Rohan’s Status Report for 3/30

This week, in preparation for our interim demo, I have been working with Arnav to get the Emotiv Focus Performance Metric and the Flow State Detection from our custom neural network integrated with the backend. Next week I plan to apply Shapley values to further understand which inputs are contributing most significantly in the flow state classification. I will also test out various model parameters, trying to determine the lower and upper bounds on model complexity in terms of the number of layers and neurons per layer. I also need to look into how the Emotiv software computes the FFT for the power values within the frequency bands which are the inputs to our model. Finally, we will also try training our own model for measuring focus to see if we can detect focus using a similar model to our flow state classifier. My progress is on schedule and I was able to test the live flow state classifier on myself while doing an online typing tests and saw some reasonable fluctuations in and out of flow states.