Model APIs
NeuroFusion hosts EEG foundation models on GPU infrastructure for AI-powered brain signal analysis. These models run on models.usefusion.ai — an NVIDIA A100 GPU server with auto-sleep/wake to minimize costs.Available Models
| Model | Task | Description |
|---|---|---|
| ZUNA | denoise | Remove artifacts (eye blinks, muscle, environmental noise) while preserving neural signals |
| ZUNA | reconstruct | Reconstruct missing or corrupted EEG channels |
| ZUNA | upsample | Expand from fewer channels to a standard montage |
Supported Devices
| Device | Channels | Sample Rate |
|---|---|---|
| Neurosity Crown | 8 (CP3, C3, F5, PO3, PO4, F6, C4, CP4) | 256 Hz |
| Muse (2, S) | 4 (TP9, AF7, AF8, TP10) | 256 Hz |
How It Works
Pipeline Detail
- CSV Input — Raw EEG data from your device (values in µV)
- Preprocessing — Automatic conversion to MNE
.fifformat with standard 10-05 montage - ZUNA Processing — Resampling to 256 Hz, filtering, epoching into 5-second segments, normalization, then GPU inference
- Output — Denoised signal returned as JSON (per-channel arrays) or CSV
Minimum Requirements
- Recording duration: At least 6 seconds (5s minimum for one ZUNA epoch + buffer)
- Channels: 4+ EEG channels with standard 10-20 names
- Format: CSV with channel columns and optional timestamp column
Architecture
- Auto-wake: If the VM is deallocated, the first request starts it and returns HTTP 202 with retry guidance
- Auto-sleep: VM deallocates after 30 minutes of inactivity to minimize costs
- Health checks:
/api/eeg-models/healthshows GPU status and model availability
Using the Platform
There are two ways to use ZUNA on NeuroFusion:1. Recordings Page (/recordings)
- Live Recording: Connect your Neurosity Crown or Muse headband, record EEG, then denoise with one click
- Upload CSV: Drop in a CSV file from a previous recording
- View Results: See denoised signal preview and download cleaned CSV
2. Analysis Page (/analysis)
- Upload & Analyze: Upload CSV, choose ZUNA AI Denoising or other analysis types
- Side-by-Side: View raw vs denoised signals in a split comparison
- Download: Export denoised data as CSV for further analysis
/recordings, denoise, then view detailed results on /analysis.
