Harmonic analysis of biosignals

Harmonic analysis of biosignals#

Important

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We count on you to help us making it better by contributing even the tiniest improvements (a typo, a rephrasing to make things clearer, a comment to the code, a new option, etc.). Biotuner belongs to you. Make yourself part of the team!

Home#

Welcome to Biotuner’s documentation where you can learn about computational tools derived from music theory and neurophysiology to develop novel ways to analyze, but also use electrophysiological signals as a source of musical or visual composition.

See also

You can find information on how to cite this documentation here.

The documentation covers installation instructions, the API, as well as notebooks that show you how to extract meaningful harmonic information from brain signals, and use the visualization methods of the toolbox. It is for scientists and artists alike.

It is constructed in an open-ended manner to allow for the addition of new methods and tools for extended signal support (e.g. cardiac signals and plant signals).

You can navigate to the different sections using the left panel.

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Biotuner

Python toolbox that incorporates tools from biological signal processing and musical theory to extract harmonic structures from biosignals.

Tests Codecov PyPI Biotuner Docs License GitHub stars Python Versions

✨ Features#

  • 🎵 Harmonic Analysis: Extract harmonic structures from biosignals using music theory principles

  • 📊 Multiple Peak Detection Methods: FOOOF, EMD, fixed-frequency, and harmonic-recurrence based methods

  • 🧮 Harmonicity Metrics: Compute consonance, dissonance, harmonic similarity, Tenney height, and more

  • 🎹 Musical Applications: Generate musical scales, tuning systems, and MIDI output from biosignals

  • 🔬 Group Analysis (BETA): Batch processing for multiple time series with automatic aggregation

  • 📈 Rich Visualizations: Publication-ready plots for spectral analysis and harmonic relationships

  • 🧠 Multi-modal Support: Compatible with EEG, ECG, EMG, plant signals, and other biosignals

  • 🎨 Interactive GUI: Graphical interface for easy exploration

Installation#

2. Install from the GitHub Repository (Development Version)#

If you want the latest development version or contribute to the code, follow these steps:

2.2. Manual Setup (Alternative)#

If you prefer to set up the environment manually, follow these steps:

1️⃣ Create a Conda environment#
conda create --name biotuner_env python=3.11 -y
conda activate biotuner_env
2️⃣ Install dependencies#
pip install -r requirements.txt
pip install -e .

3. Verify Installation by Running Tests#

To confirm that Biotuner is installed correctly, run the test suite:

invoke test

or manually using:

pytest tests/

If all tests pass ✅, your installation is complete!

🎯 Summary#

  • For general users: Install via pip install biotuner

  • For development: Clone the repo and run invoke setup

  • To verify installation: Run invoke test

Simple use case#

Single Time Series Analysis#

from biotuner import compute_biotuner

# Initialize the object
biotuning = compute_biotuner(sf=1000)

# Extract spectral peaks
biotuning.peaks_extraction(data, peaks_function='FOOOF')

# Get consonance metrics for spectral peaks
biotuning.compute_peaks_metrics()

Group Analysis (🧪 BETA)#

Analyze multiple time series simultaneously with automatic aggregation and group comparisons:

from biotuner import BiotunerGroup
import numpy as np

# Multiple trials or electrodes: shape (n_series, n_samples)
data = np.random.randn(10, 5000)

# Create group object
btg = BiotunerGroup(data, sf=1000, axis_labels=['trials'])

# Run analysis pipeline
btg.compute_peaks(peaks_function='FOOOF', min_freq=1, max_freq=50)
btg.compute_metrics(n_harm=10)

# Get summary statistics
summary = btg.summary()

Note: The BiotunerGroup module is currently in beta. The API may change in future releases.

🌐 Biotuner Engine - Web Interface#

Explore Biotuner’s capabilities through our interactive web interface:

biotuner-engine.kairos-hive.org

The Biotuner Engine provides a user-friendly web application to analyze biosignals, visualize harmonic structures, and explore musical applications directly in your browser—no installation required!

Multimodal Harmonic Analysis

biotuner_multimodal_02

The figure above illustrates Biotuner’s ability to extract harmonic structures across different biological and physical systems. It showcases harmonic ratios detected in biosignals from the brain, heart, and plants, as well as their correspondence with audio signals. By analyzing the fundamental frequency relationships in these diverse modalities, Biotuner enables a cross-domain exploration of resonance and tuning in biological and artificial systems.

Biotuner_pipeline (6)-page-001

Peaks extraction methods#

biotuner_peaks_extraction

📚 Documentation & Resources#

🤝 Contributing#

We welcome contributions! Whether it’s:

  • 🐛 Bug reports

  • 💡 Feature requests

  • 📝 Documentation improvements

  • 🔧 Code contributions

Please feel free to open an issue or submit a pull request on GitHub.

📄 License#

Biotuner is licensed under the MIT License.

📖 Citation#

If you use Biotuner in your research, please cite our work. See the citation guide for more information.

💬 Support#

Made with ❤️ by the Biotuner development team

Indices and tables#

Contents