Respiratory sound denoising using sparsity-assisted signal smoothing algorithm

• Autorzy: Haider Nishi Shahnaj , Behera Ajoy K.

Identyfikatory

DOI

10.1016/j.bbe.2022.03.005

• Języki publikacji: EN

Abstrakty

EN

Noises are the unavoidable entities which stands as a big barrier in the field of computerized lung sound (LS) based disease diagnosis, as it impairs the quality of LS and therefore greatly misleads the clinical interpretations done based on that. It has numerous sources, of which a few of them could be the noises due to body sounds, environmental noises, power line noises and recording artifacts, which easily contaminates the LS recordings. This paper presents a novel denoising algorithm to eliminate the noises from LS recordings in a more powerful way using Butterworth band-pass filter and sparsity assisted signal smoothing (SASS) algorithm. This study is carried out over LS captured from 80 Chronic Obstructive Pulmonary Disease (COPD), 80 pneumonia and 80 healthy participants in a clinical environment. Each of the recorded LS is denoised using Butterworth band-pass filter and sparse-assisted signal smoothing algorithm. The denoising performance of the proposed algorithm is evaluated on the basis of denoising performance parameters. As per the evaluation of the denoising performance parameters, it is observed that the proposed denoising method suppressed the LS noises with the signal to noise ratio (SNR) of 66.8 dB and with the peak signal to noise ratio (PSNR) of 78.5 dB. The proposed endeavour can be recommended for clinical use for producing noise free LSs to bring effective interpretations. The future endeavours involve the suppression of the heart sound noises from the LS recordings.

Słowa kluczowe

EN

chronic obstructive pulmonary disease; COPD; lung sound; pneumonia diagnosis; sparsity assisted signal smoothing

PL

przewlekła obturacyjna choroba płuc; COPD; zapalenie płuc

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2022
• Tom: Vol. 42, no. 2
• Strony: 481--493
• Opis fizyczny: Bibliogr. 27 poz., rys., tab., wykr.

Twórcy

autor

Haider Nishi Shahnaj

• Department of Biomedical Engineering, V.S.B. Engineering College, Karur, Tamil Nadu, 639111, India

autor

Behera Ajoy K.

• Department of Pulmonary Medicine & TB, All India Institute of Medical Sciences, Raipur, Chhattisgarh, India

Bibliografia

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