PhysioZoo SpO2 documentation¶
Oximetry digital biomarkers for the analysis of continuous oximetry (SpO2) time series.
Based on the paper Jeremy Levy, Daniel ́Alvarez, Aviv A Rosenberg, Alexandra Alexandrovich, F ́elix Del Campo, and Joachim ABehar. Digital oximetry biomarkers for assessing respiratory function: standards of measurement, physiologicalinterpretation, and clinical use.NPJ digital medicine, 4(1):1–14, 2021
Five types of biomarkers may be evaluated:
General statistics: time-based statistics describing the oxygen saturation time series data distribution.
Complexity: quantify the presence of long-range correlations in non-stationary time series.
Periodicity: quantify consecutive events creating some periodicity in the oxygen saturation time series.
Desaturations: time-based measures that are descriptive statistics of the desaturation patterns happening throughout the time series.
Hypoxic burden: time-based measures quantifying the overall degree of hypoxemia imposed to the heart and other organs during the recording period.
Available on pip, with the command: pip install pobm
pip project: https://pypi.org/project/pobm/
All the requirements are installed when the toolbox is installed, no need for additional commands.
Available at https://oximetry-toolbox.readthedocs.io/en/latest/
An example code is available at https://github.com/aim-lab/SPO2_tutorial/blob/main/MIT_Workshop_POBM_last.ipynb
- pobm package
- Oximetry time series analysis