AI-Driven Emotional Pattern Translation

Innovative AI prototype translating bioelectrical signals into emotional patterns

Overview

This innovation project, conducted in collaboration with MIT Professor Peter Gloor at Grenoble École de Management, focused on developing cutting-edge technology to bridge the gap between biological signals and emotional understanding.

Problem

Understanding human emotions through objective, measurable signals remains a significant challenge in both healthcare and human-computer interaction. Traditional methods of emotional assessment rely heavily on subjective reporting, limiting their application in clinical and technological contexts.

Solution

Developed an AI-driven prototype that translates bioelectrical signals into interpretable emotional patterns. Leveraged machine learning algorithms to identify correlations between physiological responses and emotional states, creating a novel approach to emotional intelligence technology.

Impact & Results

• •Created functional prototype demonstrating proof-of-concept
• •Novel approach combining neuroscience and AI for emotional intelligence
• •Potential applications in mental health monitoring and therapeutic interventions
• •Collaborative research with renowned MIT professor

Key Skills Applied