Temporal convolutional neural network-based feature extraction and asynchronous channel information fusion method for heart abnormality detection in phonocardiograms.

Journal: Computer methods and programs in biomedicine
Published Date: May 21, 2025

Abstract

BACKGROUND AND OBJECTIVE: Auscultation-based cardiac abnormality detection is valuable screening approach in pediatric populations, particularly in resource-limited settings. However, its clinical utility is often limited by phonocardiogram (PCG) signal variability and a difficulty in distinguishing between pathological and innocent murmurs.

Authors

  • Jae-Man Shin
    Department of Biomedical Engineering, University of Ulsan College of Medicine, Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, Seoul, Korea.
  • Seongyong Park
    Department of Bio and Brain Engineering, KAIST, Daejeon 34141, Korea.
  • Keewon Shin
    Department of Biomedical Engineering, Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
  • Woo-Young Seo
    Biomedical Engneering Research Center, Asan Medical Center, Seoul 05505, Korea.
  • Hyun-Seok Kim
    Section of Gastroenterology and Hepatology, Baylor College of Medicine, Houston, Texas.
  • Dong-Kyu Kim
    Department of Otorhinolaryngology-Head and Neck Surgery.
  • Baehun Moon
    Department of Anesthesiology and Pain Medicine, BK21 Project, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
  • Seul-Gi Cha
    Division of Pediatric Cardiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
  • Won-Jung Shin
    Department of Anesthesiology and Pain Medicine, BK21 Project, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
  • Sung-Hoon Kim
    Asan Medical Center, Department of Anesthesiology and Pain Medicine, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Seoul 05505, Korea.

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