Auscultation of the respiratory system
TLDR
It is necessary to understand the underlying pathophysiology of various lung sounds generation for better understanding of disease processes in order to make correct diagnosis of respiratory disorders.Abstract:
Auscultation of the lung is an important part of the respiratory examination and is helpful in diagnosing various respiratory disorders Auscultation assesses airflow through the trachea-bronchial tree It is important to distinguish normal respiratory sounds from abnormal ones for example crackles, wheezes, and pleural rub in order to make correct diagnosis It is necessary to understand the underlying pathophysiology of various lung sounds generation for better understanding of disease processes Bedside teaching should be strengthened in order to avoid erosion in this age old procedure in the era of technological explosionread more
Citations
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Journal ArticleDOI
Automatic adventitious respiratory sound analysis: A systematic review.
TL;DR: The performance of recent studies showed a high agreement with conventional non-automatic identification and suggests that automated adventitious sound detection or classification is a promising solution to overcome the limitations of conventional auscultation and to assist in the monitoring of relevant diseases.
Journal ArticleDOI
Wearable Sensing and Telehealth Technology with Potential Applications in the Coronavirus Pandemic
Xiaorong Ding,David A. Clifton,Nan Ji,Nigel H. Lovell,Paolo Bonato,Wei Chen,Xinge Yu,Zhong Xue,Ting Xiang,Xi Long,Ke Xu,Xinyu Jiang,Qi Wang,Bin Yin,Guodong Feng,Yuan-Ting Zhang +15 more
TL;DR: Enable technologies and systems suitable for monitoring the populations at risk and those in quarantine, both for evaluating the health status of caregivers and management personnel, and for facilitating triage processes for admission to hospitals are reviewed.
Book ChapterDOI
Α Respiratory Sound Database for the Development of Automated Classification
Bruno Rocha,Dimitris Filos,Luis Mendes,I. I. Vogiatzis,Eleni Perantoni,Evangelos Kaimakamis,Pantelis Natsiavas,Ana Oliveira,Cristina Jácome,Alda Marques,Rui Pedro Paiva,Ioanna Chouvarda,Paulo Carvalho,Nicos Maglaveras +13 more
TL;DR: The first scientific challenge was organized with the main goal of developing algorithms able to characterize respiratory sound recordings derived from clinical and non-clinical environments, and it includes 920 recordings acquired from 126 subjects.
Journal ArticleDOI
An open access database for the evaluation of respiratory sound classification algorithms.
Bruno Rocha,Dimitris Filos,Luis Mendes,Gorkem Serbes,Sezer Ulukaya,Yasemin P. Kahya,Niksa Jakovljevic,Tatjana Loncar Turukalo,Ioannis M. Vogiatzis,Eleni Perantoni,Evangelos Kaimakamis,Pan Tells Natsiavas,Ana Oliveira,Cristina Jácome,Alda Marques,Nicos Maglaveras,Nicos Maglaveras,Rui Pedro Paiva,Ioanna Chouvarda,Paulo Carvalho +19 more
TL;DR: A public respiratory sound database is described, which was compiled for an international competition, the first scientific challenge of the IFMBE's International Conference on Biomedical and Health Informatics.
Book ChapterDOI
Hidden Markov Model Based Respiratory Sound Classification
TL;DR: This paper presents a method based on hidden Markov models in combination with Gaussian mixture models for classification of respiratory sounds into normal, wheeze and crackle classes.
References
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Journal ArticleDOI
Respiratory sounds : Advances beyond the stethoscope
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Progressive Airway Obliteration in Adults and its Association with Rheumatoid Disease
TL;DR: Six patients with rapidly progressive airway obliteration in the absence of chronic bronchitis or emphysema are reported, and five of the six patients had classical rheumatoid arthritis an association between the two diseases is suggested.
Journal ArticleDOI
Fundamentals of lung auscultation.
TL;DR: This short review of classic lung sounds includes both audio clips and interpretations made in the light of modern pulmonary acoustics.
Journal ArticleDOI
Analysis of Respiratory Sounds: State of the Art
TL;DR: The study includes a description of the various techniques that are being used to collect auscultation sounds, a physical description of known pathologic sounds for which automatic detection tools were developed, and a search for new markers to increase the efficiency of decision aid algorithms and tools.
Journal ArticleDOI
Spectral characteristics of normal breath sounds.
TL;DR: Breath sounds picked up over the trachea were characterized by power spectra typical to a broad spectrum sound with a sharp decrease of power at a cut-off frequency that varied between 850 and 1,600 Hz among the 10 healthy subjects studied.