Term of Award
Summer 2021
Degree Name
Master of Science in Mathematics (M.S.)
Document Type and Release Option
Thesis (open access)
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 Iacob
Committee Member 1
Felix Hamza-Lup
Committee Member 2
Goran Lesaja
Abstract
As machine learning models become more sophisticated, and biometric data becomes more readily available through new non-invasive technologies, it becomes increasingly possible to gain access to interesting biometric data that could revolutionize Human Computer Interaction. In this research, we propose a framework to assess and quantify human preference (like or dislike) on presenting various external visual stimuli. Our framework relies on an Long Short-Term Memory (LSTM) Recurrent Neural Network (RNN) based model and on electroencephalogram (EEG) signals analysis to predict Like or Dislike preference of human subjects when presented with various marketing images.
OCLC Number
1273207663
Catalog Permalink
https://galileo-georgiasouthern.primo.exlibrisgroup.com/permalink/01GALI_GASOUTH/1r4bu70/alma9916469447702950
Recommended Citation
Bano, Lorela, "LSTM-Based Model For Human Brain Decisions Using EEG Signals Analysis" (2021). Electronic Theses and Dissertations. 2291.
https://digitalcommons.georgiasouthern.edu/etd/2291
Research Data and Supplementary Material
No
