PhysioZoo OBM 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

Description

Five types of biomarkers may be evaluated:

  1. General statistics: time-based statistics describing the oxygen saturation time series data distribution.

  2. Complexity: quantify the presence of long-range correlations in non-stationary time series.

  3. Periodicity: quantify consecutive events creating some periodicity in the oxygen saturation time series.

  4. Desaturations: time-based measures that are descriptive statistics of the desaturation patterns happening throughout the time series.

  5. Hypoxic burden: time-based measures quantifying the overall degree of hypoxemia imposed to the heart and other organs during the recording period.

Installation

Available on pip, with the command: pip install pobm

pip project: https://pypi.org/project/pobm/

Requirements

numpy==1.18.2

scikit-learn==0.22.2

scipy==1.4.1

lempel-ziv-complexity==0.2.2

All the requirements are installed when the toolbox is installed, no need for additional commands.