BioAmp-Python-Notebooks

BioAmp-Python-Notebooks is an open-source collection of Python notebooks for biosignal processing, designed to make bio-potential signal analysis accessible to everyone. Whether you're working with BioAmp hardware or other acquisition systems, these notebooks provide complete workflows for processing and analyzing physiological signals.

Featured Notebooks

• ECG Signal Processing: Complete pipeline for electrocardiogram analysis from acquisition to feature extraction
• EMG Signal Processing: End-to-end electromyography processing for muscle activity analysis

Perfect for:

• Students learning bio-potential signal processing
• Researchers needing reproducible analysis pipelines
• Developers building health-tech applications
• Hobbyists exploring physiological computing

📌 Features of the Notebooks

ECG Notebook

This notebook guides you through every stage of ECG signal analysis:

1. Library Imports - All necessary Python libraries
2. Initialize Chords_USB Client - Connect to BioAmp boards
3. Real-time ECG Data Acquisition - Collect data with live plotting
4. Signal Processing - Notch and low-pass filtering
5. ECG Analysis Pipeline using NeuroKit2:
   • PQRST Complex Analysis
   • ECG Beat Morphology
6. Data Export - Save processed signals to CSV
7. Stop Streaming - Terminate acquisition safely

EMG Notebook

This notebook provides comprehensive EMG signal processing:

1. Library Imports - All necessary Python libraries
2. Initialize Chords_USB Client - Connect to BioAmp boards
3. Real-time EMG Data Acquisition - Collect data with live plotting
4. Signal Processing:
   • 50Hz notch filter for powerline noise removal
   • 70Hz high-pass filter for EMG signal isolation
5. Visualization:
   • Raw vs filtered signal comparison
   • Muscle activation envelope
6. EMG Strength Meter - Real-time muscle activation level display
7. Data Export - Save processed signals to CSV
8. Stop Streaming - Terminate acquisition safely

🎯 Who Is This For?

• 🧑‍🎓 Students looking for hands-on biosignal processing
• 🧪 Researchers analyzing physiological data
• 💡 Developers building health-related applications
• ❤️ Hobbyists experimenting with bio-potential signals

🚀 Getting Started

1. Clone this repository

git clone https://github.com/upsidedownlabs/BioAmp-Python-Notebooks.git

2. Install required packages

pip install -r requirements.txt

3. Run the Notebooks
   • Open the .ipynb file in Jupyter Notebook/Lab
   • Follow each cell in sequence

📌 Upcoming Notebooks

The repo will gradually include:

• EEG (Electroencephalogram) Feature Extraction
• EOG (Electrooculogram) Blink Detection

Stay tuned!

🤝 Contributing

Contributions, issues, and suggestions are welcome! If you have your own notebooks or improvements, feel free to submit a pull request.