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Virginia Commonwealth University

Development of a Software Application to Extract the Features of Normal Respiratory Sounds from the Lungs and the Trachea

Abstract

dc:description.abstract

Auscultation has been widely regarded as one of the most important noninvasive diagnostic tools for clinical diagnosis of the respiratory tract. The purpose of this thesis was to develop a software application capable of extracting the key features of respiratory sound signals from the lungs and trachea of healthy persons. The efficacy of the program was evaluated by the verification of the important features of the sound signals from the left and right lungs and the trachea such as 1) right and left lung symmetry and 2) dissimilarity between the trachea and both lungs. The program was developed in LabView and was designed to capture the respiratory sound signals from the lungs and the trachea in real-time and process them in the time and frequency domains for further analysis. The features compared were 1) signal amplitude in the time domain and 2) power spectra in the frequency domain. Results of the study had shown that the program had been able to verify that 1) the key features of the breath sound signals from the left and right lungs were similar and 2) the features of the signals from the trachea and both lungs were different.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
Thesis
Discipline thesis:degree_discipline
Biomedical Engineering
Year dc:date.available
2006

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Sabarinathan, Ranjani
Contributors dc:contributor
  • Dr. Ding-Yu Fei

Subjects

dc:subject × 10

Rights

dc:rights
Statement dc:rights
  • © The Author

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:scholarscompass.vcu.edu:etd-2177

Chain of custody

source
Harvested from
Virginia Commonwealth University
Base URL
scholarscompass.vcu.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Sabarinathan, Ranjani. Development of a Software Application to Extract the Features of Normal Respiratory Sounds from the Lungs and the Trachea. Thesis thesis, 2006. https://doi.org/10.25772/FQTA-ZW87