Tuly Hazbar

  WORK






Electroencephalography and Musical Preference Correlation



A research project I conducted in Spring 2016 as part of the BioRobotics/Cybernetics course.

Motivation 

As someone who is always searching for a new favorite song, I was interested in discovering ways that will help others like me find songs which match their music preferences without an exhausting hunt. I found in this project the opportunity to explore a question I had: if music influences our brain activity, is there a difference in our brain activity when listening to music we like and music we dislike?


How I built it


I collected, preprocessed, and extracted features from raw EEG data to explore if there is a difference in our brain activity when listening to music we like and music we dislike. I used Support Vector Machine algorithm to solve my classification problem which provided a classification accuracy of 87% for one participant (me :D).