Open-Source Low-Cost EEG System

This independent project aims to democratize neuroscience research by creating an accessible, research-grade EEG (electroencephalography) system. Traditional EEG systems cost tens of thousands of dollars, putting them out of reach for many researchers, students, and institutions.

Project Vision

Accessibility Goals

• Sub-$1000 total cost compared to $20,000+ commercial systems
• Open-source design enabling community contributions
• 3D-printable components for easy reproduction
• Research-grade quality suitable for academic publications

Educational Impact

Making neuroscience accessible to:

• Universities with limited budgets
• High schools teaching advanced biology
• Maker communities interested in brain-computer interfaces
• Developing countries building research capacity

Hardware Architecture

3D-Printed Mechanical Components

All structural elements are designed for standard 3D printers:

Electrode Housing System

• Adjustable electrode holders for different head sizes
• Quick-release mechanisms for easy electrode changes
• Modular design supporting 8, 16, or 32 electrode configurations

Headset Frame

• Lightweight design (<200g total weight)
• Ergonomic fit optimized for extended recording sessions
• Cable management system to reduce movement artifacts

Custom Analog Frontend

High-Resolution ADC Design

• 24-bit resolution for capturing microvolt brain signals
• 1kHz+ sampling rate for capturing fast neural events
• Low-noise design with <1μV RMS noise floor
• Differential inputs with high common-mode rejection

Signal Conditioning

• Programmable gain amplifiers (1000x - 10,000x)
• Anti-aliasing filters to prevent signal distortion
• Power line noise rejection (50/60 Hz notch filters)
• ESD protection for electrode safety

Software Stack

Real-Time Signal Processing

Built on proven Python libraries:

MNE-Python Integration

• Industry-standard library for neurophysiological data
• Automatic artifact detection and removal
• Frequency domain analysis capabilities
• Statistical analysis tools for research

Custom Acquisition Software

• Real-time signal visualization
• Event marking for experimental paradigms
• Data export in standard formats (EDF, BrainVision)
• Network streaming for multi-computer setups

User Interface

Dashboard Features

• Live signal display with adjustable time windows
• Spectral analysis plots (FFT, spectrogram)
• Signal quality indicators for each electrode
• Recording controls and experiment management

Validation and Testing

Signal Quality Verification

Comparing against commercial systems:

• Standard test signals (sine waves, square waves)
• Alpha wave detection in relaxed subjects
• Event-related potential (ERP) measurements
• Inter-system correlation analysis

Clinical Applications

Testing with real neuroscience experiments:

• Visual evoked potentials
• Auditory oddball paradigms
• Sleep stage classification
• Motor imagery tasks

Manufacturing and Assembly

Bill of Materials

• Custom PCB: ~$150
• 3D-printed parts: ~$50
• Electronic components: ~$200
• Electrodes and consumables: ~$100
• Total system cost: <$500

Assembly Documentation

• Step-by-step build instructions
• Video tutorials for complex procedures
• Troubleshooting guides
• Community forum for support

Open Source Commitment

Licensing

• Hardware designs: CERN Open Hardware License
• Software: MIT License
• Documentation: Creative Commons Attribution

Community Development

• GitHub repository with full design files
• Regular design reviews and improvements
• Collaboration with other open-source projects
• Integration with existing analysis tools

Current Development Status

• ✅ Hardware design completed and tested
• ✅ Basic signal acquisition demonstrated
• ✅ 3D-printed prototypes validated
• 🔄 Software optimization in progress
• 🔄 Clinical validation studies ongoing
• 📋 Manufacturing partnership discussions

Future Enhancements

Advanced Features

• Wireless data transmission
• Real-time brain-computer interface capabilities
• Machine learning integration for automatic analysis
• Mobile app for portable monitoring

Scaling Impact

• Educational curriculum development
• Workshop programs for universities
• Partnerships with neuroscience organizations
• Translation to low-resource settings

This project represents a significant step toward democratizing neuroscience research and education, enabling the next generation of brain researchers to explore the mysteries of human cognition.