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Critical Reviews™ in Biomedical Engineering

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ISSN Druckformat: 0278-940X

ISSN Online: 1943-619X

SJR: 0.262 SNIP: 0.372 CiteScore™:: 2.2 H-Index: 56

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

Volumen 46, Ausgabe 1, 2018, pp. 33-52
DOI: 10.1615/CritRevBiomedEng.2018025112
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ABSTRAKT

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.

REFERENZIERT VON
  1. Klum Michael, Leib Fabian, Oberschelp Casper, Martens David, Pielmus Alexandru-Gabriel, Tigges Timo, Penzel Thomas, Orglmeister Reinhold, Wearable Multimodal Stethoscope Patch for Wireless Biosignal Acquisition and Long-Term Auscultation, 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019. Crossref

  2. Li Haixia, Ren Yongfeng, Zhang Guojun, Wang Renxin, Zhang Xiaoyong, Zhang Ting, Zhang Lansheng, Cui Jiangong, Xu QingDa, Duan Sicun, Design of a high SNR electronic heart sound sensor based on a MEMS bionic hydrophone, AIP Advances, 9, 1, 2019. Crossref

  3. Kimball Jacob P., Gazi Asim H., Ozmen Goktug Cihan, Jung Hewon, Shandhi Md Mobashir Hasan, Mabrouk Samer, Gharehbaghi Sevda, Ganti Venu G., Inan Omer T., Noninvasive Multimodal Physiological Sensing Systems: Design, Implementation and Validation, in Reference Module in Biomedical Sciences, 2021. Crossref

  4. Sait Unais, K.V. Gokul Lal, Shivakumar Sanjana, Kumar Tarun, Bhaumik Rahul, Prajapati Sunny, Bhalla Kriti, Chakrapani Anaghaa, A deep-learning based multimodal system for Covid-19 diagnosis using breathing sounds and chest X-ray images, Applied Soft Computing, 109, 2021. Crossref

  5. Petmezas Georgios, Cheimariotis Grigorios-Aris, Stefanopoulos Leandros, Rocha Bruno, Paiva Rui Pedro, Katsaggelos Aggelos K., Maglaveras Nicos, Automated Lung Sound Classification Using a Hybrid CNN-LSTM Network and Focal Loss Function, Sensors, 22, 3, 2022. Crossref

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