Cardiopulmonary auscultation enhancement with a two-stage noise cancellation approach-Reference-Cited by-同舟云学术

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Cardiopulmonary auscultation enhancement with a two-stage noise cancellation approach

Published:2023-01 Issue: Volume:79 Page:104175
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Yang Chunjian,Dai Neng,Wang Zhi,Cai Shengsheng,Wang Jiajun,Hu Nan

Funder

Science and Technology Program of Suzhou

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing,Biomedical Engineering

Reference48 articles.

1. The Stethoscope Gets Smart: Engineers from Johns Hopkins are giving the humble stethoscope an AI upgrade;Elhilali;IEEE Spectr.,2019

2. Design and comparative performance of a robust Lung auscultation system for noisy clinical settings;McLane;IEEE J. Biomed. Health. Inf.,2021

3. Optimal wavelet denoising for phonocardiograms;Messer;Microelectron. J.,2001

4. O. Beya, B. Jalil, E. Fauvet, and O. Laligant, Empirical modal decomposition applied to cardiac signals analysis, in: Proc. of SPIE-IS&T Electronic Imaging, vol. 7535, Feb. 2010, pp. 1–11.

5. M. K. Zia, B. Griffel, and J. L. Semmlow, Robust detection of background noise in phonocardiograms, in: Proc. first Middle East Conf. Biomed. Eng., 2011, pp. 130–133.

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1. Enhancing Fetal Electrocardiogram Signal Extraction Accuracy through a CycleGAN Utilizing Combined CNN–BiLSTM Architecture;Sensors;2024-05-06

2. Developing an AI-assisted digital auscultation tool for automatic assessment of the severity of mitral regurgitation: protocol for a cross-sectional, non-interventional study;BMJ Open;2024-03

3. Electrostatic Acoustic Sensor with an Impedance-Matched Diaphragm Characterized for Body Sound Monitoring;ACS Applied Bio Materials;2023-07-20

4. Monaural cardiopulmonary sound separation via complex-valued deep autoencoder and cyclostationarity;Biomedical Physics & Engineering Express;2023-03-01

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