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  1. Medical and Biological Engineering and Computing
  2. Medical and Biological Engineering and Computing : Volume 50
  3. Medical and Biological Engineering and Computing : Volume 50, Issue 3, March 2012
  4. Acoustic breath-phase detection using tracheal breath sounds
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Medical and Biological Engineering and Computing : Volume 55
Medical and Biological Engineering and Computing : Volume 54
Medical and Biological Engineering and Computing : Volume 53
Medical and Biological Engineering and Computing : Volume 52
Medical and Biological Engineering and Computing : Volume 51
Medical and Biological Engineering and Computing : Volume 50
Medical and Biological Engineering and Computing : Volume 50, Issue 12, December 2012
Medical and Biological Engineering and Computing : Volume 50, Issue 11, November 2012
Medical and Biological Engineering and Computing : Volume 50, Issue 10, October 2012
Medical and Biological Engineering and Computing : Volume 50, Issue 9, September 2012
Medical and Biological Engineering and Computing : Volume 50, Issue 8, August 2012
Medical and Biological Engineering and Computing : Volume 50, Issue 7, July 2012
Medical and Biological Engineering and Computing : Volume 50, Issue 6, June 2012
Medical and Biological Engineering and Computing : Volume 50, Issue 5, May 2012
Medical and Biological Engineering and Computing : Volume 50, Issue 4, April 2012
Medical and Biological Engineering and Computing : Volume 50, Issue 3, March 2012
An explanation for the effectiveness of the ‘Draijer’ algorithm for high speed laser Doppler perfusion imaging
Indirect measurement of pinch and pull forces at the shaft of laparoscopic graspers
Error potential detection during continuous movement of an artificial arm controlled by brain–computer interface
Robust extraction of P300 using constrained ICA for BCI applications
Asymptotic model of electrical stimulation of nerve fibers
Wear analysis of chamfered elongated acetabular cup liners
Point process time–frequency analysis of dynamic respiratory patterns during meditation practice
Modeling hemodynamics in an unoccluded and partially occluded inferior vena cava under rest and exercise conditions
Targeting an efficient target-to-target interval for P300 speller brain–computer interfaces
Acoustic breath-phase detection using tracheal breath sounds
The theory of velocity selective neural recording: a study based on simulation
Medical and Biological Engineering and Computing : Volume 50, Issue 2, February 2012
Medical and Biological Engineering and Computing : Volume 50, Issue 1, January 2012
Medical and Biological Engineering and Computing : Volume 49
Medical and Biological Engineering and Computing : Volume 48
Medical and Biological Engineering and Computing : Volume 47
Medical and Biological Engineering and Computing : Volume 46
Medical and Biological Engineering and Computing : Volume 45
Medical and Biological Engineering and Computing : Volume 44
Medical and Biological Engineering and Computing : Volume 43
Medical and Biological Engineering and Computing : Volume 42
Medical and Biological Engineering and Computing : Volume 41
Medical and Biological Engineering and Computing : Volume 40
Medical and Biological Engineering and Computing : Volume 39
Medical and Biological Engineering and Computing : Volume 38
Medical and Biological Engineering and Computing : Volume 37
Medical and Biological Engineering and Computing : Volume 36
Medical and Biological Engineering and Computing : Volume 35

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Acoustic breath-phase detection using tracheal breath sounds

Content Provider SpringerLink
Author Huq, Saiful Moussavi, Zahra
Copyright Year 2012
Abstract Current breathing flow estimation methods use tracheal breath sounds, but one step of the process, ‘breath phase (inspiration/expiration) detection’, is done by either assuming alternating breath phases or using a second acoustic channel of lung sounds. The alternating assumption is unreliable for long recordings, non-breathing events, such as apnea, swallow or cough change the alternating nature of the phases. Using lung sounds intensity requires the addition of a secondary channel and the associated labor. Hence, an automatic and accurate method for breath-phase detection using only tracheal sounds would be of great benefit. We present a method using several breath sound parameters to differentiate between the two respiratory phases. The proposed method is novel and independent of flow level; it requires only one prior- and one post-breath sound segment to identify the phase. The proposed method was tested on data from 93 healthy individuals, without any history of pulmonary diseases breathing at 4 different flow levels. The most prominent features were from the duration, volume and shape of the sound envelope. This method has shown an accuracy of 95.6% with 95.5% sensitivity and 95.6% specificity for breath-phase identification without assuming breath-phase-alteration and/or using any other information.
Starting Page 297
Ending Page 308
Page Count 12
File Format PDF
ISSN 01400118
Journal Medical and Biological Engineering and Computing
Volume Number 50
Issue Number 3
e-ISSN 17410444
Language English
Publisher Springer-Verlag
Publisher Date 2012-02-24
Publisher Place Berlin, Heidelberg
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Flow estimation Tracheal sounds Breath-phase detection Sound intensity Classification Human Physiology Computer Applications Imaging Radiology Biomedical Engineering
Content Type Text
Resource Type Article
Subject Biomedical Engineering Computer Science Applications
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