Heart Sound Segmentation Using Deep Learning Techniques

Manas Madine
6/9/2024
cs.SDcs.AIeess.AS

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Abstract

Heart disease remains a leading cause of mortality worldwide. Auscultation, the process of listening to heart sounds, can be enhanced through computer-aided analysis using Phonocardiogram (PCG) signals. This paper presents a novel approach for heart sound segmentation and classification into S1 (LUB) and S2 (DUB) sounds. We employ FFT-based filtering, dynamic programming for event detection, and a Siamese network for robust classification. Our method demonstrates superior performance on the PASCAL heart sound dataset compared to existing approaches.

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Cite this paper

@article{madine2024heart,
  title  = {Heart Sound Segmentation Using Deep Learning Techniques},
  author = {Manas Madine},
  year   = {2024},
  eprint = {2406.05653},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2406.05653v1}
}

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