Combination of frequency and amplitude-modulated model for the synthesis of normal and wheezing sounds
Journal
Australasian Physical and Engineering Sciences in Medicine
Journal Volume
34
Journal Issue
4
Pages
449-457
Date Issued
2011
Author(s)
Abstract
Based on communication theory, this study proposes a model to synthesize normal and wheezing sounds. The model included five parts: the flow source as a transmitter, the frequency and amplitude-modulated (FM-AM) sounds, the accompanying noise as a modulator, the airway wall as a medium, and the microphone as a receiver. The hypothesis of modulation builds on that the deviation of frequency and amplitude of the sounds which cause from the deviation of collision speed of the air flow on the wall. The model was successful to simulate the normal breath and wheezing sounds. Furthermore, it provided a correct proof for the CORSA description, which indicates that the wheeze was contained in the domain frequency at 400 Hz, but a number of investigators have suggested that the range is actually between 80-1,600 Hz and 350-950 Hz by filter theory. This study modifies the signal source in Wodicka et al. model, and describes it in functional blocks. In fact, the design of the signal source base on the knowledge of the lung sound studies, especially the analysis of components in the frequency and time domains. We synthesized the required components to reproduce the lung sounds, and proposed a mechanism of wheeze which was examined by the computer simulation in the points of the system engineering view. ? 2011 Australasian College of Physical Scientists and Engineers in Medicine.
SDGs
Other Subjects
Air flow; Airway walls; Amplitude-modulated; Collision speed; Filter theory; Frequency and time domains; Functional block; Lung sounds; Respiration acoustic signal; Signal source; Wheeze; Biological organs; Computer simulation; Information theory; Models; Time domain analysis; Amplitude modulation; abnormal respiratory sound; article; biological model; computer simulation; human; methodology; signal processing; sound detection; Computer Simulation; Humans; Models, Biological; Respiratory Sounds; Signal Processing, Computer-Assisted; Sound Spectrography
Type
journal article