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/.

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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

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article

pyPCG: a Python toolbox specialized for phonocardiography analysis

Márton Áron Goda, Miklós Koller, Janka Hatvani, Kristóf Müller
2 citations
Physiological Measurement
Phonocardiography and Auscultation Techniques
0.84
article

pyPCG: a Python toolbox specialized for phonocardiography analysis

Márton Áron Goda, Miklós Koller, Janka Hatvani, Kristóf Müller
article en
2 citations

Abstract

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/.

Physiological MeasurementVol. 45(12)
Technion – Israel Institute of Technology (IL), Pázmány Péter Catholic University (HU)
Nemzeti Kutatási, Fejlesztési és Innovaciós Alap
Openalex Percentile: Top 22%
Phonocardiography and Auscultation Techniques
0.84
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