Andrew Sweet

04 Mar 2014


Due to Nike’s generosity, nearly everybody in our class wore a Nike Fuelband between mid-January and the date of this posting (March 3). While Nike offers a public API for viewing the data, it’s not that comprehensive. Using some basic packet sniffing, and borrowing individuals’ fuelbands for < 30 seconds, connecting it to my laptop, and allowing the Fuelband to attempt to connect to website, I managed to collect the each individual’s Access Token, which I then passed to alongside some other parameters to receive a wide array of data, including daily minute by minute fuel data, calories, steps, and distance.Screen Shot 2014-03-04 at 8.21.29 AMScreen Shot 2014-03-04 at 8.21.25 AMScreen Shot 2014-03-04 at 8.21.20 AMScreen Shot 2014-03-04 at 8.20.59 AMScreen Shot 2014-03-04 at 8.21.04 AMScreen Shot 2014-03-04 at 8.21.09 AMScreen Shot 2014-03-04 at 8.21.15 AM 

Here I’ve compared male and female activity for the class on an average Tuesday:


Screen Shot 2014-03-04 at 8.21.54 AM



You can find on visual inspection schedule similarities between individuals as shown in the next two examples:Screen Shot 2014-03-04 at 8.22.51 AM


Here you can see activity for both individuals fits between scheduled points in timeScreen Shot 2014-03-04 at 8.27.54 AM

Here I’ve compared my data to the average male in the class on Fridays.Screen Shot 2014-03-04 at 8.28.19 AM