  Engagement is a vital metric in the advertising industry and its automatic
estimation has huge commercial implications. This work presents a basic and
simple framework for engagement estimation using EEG (electroencephalography)
data specifically recorded while watching advertisement videos, and is meant to
be a first step in a promising line of research. The system combines recent
advances in low cost commercial Brain-Computer Interfaces with modeling user
engagement in response to advertisement videos. We achieve an F1 score of
nearly 0.7 for a binary classification of high and low values of self-reported
engagement from multiple users. This study illustrates the possibility of
seamless engagement measurement in the wild when interacting with media using a
non invasive and readily available commercial EEG device. Performing engagement
measurement via implicit tagging in this manner with a direct feedback from
physiological signals, thus requiring no additional human effort, demonstrates
a novel and potentially commercially relevant application in the area of
advertisement video analysis.
