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Respiratory sound denoising using sparsity-assisted signal smoothing algorithm

  • Published:2022-04 Issue:2 Volume:42 Page:481-493
  • ISSN:0208-5216
  • Container-title:Biocybernetics and Biomedical Engineering
  • language:en
  • Short-container-title:Biocybernetics and Biomedical Engineering

Author:

Haider Nishi Shahnaj,Behera Ajoy K.

Publisher

Elsevier BV

Subject

Biomedical Engineering

Reference27 articles.

1. Auscultation of the respiratory system;Sarkar;Annals Thoracic Med,2015

2. Respiratory sound analysis in the era of evidence-based medicine and the world of medicine 2.0;Andrès;J Med Life,2018

3. An investigation on the statistical significance of spectral signatures of lung sounds;Haider;Biomed Res (0970–938X),2017

4. Characterization of noise contaminations in lung sound recordings;Emmanouilidou,2013

5. Respiratory sound classification for crackles, wheezes, and rhonchi in the clinical field using deep learning;Kim;Sci Rep,2021

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1. Automatic breathing phase identification based on the second derivative of the recorded lung sounds;Biomedical Signal Processing and Control;2024-08

2. Efficient Noise Cancellation in Lung Signals Using Pipelined Adaptive LMS Algorithm;2024 International Conference on Smart Systems for Electrical, Electronics, Communication and Computer Engineering (ICSSEECC);2024-06-28

3. Hybrid method for noise rejection from breath sound using transient artifact reduction algorithm and spectral subtraction;Biomedical Engineering / Biomedizinische Technik;2024-03-21

4. Full-field deformation measurement and cracks detection in speckle scene using the deep learning-aided digital image correlation method;Mechanical Systems and Signal Processing;2024-03

5. Deep learning-based lung sound analysis for intelligent stethoscope;Military Medical Research;2023-09-26
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