Building an Open-Source EEG System

One of my current independent projects involves developing an accessible EEG (electroencephalography) system that democratizes neuroscience research. Traditional EEG systems cost tens of thousands of dollars, putting them out of reach for many researchers and students.

Project Goals

The system aims to provide:

• Low-cost alternative to commercial EEG systems
• Open-source design for community development
• Research-grade data quality suitable for academic work
• Educational tool for learning about brain signals

Hardware Design

3D-Printed Components

The mechanical components are designed for 3D printing, making the system easily reproducible:

• Custom electrode holders with adjustable positioning
• Lightweight headset frame optimized for comfort
• Modular design allowing different electrode configurations

Custom AD Converters

High-resolution analog-to-digital conversion is crucial for EEG signal quality:

• 24-bit resolution for capturing micro-volt brain signals
• Low-noise design to minimize artifacts
• Multiple channels for spatial recording

Software Stack

Signal Processing Pipeline

Using Python libraries for robust signal analysis:

• MNE-Python: Industry-standard library for neurophysiological data
• Real-time filtering: Remove power line noise and movement artifacts
• Event detection: Automated identification of neural events

Visualization Interface

Custom dashboard for real-time brain activity monitoring:

• Live signal display with multiple time scales
• Frequency domain analysis (FFT)
• Export capabilities for further analysis

Current Status

The project is in active development with functional prototypes. Key milestones include:

• ✅ Hardware design completed
• ✅ Basic signal acquisition working
• 🔄 Software optimization in progress
• 📋 Clinical validation planned

This system will enable more researchers to explore neuroscience questions and provide hands-on learning opportunities for students interested in brain-computer interfaces.

Open Source Commitment

All designs, code, and documentation will be released under open-source licenses, ensuring the scientific community can build upon and improve the system.