It causes a persistent cough which usually brings up phlegm (sputum), and breathlessness. 11 It can make the lungs more vulnerable to infection, resulting in a build-up of excess mucus. Bronchiectasis is a long-term condition where the airways of the lungs become abnormally widened. 10 The less severe infections can have the same symptoms as bronchiolitis or bronchiectasis. 9, 10 LRTI symptoms, on the other hand, vary and depend on the severity of the infection, and it is the leading cause of pediatric mortality and morbidity in low and middle-income countries. 8 URTIs affect the upper respiratory tract, including the nose, sinuses, pharynx, or larynx. 8 It is caused by several families of viruses, such as rhinovirus, coronavirus, parainfluenza, respiratory syncytial virus (RSV), adenovirus, human metapneumovirus, influenza, enterovirus, and the recently discovered bocavirus. An upper respiratory tract infection (URTI) is a respiratory illness that occurs commonly in both children and adults and is a major cause of mild morbidity. 7 It causes coughing that may cause mucus production, fever, chest pain, and shortness of breath. 5 Pneumonia is an infection that can be caused by bacteria, viruses, and fungi and inflames the air sacs called alveoli in one or both lungs. 4–6 It causes recurrent episodes of wheezing, breathlessness, chest tightness, and coughing, particularly at night or early in the morning. 2, 3 These symptoms are also common in asthma disease, 4 which is another most common and widespread lung diseases that is associated with airway obstruction in the lungs. 1–3 It causes breathing difficulty, cough, production of mucus (sputum), and wheezing. COPD is a common chronic inflammatory lung disease that is primarily caused by smoking. Chronic obstructive pulmonary disease (COPD), asthma, pneumonia, upper respiratory tract infection (URTI), lower respiratory tract infection (LRTI), bronchiectasis, bronchiolitis, and other disorders are examples. Lungs, the principal organs of the human respiratory system, can be affected by a variety of disorders. Keywords: auscultation, classification, denoising, discrete wavelet transform, feature extraction, lung diseases, lung sounds Results: A test classification accuracy of 99%, specificity of 99.2%, and sensitivity of 99.04%, have been achieved for the 7 lung diseases using the optimized Fine Gaussian SVM classifier.Ĭonclusion: Our experimental results demonstrate that the proposed method has the potential to be used as a decision support system for the classification of lung diseases, especially in those areas where the expertise and the means are limited. Model optimization was accomplished through the application of Bayesian optimization techniques. The classification accuracy of various machine learning classifiers was compared, and the Fine Gaussian SVM was chosen for final classification due to its superior performance. To choose the most relevant features, feature selection using one-way ANOVA was performed. Lung sounds were analyzed using a wavelet multiresolution analysis. Lung sound signals were then collected from people with COPD, upper respiratory tract infections (URTI), lower respiratory tract infections (LRTI), pneumonia, bronchiectasis, bronchiolitis, asthma, and healthy people. Methods: An electronic stethoscope has been constructed for signal acquisition. In this paper, a method for the acquisition of lung sound signals and classification of the top 7 lung diseases has been proposed for improving the efficacy of auscultation diagnosis of pulmonary disease. Moreover, the stethoscope recording is vulnerable to different noises that can mask the important features of lung sounds which may lead to misdiagnosis. However, the manual auscultation-based diagnosis procedure is prone to error, and its accuracy is dependent on the physician’s experience and hearing capacity. Stethoscope-based auscultation is the most commonly used, non-invasive, inexpensive, and primary diagnostic approach for assessing lung conditions. Purpose: Lung diseases are the third leading cause of death worldwide. Biruk Abera Tessema, 1, 2 Hundessa Daba Nemomssa, 1 Gizeaddis Lamesgin Simegn 1ġSchool of Biomedical Engineering, Jimma Institute of Technology, Jimma University, Jimma, Ethiopia 2School of Medicine, Haramaya University College of Health and Medical Sciences, Haramaya University, Harar, EthiopiaĬorrespondence: Hundessa Daba Nemomssa, Tel +251913763777, Email
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