NeoSSNet: Real-Time Neonatal Chest Sound Separation Using Deep Learning

NeoSSNet: Real-Time Neonatal Chest Sound Separation Using Deep Learning

<italic>Goal:</italic> Auscultation for neonates is a simple and non-invasive method of diagnosing cardiovascular and respiratory disease. However, obtaining high-quality chest sounds containing only heart or lung sounds is non-trivial. Hence, this study introduces a new deep-learning mo...

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Bibliographic Details
Main Authors: Yang Yi Poh, Ethan Grooby, Kenneth Tan, Lindsay Zhou, Arrabella King, Ashwin Ramanathan, Atul Malhotra, Mehrtash Harandi, Faezeh Marzbanrad
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Open Journal of Engineering in Medicine and Biology
Subjects:
Deep learning
heart sound
lung sound
phonocardiogram (PCG)
single-channel sound separation
Online Access:https://ieeexplore.ieee.org/document/10531026/
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https://ieeexplore.ieee.org/document/10531026/

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