Analysis of Viewer EEG Data to Determine Categorization of Short Video Clip

This paper discusses some very early research results for a Machine Learning System using Brain-Machine Interface data to categorize whether a viewer likes a short video. Prior art teaches that Machine Learning can be used to categorize alertness of volunteers using Brain-Machine Interface Electroencephalogram (EEG) data. Also, published research has described how EEG data can be correlated to the ability of participants to remember television commercials. This paper advances this research one step further. The paper examines whether or not Machine Learning can tell whether or not a participant likes a short YouTube video using only EEG data. The research is in the preliminary stage (two subjects thus far), but early results are promising. Also discussed in the paper is information regarding commercialization of the invention which is of interest to many universities. A provisional patent application was filed and a critique was gathered from executives from a famous advertising agency regarding commercialization of the invention for Neuromarketing. These executives provided valuable detailed feedback regarding pros and cons of different commercialization possibilities. Presented in the paper are the results of these discussions including specific areas where the research would and would not likely yield a successful commercial product.