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PySio: A New Python Toolbox for Physiological Signal Visualization and Feature Analysis.

Ozgun Ozan Nacitarhan, Beren Semiz

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |September 9, 2022
    PubMed
    Summary

    PySio is a new Python toolbox for analyzing physiological signals. It offers user-friendly tools for time and frequency domain analysis, extracting key features for research and applications.

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    Area of Science:

    • Physiological signal analysis
    • Biomedical data science
    • Computational physiology

    Background:

    • MATLAB has been dominant in signal processing, but Python is rising due to data science, machine learning, and AI.
    • A Python-native package is needed for physiological feature analysis to integrate with existing Python-based machine learning models.
    • Physiological signals contain valuable information about a subject's state and changes.

    Purpose of the Study:

    • Introduce PySio, a novel Python toolbox for rapid, efficient, and user-friendly physiological signal analysis and visualization.
    • Enable seamless integration of physiological signal analysis into Python-based machine learning and AI workflows.
    • Provide a comprehensive suite of tools for both time and frequency domain analysis of physiological data.

    Main Methods:

    • Importing physiological signals with their sampling rates.
    • Analyzing signals in the time domain (visualization, segmentation).
    • Analyzing signals in the frequency domain using Discrete Fourier Transform and spectrograms.
    • Extracting common time-domain features (energy, entropy, zero crossing rate, peaks).
    • Extracting common frequency-domain features (spectral entropy, rolloff, centroid, spread, peaks, bandpower).

    Main Results:

    • PySio provides one-click access to signal visualization and feature extraction.
    • The toolbox supports analysis of entire signals or user-selected segments.
    • Offers both time and frequency domain analysis capabilities within a single package.

    Conclusions:

    • PySio facilitates efficient and user-friendly analysis of physiological signals in Python.
    • The toolbox supports the extraction of crucial physiological features for downstream applications.
    • Enables advancements in personalized treatment and wearable technology through enhanced signal analysis.