Wavelet is a transformer based custom model that enables real-time EEG to AI-Derived MEG brain waves enhancing.
- Real-time Signal Processing: Visualize EEG signals with milliseconds latency
- 3D Brain Visualization: Interactive 3D model with real-time sensor activity mapping
- AI Signal Enhancement: Transform EEG signals into MEG-like data for deeper insights
- Frequency Band Analysis: Live monitoring of Delta, Theta, Alpha, Beta, and Gamma bands
- Audio Synthesis: Convert brain signals into real-time auditory feedback (just a cool idea, no use, must try!)
- Data Export: Download raw EEG or enhanced MEG data in CSV/JSON formats
- Frontend: Next.js 14, TypeScript, Tailwind CSS
- 3D Rendering: Three.js with custom WebGL shaders
- Data Visualization: Recharts with custom animations
- Signal Processing: Custom FFT implementation with real-time filtering
- Audio: Web Audio API with dynamic synthesis
- Clone the repository:
npm run dev
# or
yarn dev
# or
pnpm dev
# or
bun dev
Open http://localhost:3000 with your browser to see the result.
- This data was obtained from the OpenfMRI database. Its accession number is ds000117.
- Perri Karyal (her work on EEG gaming is incredible,check it out) and Charles Cumpsty for lending us the EEG equipment!
- Tim and Gleb for letting us explore more their initial idea: BrainTransform ❤️
- Nebius for offering the Nvidia H100s used!