An analysis conducted on the famous DEAP Dataset - a dataset for emotion analysis using psychophysiological measurements like EEG, EMG, ECG. The electroencephalogram (EEG) and peripheral physiological signals of 32 participants were recorded as each watched 40 one-minute long excerpts of music videos. Participants rated each video in terms of the levels of arousal, valence, like/dislike, dominance and familiarity. For 22 of the 32 participants, frontal face video was also recorded. A novel method for stimuli selection was used, utilising retrieval by affective tags from the last.fm website, video highlight detection and an online assessment tool.
Link to the original paper of the dataset: https://www.eecs.qmul.ac.uk/mmv/datasets/deap/doc/tac_special_issue_2011.pdf
In this colab is the code used to achieve ~100 % accuracy on the classification of the affective response of individual participants. The model used was a Gradient Boosting Machine along with PCA decomposition.
