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jyotiradityachavan/Temporal_Emotion_Transition_Modeling

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App README

🧠 EEG Emotion Recognition System

A comprehensive multi-modal cognitive state recognition system that analyzes EEG, eye tracking, GSR, and facial emotion data to identify patterns in cognitive states and emotional responses using advanced machine learning techniques.

🌟 Key Features

🔬 Multi-modal Data Integration

  • —EEG Data: Brainwave analysis (Delta, Theta, Alpha, Beta, Gamma bands)
  • —Eye Tracking: Gaze patterns, pupil dilation, fixation metrics
  • —GSR (Galvanic Skin Response): Emotional arousal measurement
  • —Facial Emotion Analysis: Valence, attention, engagement metrics
  • —I-VT Algorithm: Fixation detection and saccade analysis

🤖 Advanced Machine Learning Pipeline

  • —Hidden Markov Models (HMM): 5-state cognitive modeling
  • —RNN-HMM Hybrid: Temporal sequence modeling with LSTM networks
  • —Seq2Seq with Attention: Transformer-based sequence prediction
  • —Real-time State Classification: Cognitive state identification

📈 Interactive Visualization

  • —Streamlit Dashboard: Web-based interactive interface
  • —t-SNE Trajectory Plots: 2D visualization of cognitive state evolution
  • —Transition Matrix Analysis: State transition probabilities
  • —Real-time Monitoring: Live cognitive state tracking

🎯 Cognitive State Detection

Identify and classify 5 primary cognitive states with physiological indicators:

StateEmojiDescriptionKey Physiological Indicators
State 0🎯FocusedHigh beta waves, stable gaze, reduced blink rate
State 1😕DistractedIncreased theta waves, gaze variability, high saccade rate
State 2😴FatiguedElevated alpha waves, slow pupil response, increased blink duration
State 3🤔EngagedModerate beta waves, positive valence, steady attention
State 4🥱BoredReduced physiological responses, gaze disengagement

Installation

bash
pip install -r requirements.txt

## Run full pipeline
cd project python main.py
# After completely run of main.py file then start app.py
streamlit run app.py

## Clone the repository
git clone https://github.com/yourusername/eeg-emotion-recognition.git

# Navigate to project directory
cd eeg-emotion-recognition