Abnormal-respiration detection by considering correlation of observation of adventitious sounds

Matsutake, Shohei; Yamashita, Masaru; Matsunaga, Shoichi

doi:10.1109/eusipco.2015.7362460

Cited by 8 publications

(6 citation statements)

References 7 publications

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“…According to the literature on lung sound analysis, the most common respiratory diseases that are studied include COPD , 53,54,65,75,79,83,86,87,94,101,105,144 asthma, 53,54,65,71,72,85,87,105,107,110,117 and pulmonary emphysema. 58,70,93,99,106,112 However, lung sounds recorded during pneumonia, 54,65,76,79,103 pulmonary fibrosis, 56,70,76 chronic bronchitis, 56 idiopathic pulmonary fibrosis, 63 congestive heart failure, 76,79 parenchymal pathology, 75,90 and interstitial lung disease 79,87,104 appear less frequently in the literature. Regarding heart sound analysis, it is observed that murmurs 26,121,<...>…”

Section: Discussionmentioning

confidence: 99%

Lung and Heart Sounds Analysis: State-of-the-Art and Future Trends

Padilla-Ortiz

Ibarra

2018

Crit Rev Biomed Eng

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Lung sounds, which include all sounds that are produced during the mechanism of respiration, may be classified into normal breath sounds and adventitious sounds. Normal breath sounds occur when no respiratory problems exist, whereas adventitious lung sounds (wheeze, rhonchi, crackle, etc.) are usually associated with certain pulmonary pathologies. Heart and lung sounds that are heard using a stethoscope are the result of mechanical interactions that indicate operation of cardiac and respiratory systems, respectively. In this article, we review the research conducted during the last six years on lung and heart sounds, instrumentation and data sources (sensors and databases), technological advances, and perspectives in processing and data analysis. Our review suggests that chronic obstructive pulmonary disease (COPD) and asthma are the most common respiratory diseases reported on in the literature; related diseases that are less analyzed include chronic bronchitis, idiopathic pulmonary fibrosis, congestive heart failure, and parenchymal pathology. Some new findings regarding the methodologies associated with advances in the electronic stethoscope have been presented for the auscultatory heart sound signaling process, including analysis and clarification of resulting sounds to create a diagnosis based on a quantifiable medical assessment. The availability of automatic interpretation of high precision of heart and lung sounds opens interesting possibilities for cardiovascular diagnosis as well as potential for intelligent diagnosis of heart and lung diseases.

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Section: Discussionmentioning

confidence: 99%

Lung and Heart Sounds Analysis: State-of-the-Art and Future Trends

Padilla-Ortiz

Ibarra

2018

Crit Rev Biomed Eng

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“…Continuous Adventitious Sounds (CASs) are characterized by a long duration of more than 100 ms, such as rhonchi, stridor, and wheezing [ 14 ]. In recent years, several works have been published that carried out an exhaustive review of lung acoustic measurements [ 15 ] and signal processing methods [ 16 , 17 ] applied to adventitious sounds, most of them focused on detection [ 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 ] and classification tasks [ 16 , 17 , 24 , 25 , 26 , 27 , 28 , 29 ].…”

Section: Introductionmentioning

confidence: 99%

Monophonic and Polyphonic Wheezing Classification Based on Constrained Low-Rank Non-Negative Matrix Factorization

Cruz

Quesada

Ruiz-Reyes

et al. 2021

Sensors

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The appearance of wheezing sounds is widely considered by physicians as a key indicator to detect early pulmonary disorders or even the severity associated with respiratory diseases, as occurs in the case of asthma and chronic obstructive pulmonary disease. From a physician’s point of view, monophonic and polyphonic wheezing classification is still a challenging topic in biomedical signal processing since both types of wheezes are sinusoidal in nature. Unlike most of the classification algorithms in which interference caused by normal respiratory sounds is not addressed in depth, our first contribution proposes a novel Constrained Low-Rank Non-negative Matrix Factorization (CL-RNMF) approach, never applied to classification of wheezing as far as the authors’ knowledge, which incorporates several constraints (sparseness and smoothness) and a low-rank configuration to extract the wheezing spectral content, minimizing the acoustic interference from normal respiratory sounds. The second contribution automatically analyzes the harmonic structure of the energy distribution associated with the estimated wheezing spectrogram to classify the type of wheezing. Experimental results report that: (i) the proposed method outperforms the most recent and relevant state-of-the-art wheezing classification method by approximately 8% in accuracy; (ii) unlike state-of-the-art methods based on classifiers, the proposed method uses an unsupervised approach that does not require any training.

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“…In literature, sensor based medical devices such as Piezoelectric microphone (Himeshima et al, 2012;Homs-Corbera et al, 2004;Matsutake et al, 2015;Umeki et al, 2015), electret microphone (Güler et al, 2005), LS-60 microphone (Waitman et al, 2000) electronic stethoscope (Dokur, 2009;Himeshima et al, 2012;Matsutake et al, 2015;Nakamura et al, 2016;Umeki et al, 2015) have been used while recording the auscultation sounds. It is imperative to use very sensitive devices to hear very short and hoarse lung and heart sounds such as crackles, wheezes and murmurs.…”

Section: Digitization Of the Auscultation Soundsmentioning

confidence: 99%

Multimedia Respiratory Database (RespiratoryDatabase@TR): Auscultation Sounds and Chest X-rays

Altan¹,

Kutlu²,

Garbi³

et al. 2017

Natural and Engineering Sciences

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Auscultation is a method for diagnosis of especially internal medicine diseases such as cardiac, pulmonary and cardio-pulmonary by listening the internal sounds from the body parts. It is the simplest and the most common physical examination in the assessment processes of the clinical skills. In this study, the lung and heart sounds are recorded synchronously from left and right sides of posterior and anterior chest wall and back using two digital stethoscopes in Antakya State Hospital. The chest X-rays and the pulmonary function test variables and spirometric curves, the St. George respiratory questionnaire (SGRQ-C) are collected as multimedia and clinical functional analysis variables of the patients. The 4 channels of heart sounds are focused on aortic, pulmonary, tricuspid and mitral areas. The 12 channels of lung sounds are focused on upper lung, middle lung, lower lung and costophrenic angle areas of posterior and anterior sides of the chest. The recordings are validated and labelled by two pulmonologists evaluating the collected chest x-ray, PFT and auscultation sounds of the subjects. The database consists of 30 healthy subjects and 45 subjects with pulmonary diseases such as asthma, chronic obstructive pulmonary disease, bronchitis. The novelties of the database are the combination ability between auscultation sound results, chest X-ray and PFT; synchronously assessment capability of the lungs sounds; image processing based computerized analysis of the respiratory using chest X-ray and providing opportunity for improving analysis of both lung sounds and heart sounds on pulmonary and cardiac diseases.

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Abnormal-respiration detection by considering correlation of observation of adventitious sounds

Cited by 8 publications

References 7 publications

Lung and Heart Sounds Analysis: State-of-the-Art and Future Trends

Lung and Heart Sounds Analysis: State-of-the-Art and Future Trends

Monophonic and Polyphonic Wheezing Classification Based on Constrained Low-Rank Non-Negative Matrix Factorization

Multimedia Respiratory Database (RespiratoryDatabase@TR): Auscultation Sounds and Chest X-rays

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