Term of Award
Fall 2020
Degree Name
Master of Science in Mathematics (M.S.)
Document Type and Release Option
Thesis (restricted to Georgia Southern)
Copyright Statement / License for Reuse
This work is licensed under a Creative Commons Attribution 4.0 License.
Department
Department of Mathematical Sciences
Committee Chair
Ionut Emil Iacob
Committee Member 1
Stephen Carden
Committee Member 2
Felix Hamza Lup
Abstract
We perform an analysis of the brain electroencephalogram (EEG) signals to determine what part of the brain is responsible with consumers’ preference on selecting marketing products. In our study we use real brain signals collected from different regions of the brain through 14 channels. We de-noise and pre-process these signals, extract the characteristic brain waves (delta, theta, alpha, beta, and gamma) from each brain region signal (using Discrete Fourier Transform filters), and perform comprehensive comparison and analysis for different signal types, individuals, and brain regions (brain sensors locations). We then use an Artificial Neural Network model to learn and predict consumers’ choice based on their detected brain activity. Our extensive experimental results show that these largely available, non-invasive technologies can be successfully employed in neuromarketing, a new emerg- ing field of using neuroscience to determine consumers’ genuine preferences and reactions on different marketing stimuli.
OCLC Number
1382331533
Catalog Permalink
https://galileo-georgiasouthern.primo.exlibrisgroup.com/permalink/01GALI_GASOUTH/1r4bu70/alma9916564850102950
Recommended Citation
Rasheed, Lateef, "Decision Pattern Detection From Brain Response To Marketing Stimuli" (2020). Electronic Theses and Dissertations. 2185.
https://digitalcommons.georgiasouthern.edu/etd/2185
Research Data and Supplementary Material
Yes
