An EEG and Biometric-Based Emotion AI System for Real-Time Consumer Insights
The Challenge
Traditional surveys in neuromarketing research and polls often fail to capture what people truly feel. They can be biased, slow, and unsuccessful in capturing how emotions shift in real time. This makes it difficult to understand why someone prefers, remembers, or avoids certain products such as food flavors, scents, ads, or packaging.
Hypothesis
By combining signals from the brain (EEG consumer insights), skin responses (GSR), facial expressions (facial expression analysis), and eye movements, we could:
- Understand emotions in real time (measure emotions in real time with EEG and GSR).
- Connect hidden emotional reactions with survey answers in consumer neuroscience studies.
- Provide more accurate insights into what drives emotion-driven consumer behavior.
Execution
- Collected data using EEG headsets, skin sensors, cameras, and eye tracking for biometric marketing.
- Developed custom EEG and GSR hardware for higher accuracy and control in neuromarketing studies.
- Translated signals into emotional states such as excited, relaxed, stressed, or bored, using Emotion AI.
- Built a professional dashboard powered by marketing AI to visualize and analyze emotion data for end-users.
Outcomes
- Successfully developed a real-time emotional marketing studies prediction system that outperformed existing solutions.
- Built a highly accurate webcam-based eye-tracking system for neuromarketing research applications.
- Designed a scalable hardware ecosystem capable of long-duration synchronized recording.
Project Highlights
30%
accuracy gain vs emotion AI alternatives
3.6%
error in webcam
eye-tracking
eye-tracking
8+
hours continuous, 128-FPS
synchronized capture
synchronized capture