pyPCG: a Python toolbox specialized for phonocardiography analysis
Our detection method outperformed all other tested methods on the fetal dataset and
achieved results comparable to the state of the art on the PhysioNet dataset. Accurate segmentation of signals is critical for the calculation of accurate statistical measures and the creation of classification models. Our toolbox contains functions for both feature extraction and calculation of statistics which are compatible with the previous steps. All of our methods can be fine tuned for specific datasets. pyPCG is available on https://pypcg-toolbox.readthedocs.io/en/latest/.
Authors
- Márton Áron Goda (ORCID: https://orcid.org/0000-0003-0120-5940)
- Miklós Koller (ORCID: https://orcid.org/0000-0001-6283-114X)
- Janka Hatvani
- Kristóf Müller
Institutions
- Technion – Israel Institute of Technology (IL)
- Pázmány Péter Catholic University (HU)
Publication Details
- Journal
- Physiological Measurement
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1088/1361-6579/ad9af7
- Citations
- 2
- Primary Topic
- Phonocardiography and Auscultation Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.84
Funders
- Nemzeti Kutatási, Fejlesztési és Innovaciós Alap