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That sounds like a very rewarding application that will be a great net benefit for humanity.

I'm looking at using machine learning on time series data in a similar way, replacing EEG with 3D motion data. However, ML is not my forte and I am just cutting my teeth. I would really appreciate if you be able to share some of the 'buzzwords' or ML topics that I might look into as I explore this work?

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I have found recurrent NNs and their variants (LSTMs and GRUs) to be very useful for the time series I've been working with. It can also be useful to use 1-d convolutional NNs as well. Depending on your data, sometimes working in frequency space can be easier (i.e., train on the FFT of your data). I'm still a neophyte in this area (my background is in astronomy), so I'm learning, too!

Many thanks.

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