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Computer-based respiratory sound analysis: a systematic review

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Main Authors: Palaniappan, Rajkumar, Sundaraj, Kenneth, Prof. Dr., Nizam Uddin, Ahamed, Arjunan, Agilan, Sundaraj, Sebastian
Other Authors: prkmect@gmail.com
Format: Article
Language:English
Published: Medknow publications 2014
Subjects:
Lung disorder
Machine learning
Respiratory sound
Review
Statistical
Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/33285
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spelling my.unimap-332852014-04-01T01:58:40Z Computer-based respiratory sound analysis: a systematic review Palaniappan, Rajkumar Sundaraj, Kenneth, Prof. Dr. Nizam Uddin, Ahamed Arjunan, Agilan Sundaraj, Sebastian prkmect@gmail.com kenneth@unimap.edu.my ahamed1557@hotmail.com agilansc@gmail.com seby1984@gmail.com Lung disorder Machine learning Respiratory sound Review Statistical Link to publisher's homepage at http://www.medknow.com/ Over the years, lung auscultation has been used as an effective clinical tool to monitor the state of the respiratory system. Lung auscultation provides valuable information regarding the patient's respiratory function. Recent technical advances have led to the development of computer-based respiratory sound analysis which serves as a powerful tool to diagnose abnormalities and disorders in the lung. This paper provides a comprehensive review on computer-based respiratory sound analysis techniques employed by various researchers in the past. The search for articles related to computer-based respiratory sound analysis was carried out on electronic resources such as IEEE, Springer, Elsevier, Pub Med, and ACM digital library databases. Around 55 articles were identified and were subjected to a systematic review. In this review, we examine lung sound/lung disorder, sensor used, sensor locations, number of subjects, signal processing methods, classification methods, and statistical methods employed for the analysis of lung sounds by previous researchers. A brief discussion is undertaken on the overview from the previous works. Finally, the review is concluded by discussing the possibilities and recommendations for further improvements. 2014-04-01T01:58:40Z 2014-04-01T01:58:40Z 2013 Article IETE Technical Review, vol. 30(3), 2013, pages 248-256 0256-4602 http://dspace.unimap.edu.my:80/dspace/handle/123456789/33285 http://www.medknow.com/searcharticle.asp?author=palaniappan%2C+rajkumar&search=&journal=Y&entries=10&pg=1&s=0 10.4103/0256-4602.113524 en Medknow publications
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Lung disorder
Machine learning
Respiratory sound
Review
Statistical
spellingShingle Lung disorder
Machine learning
Respiratory sound
Review
Statistical
Palaniappan, Rajkumar
Sundaraj, Kenneth, Prof. Dr.
Nizam Uddin, Ahamed
Arjunan, Agilan
Sundaraj, Sebastian
Computer-based respiratory sound analysis: a systematic review
description Link to publisher's homepage at http://www.medknow.com/
author2 prkmect@gmail.com
author_facet prkmect@gmail.com
Palaniappan, Rajkumar
Sundaraj, Kenneth, Prof. Dr.
Nizam Uddin, Ahamed
Arjunan, Agilan
Sundaraj, Sebastian
format Article
author Palaniappan, Rajkumar
Sundaraj, Kenneth, Prof. Dr.
Nizam Uddin, Ahamed
Arjunan, Agilan
Sundaraj, Sebastian
author_sort Palaniappan, Rajkumar
title Computer-based respiratory sound analysis: a systematic review
title_short Computer-based respiratory sound analysis: a systematic review
title_full Computer-based respiratory sound analysis: a systematic review
title_fullStr Computer-based respiratory sound analysis: a systematic review
title_full_unstemmed Computer-based respiratory sound analysis: a systematic review
title_sort computer-based respiratory sound analysis: a systematic review
publisher Medknow publications
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/33285
_version_ 1643797125032574976
score 13.222552

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