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Not really that easy with just IMU sensors, I’d assume ?

I did one project in school (albeit a simple SVM based model) to classify walking vs running (and so on) and ambiguity was still there. Stationary vs. Walking was easy to draw a hyper plane in between, not Running.

I still find it a difficult problem to get into, after 5 years. Perhaps ANN models might work better? Although my heart is still at Hidden MM states...

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Do you have the code for your classification project? It would be great to see it on github or something.

I have it, not only the code but labelled dataset I created with an arduino, first, and then iPhone. It’s been a private repository forever, but thanks! I’ll make it public and Edit post the link down here.

(Its not pretty though...)

Edit: https://github.com/prashnts/MPU-9250

I have proper project reports I’d submitted somewhere for sure, as well. I’ll add it there in repo. I never bothered earlier.

Edit 2: this was the paper i finally submitted at school.

https://github.com/prashnts/MPU-9250/blob/master/Docs/submit...

I enjoyed reading that, thank you!

Thanks! To be more honest, this paper had a "constraint" against using FFT, simply because I didn't really know how it worked then...

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