A Blind Filtering Framework for Noisy Neonatal Chest Sounds-Reference-Cited by-同舟云学术

A Blind Filtering Framework for Noisy Neonatal Chest Sounds

Published:2022 Issue: Volume:10 Page:50715-50727
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Fattahi Davood¹^ORCID,Sameni Reza²,Grooby Ethan¹^ORCID,Tan Kenneth³,Zhou Lindsay³,King Arrabella³,Ramanathan Ashwin³,Malhotra Atul³^ORCID,Marzbanrad Faezeh¹^ORCID

Affiliation:

1. Department of Electrical and Computer Systems Engineering, Monash University, Clayton, VIC, Australia

2. Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA, USA

3. Monash Newborn, Monash Children’s Hospital, Clayton, VIC, Australia

Funder

Monash Institute of Medical Engineering

Monash Data Future Institute

MIME-Monash Partners-Commonwealth Scientific and Industrial Research Organisation (CSIRO) Sponsored Ph.D. Research Support and Australian Government Research Training Program (RTP) Scholarship

Royal Australasian College of Physicians Research Fellowship

Advancing Women’s Research Success Grant Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09762701.pdf?arnumber=9762701

Reference70 articles.

1. Blind source separation of heart and lung sounds based on nonnegative matrix factorization

2. Fetal phonocardiogram extraction using single channel blind source separation

3. Analyse des signaux acoustiques respiratoires: Contribution à la détection automatique des sibilants par paquets d’ondelettes;bahoura,1999

4. Standardization of computerized respiratory sound analysis: Basic techniques for respiratory sound analysis;charbonneau;Eur Respiratory Rev,2000

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