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Model APIs

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Available Models

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Supported Devices

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How It Works

Your EEG Device → CSV data → NeuroFusion API → ZUNA Model (GPU) → Cleaned signal → Your app

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Pipeline Detail

1. CSV Input — Raw EEG data from your device (values in µV)
2. Preprocessing — Automatic conversion to MNE .fif format with standard 10-05 montage
3. ZUNA Processing — Resampling to 256 Hz, filtering, epoching into 5-second segments, normalization, then GPU inference
4. Output — Denoised signal returned as JSON (per-channel arrays) or CSV

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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

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Architecture

┌─────────────┐     ┌──────────────────┐     ┌───────────────────────┐
│  Frontend    │────▶│  Backend Server   │────▶│  GPU VM               │
│  /recordings │     │  /api/eeg-models  │     │  models.usefusion.ai  │
│  /analysis   │     │  (auto-wake VM)   │     │  NVIDIA A100 80GB     │
└─────────────┘     └──────────────────┘     │  ZUNA model           │
                                              └───────────────────────┘

• 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/health shows GPU status and model availability

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Using the Platform

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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

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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