Hi! I'm looking into improving the accuracy of Bangle.js's pedometer by adding this project
However to calibrate it, I need data!
If you're willing to help, please could you install this app:
Then run it (Accel Log), choose Start, and then walk exactly 150 paces in a variety of ways - along a road, bumpy path, up/down stairs, fast, slow, pausing, and so on - then press BTN2 to stop recording when you're done.
You can then:
Hopefully when I get a few examples of different walking styles I can feed it into their tools and it'll calibrate itself!
Do you want separate recordings for each walking style, 150 paces of each. Or one recording of mixed styles across 150 paces?
I think probably a few recordings of normal-ish activities - so eg if you're walking then going up stairs and then walking fast that'd good to have in one recording.
here you go :-) walking down/up stairs, walking fast and slow
Great - thanks!
App loaded will give it a spin a few times tonight.
Is this the oxford pedometer algorithm ?
log 0 is walking round the house, upstairs and downstairs.
log 1 is walking up hill fast and slow
log 2 is walking on flat, downhil, stop for a moment and restart
Thanks for this! Yes, it's the oxford pedometer algorithm that had been mentioned previously. However even if that doesn't work out, having a bunch of data should really help to come up with a reliable algorithm.
HOpe it helps!
Thanks! I'll try and get on it this week
thank you all! you can follow the development at https://github.com/espruino/Espruino/issues/1846
Thanks for sharing, interesting reading. Looking forward to a more accurate step counter.
Hi. Here are 150 steps. I will upload more data hiking next week. Thanks!
Thanks! I think we've got a decent amount of data now. There is now a Branch of Bangle.js with some calibrated data in: https://github.com/espruino/Espruino/tree/step_counting
But we just have to do some work to stop it automatically lowering the step threshold too much and just randomly counting steps when you're stationary :)
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