Better Pedometer - HELP NEEDED!

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:

https://banglejs.com/apps/#accellog

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:

• Go to the Bangle.js App Loader
  
• Connect to your Bangle
  
• Under My Apps look for Acceleration Logger
  
• You'll see a download arrow next to it - click that
  
• You can now choose to Save the data you've recorded, and then please upload it here!
  
  

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

1 Attachment

• accellog.0.csv

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

3 Attachments

• accellog.0.csv
• accellog.2.csv
• accellog.1.csv

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!

1 Attachment

• accellog.0.csv

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!

1 Attachment

• accellog.0.csv

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 :)

walking around in my bedroom

1 Attachment

• accellog.1.csv

I'm new bangle.js owner and effectively pedometer needs improvment.

It looks gadget bridge and other pedometer widget don't have the same result. Do they calculte step their own way or is directly implement in the firmware?

Using the last stable firmware 1.8 I think the main issue is sensitivy. Steps are triggered too quickly. This morning at wake up i did already 1k steps :)
Edit: this feedback is when using widpedom ; I'm testing today activepedom which looks having more settings about sensitivity.

Do you need more sample with other kind of use case? Do you need testing on this specific branch?

Hi - for now I think we're good as far as sample data goes.

wedpedom and gadgetbridge should match, but activepedom does some processing on the watch and should be more accurate.

I hope to have an update soon (but it'll probably still be a few weeks off). The issue is that with both old and new step counters, they should filter out detected steps that don't form part of a regular step...step..step pattern - but they don't currently do this.