Jean’s Status Report for 02/26/2022

This week I spent time preparing for the presentation for the Design Proposal and polishing the slides. I was reading a lot of papers on the techniques they used for ML classifications and the signal processing modules that we can use on Python. I have never had an experience with ML so I have been trying to understand more on how it works in order to extract the main features of the blinks and the winks. I was thinking of a way to process real-time data and plan out the steps we need to do to process the data. First, we will either delete the artifacts or ignore those. Then, we will look into the temporal information which will be fed into the ML and spectral information which will be calculated based on the fast-fourier transform which I will start to look more into details and find useful features to be fed into our ML algorithm. I aim to be able to gather useful features that can be used for discerning different signals over next week and the break. We have just received the EMG device on Friday, so currently I am trying to connect everything up and have it running on Arduino. I spent time with my teammates collecting our EEG signals together, where Jonathan uses them for a testing of ML classifications. For the next plan ahead, the goals I have to complete over the next weeks are to gather EMG data and transmit it to Backend Python, and be able to calibrate and turn it into control data. On the other hand, I will be coordinating with Jonathan in finding additional features to feed into our ML classification, especially the spectral data information.