Publication
Title
JAMF-based representation for computational lung sound analysis
Author
Abstract
Obstructive lung disease is a category of respiratory disease characterized by an obstruction of the airflow, inflamed and/or easily collapsible airways, and mucus retention. Asthma, bronchiectasis, and chronic obstructive pulmonary disease (COPD) are the three main types of obstructive lung diseases. This type of diseases causes adventitious lung sounds which can be heard through lung auscultation. Physiotherapists can detect these sounds and use them to adapt their treatment. Physicians the world over are starting to rely more on computers than ever before. For lung auscultation data, this is mostly limited to representing the sound as a time-pressure graph or a spectrogram, while still doing the actual analysis themselves. Researchers however, have already shown the strength of computational lung sound analysis. In this paper, we propose the Joint Acoustic-and Modulation Frequency (JAMF) representation as a signal-processing technique for a lung-sound sensor which create a visually clean, simple and yet powerful representation which allows physicians to determine possible problems at first glance, with future possibilities for easy automatic analysis of the lung sounds.
Language
English
Source (journal)
Proceedings of IEEE Sensors. - Piscataway, NJ, 2002, currens
Source (book)
2015 IEEE SENSORS, NOV 01-04, 2015, Busan, SOUTH AFRICA
Publication
New york : Ieee , 2015
ISSN
1930-0395
ISBN
978-1-4799-8203-5
978-1-4799-8203-5
978-1-4799-8202-8
DOI
10.1109/ICSENS.2015.7370198
Volume/pages
(2015) , p. 142-145
ISI
000380440800037
Full text (Publisher's DOI)
Full text (publisher's version - intranet only)
UAntwerpen
Faculty/Department
Research group
Project info
Development and validation of an ambulatory 3D motion capture based model to assess trunk performance and locomotion after stroke.
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identifier
Creation 06.10.2016
Last edited 09.10.2023
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