EPSimFilt 🧠

Systematic Digital Filter Evaluation for Evoked Potentials

Version 1.0.0 | Justin W. Andrushko, PhD | Northumbria University

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Quick Deploy to Streamlit Cloud (Free, ~5 minutes)

1. Push to GitHub

EPSimFilt/
├── app.py
├── signal_generator.py
├── noise_generator.py
├── filters.py
├── metrics.py
├── methods_template.py
├── requirements.txt
├── .streamlit/
│   └── config.toml
└── assets/
    └── TMSMultiLab_logo.png

git init
git add .
git commit -m "Initial EPSimFilt deployment"
git remote add origin https://github.com/YOUR_USERNAME/EPSimFilt.git
git push -u origin main

2. Deploy on Streamlit Community Cloud

1. Go to share.streamlit.io
2. Sign in with GitHub
3. Click "New app"
4. Select your repository, branch (main), and main file (app.py)
5. Click "Deploy!"

Your app will be live at https://YOUR_USERNAME-epsimfilt-app-XXXX.streamlit.app

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Run Locally

# Clone or download the repo
git clone https://github.com/YOUR_USERNAME/EPSimFilt.git
cd EPSimFilt

# Install dependencies
pip install -r requirements.txt

# Launch
streamlit run app.py

App opens automatically at http://localhost:8501

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Features

• Signal Generation — Mono/bi/tri-phasic EPs with configurable parameters
• Real Waveform Loading — LabChart, Spike2, LabView, CSV, MAT formats
• Noise Models — EMG, line noise, ECG, TMS artefact, movement
• Filter Testing — Butterworth (1–8th order), FIR, notch filters
• Batch Analysis — Up to 10,000 iterations per configuration
• Time-Frequency — Morlet wavelet analysis
• Methods Generator — Publication-ready methods text (3 detail levels)
• Export — CSV results, 300/600 DPI figures, RIS references

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Citation

Andrushko, J.W. (2025). EPSimFilt: A Systematic Digital Filter Evaluation tool for Evoked Potentials (Version 1.0.0). Northumbria University.

Part of TMSMultiLab