps walked, steps runned and movement done while asleep. You might think that its not much but this data is quite interessting. Its amazing how many/ how little steps one does during the days. The vivofit runs on batteries, that should last for one year and may be replaced afterwards. So the no charging requirement is met. Whats left is the cloud connection. Out of the box the vivofit syncs with garmin apps against the “garmin connect” cloud. But…
Get the data from vivofit localy
But luckily there is a python implementation of the ant+ protocoll (openant). It’s the protocol that is used by the vivofit to transmit its data. Further more there is python code to download all the data from the vivofit, so called ‘.fit’ files. Its called antfs-cli. Now one may decode the ‘.fit’ files and extract its values to generate statisitcs, graphics and so on. I’ve written some code to dump the ‘.fit’ content to the mysql-db of a remote webserver, and further some php & js number of steps per day. If there is interest drop me a line and I might publish the code. Further more I think about creating a detailed description how to setup a raspi to read data from vivofit and display the data on a website.
After using all the python projects and my own code, the vivofit meets all my expectations.
And works like a charm.
Nachdem die Veröffentlichung 9 Years of Sleep, in der Dominic Szablewski seine IRC-Logs auswertete und daraus Schlafenszeiten rekonstruierte, auch wieder einige Jahre her ist, stolperte ich heute über einen Blogpost der in eine ähnliche Richtung geht. Unter dem Titel Three Years of Logging My Inbox Count hat Mark Willson eine Analyse der von ihm gesammelten Daten über sein Email-Postfachs angestellt. Dabei zieht er spannende Verbindungen zu Stress und schaut sich die liegen gebliebenen Mails auch genauer an.