Rohan’s Status Report for 4/27

This week I worked on some further experimentation with the flow state model. I tested out different configurations of training, validation, and test sets. I also experimented with adjusting the size of the model to see if we could learn the training data without overfitting such that the model can generalize to new data. Regardless of the training, validation, test splits and the size of the model, I was unable to improve the performance on unseen data which indicates we likely just need more recordings with new individuals as well as with the same people over multiple days. I also realized that the way I was normalizing the data in training, validation, and test set evaluation was different than the process I implemented for normalization during inference. So, I have been working with Arnav and Karen to resolve this issue which also introduces a need for an EEG calibration phase. We have discussed a few possible approaches for implementing this and also have a backup plan to mitigate the risk of the calibration not working out which would make it possible for us to make inferences without any calibration if necessary. My progress is on schedule and mainly will involve last minute testing to ensure we are ready for our demo on Friday next week.