I am building a project to visualise brain data from EEG, specifically emotions. I have found a significant numbers of papers that describe methods that include pre-processing, feature extraction and classification to get a 2 dimensional affect-valence measure.
However the methods in the papers are too complex for a programmer who doesn't specialise in EEG and they don't describe the details of the process.
Is there a way that one can turn either raw data or frequency band data into an emotional readout? I have access to the Emotiv Insight (5 channel) and the Muse (4 channel). It's not for a scientific purpose, so it doesn't need to be too exact. A crude guess would do.
I have found this paper from 2001 which describes a method using the frontal lobes which I might be able to reproduce. However the reason it is easy to implement is because it lacks the machine learning and processing that more contemporary papers have to classify EEG data into emotion.