Welcome to pyPCG’s documentation!
A signal processing toolbox for processing phonocardiography (PCG) data. Including support for multiple data formats, segmentation based on envelope peak detection, and Markov model based methods, feature extraction, and statistics calculation.
Current version: 0.1b4
Planned release: August 2024
If you use pyPCG please cite the accompanying article:
Müller, J. Hatvani, M. Koller, and M. Á. Goda, “pyPCG: a Python toolbox specialized for phonocardiography analysis,” Physiological Measurement, vol. 45, p. 125007, dec 2024.
Introduction
pyPCG was created to standardize the multiple methods described in literature and to create a toolbox to streamline the use of common processing steps.
The main design was to create a framework which can be easily expanded and once a processing pipeline was created it can be reused without major modifications to the code.
We used type annotations in public functions to help development using this library.
Description
The modules implement the following steps:
Signal I/O
Separation of long signals to shorter ones
Signal quality index calculation
Denoising
Filtering
Envelope extraction
Peak detection and sorting
Segmentation
Feature extraction
Statistics calculation
Visualization
The basic flowchart of the pyPCG toolbox
Correspondence
Kristóf Müller (Phd student) PPCU-ITK, Budapest, Hungary