2024
DOI: 10.20944/preprints202405.0829.v1
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

Benchmarking Time-Frequency Representations of PCG Signals for Classification Valvular Heart Diseases Using Deep Features and Machine Learning

Edwin M. Chambi,
Jefry Cuela,
Milagros Zegarra
et al.

Abstract: Heart sounds and murmurprovidecrucial diagnosis information for valvular heart diseases (VHD). Phonocardiogram (PCG) combined with modern digital processing techniques, provides a complementary tool for clinicians. This article proposes a benchmark different time-frequency representations, which are spectogram, mel-spectogram and cochleagram for obtaining images, in addition to the use of two interpolation techniques to improve the quality of the images, which are Bicubic and Lanczos. Deep features are extract… Show more

Help me understand this report
View published versions

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 42 publications
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?