hamedtu/eeg_dsr_demo

🧠 EEG Motor Imagery Music Composer

A sophisticated machine learning application that transforms brain signals into music compositions using motor imagery classification. This system uses a trained ShallowFBCSPNet model to classify different motor imagery tasks from EEG data and creates layered musical compositions based on the classification results.

🎯 Features

• —Real-time EEG Classification: Uses ShallowFBCSPNet architecture for motor imagery classification
• —Music Composition: Automatically creates layered music compositions from classification results
• —Interactive Gradio Interface: User-friendly web interface for real-time interaction
• —Six Motor Imagery Classes: Left/right hand, left/right leg, tongue, and neutral states
• —Sound Mapping: Each motor imagery class is mapped to different musical instruments
• —Composition Management: Save, clear, and manage your musical creations

🏗️ Architecture

Project Structure

├── app.py                    # Main Gradio application
├── classifier.py             # Motor imagery classifier with ShallowFBCSPNet
├── data_processor.py         # EEG data loading and preprocessing
├── sound_library.py          # Sound management and composition system
├── config.py                 # Configuration settings
├── requirements.txt          # Python dependencies
├── SoundHelix-Song-1/        # Audio files for different instruments
│   ├── bass.wav
│   ├── drums.wav
│   ├── other.wav
│   └── vocals.wav
└── src/                      # Additional source files
    ├── model.py
    ├── preprocessing.py
    ├── train.py
    └── visualize.py

System Components

1. 1.EEGDataProcessor (data_processor.py)
2. 2.Loads and processes .mat EEG files
3. 3.Handles epoching and preprocessing
4. 4.Simulates real-time data for demo purposes

1. 1.MotorImageryClassifier (classifier.py)
2. 2.Implements ShallowFBCSPNet model
3. 3.Performs real-time classification
4. 4.Provides confidence scores and probability distributions

1. 1.SoundManager (sound_library.py)
2. 2.Maps classifications to audio files
3. 3.Manages composition layers
4. 4.Handles audio file loading and playback

1. 1.Gradio Interface (app.py)
2. 2.Web-based user interface
3. 3.Real-time visualization
4. 4.Composition management tools

🚀 Quick Start

Requirements

Python 3.9–3.11 recommended. Install dependencies:

python -m pip install -r requirements.txt

How to run (Gradio)

Local launch:

python app.py

This starts a server on http://127.0.0.1:7860 by default.

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