Last Updated on January 21, 2023 by pg@petergamma.org
We appreciate foot pods from sports watches. The android app aTraining tracker delivers all information we want for walking mediation, and we are happy with the data it delivers to us. What we are not happy about are to carry around five different smartphones with 5 different apps, and to analyse those apps we need to code an Adinstruments LabChart software.
We learned from BITalino, that a foot pod is basically an accelerometer. Fellnr who took apart the Stryd is much more differentiated:
“A Footpod is a small device that measures pace and distance while running or walking. These Footpods contain accelerometers that calculate the movement of your foot, providing an accurate measurement across a broad range of paces and stride lengths. A Footpod does not simply measure each stride, which would be wildly inaccurate. These first-generation Footpods can be quite accurate, but require calibration, and this calibration has to be repeated for different shoes. The Stryd footpod is a second-generation Footpod and it’s so accurate it doesn’t require calibration. The first generation Footpods use a 3-axis accelerometer, where second generation Footpods typically use 9-axis sensors which combine accelerometers, gyroscopes, and magnetometers for far greater accuracy. (This page focuses on the first generation Footpods, though Stryd is far superior.) “
https://fellrnr.com/wiki/Footpod
We focus on the first generation of foot pods, and want it as easy as possible. InfluxDB is challenging for non-coders as we are. OpenBCI has up to 16 channels, and additionally 3 Aux channels. For walking meditation, we can live with a foot pod cable version connected to the AUX channels of OpenBCI.
How to build an Adafruit Step counter from an Adafruit Clue chip can be found here:
Further components can be found here:
We studied a lot about InfluxDB. But for non-coders to have a multi-sensor device, OpenBCI is easier, which has additionally 3 AUX channels. OpenBCI supports also an external trigger to mark events. This should be enough to analyse a walking meditation activities, to mark when it starts and when it stops.