Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/73855
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Type: Conference paper
Title: Thoraco-abdominal asynchrony in children during quiet sleep using Hilbert transform
Author: Immanuel, S.
Kohler, M.
Pamula, Y.
Kabir, M.
Saint, D.
Baumert, M.
Citation: Engineering Innovation in Global Health: Proceedings of the 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, held in San Diego, August 28-September 1, 2012: pp. 3448-3451
Publisher: IEEE
Publisher Place: CD
Issue Date: 2012
Series/Report no.: IEEE Engineering in Medicine and Biology Society Conference Proceedings
ISBN: 1457717875
9781424441198
ISSN: 1557-170X
Conference Name: Annual International Conference of the IEEE Engineering in Medicine and Biology Society (34th : 2012 : San Diego)
Statement of
Responsibility: 
Sarah Anita Immanuel, Mark Kohler, Yvonne Pamula, Muammar Muhammad Kabir, David Saint and Mathias Baumert
Abstract: We present a technique based on the Hilbert transform to quantify the thoraco-abdominal asynchrony (TAA) based on the phase shift between ribcage (RC) and abdomenal (AB) breathing signals acquired using respiratory inductive plethysmography (RIP). We employed this method to investigate RIP during overnight polysomnography (PSG) in 40 healthy children for analysis of their breathing patterns in various stages of sleep (ss 2, 3, 4 and REM) and in two common sleeping positions (supine and lateral). RIP signals free of respiratory or movement artifacts were segmented into 30 second epochs. Those epochs with maximum power in the quiet breathing frequency range and positional invariance throughout were included for further processing. TAA was calculated from corresponding RC and AB excursions. We found a statistically significant influence of sleep position on the level of TAA in all stages of non-REM sleep. In conclusion, the Hilbert transform provides a simple tool for the quantification of thoraco-abdominal asynchrony.
Keywords: Signal processing in physiological systems; nonlinear analysis of biomedical signals; nonlinear dynamics in biomedical signals
Rights: Copyright © 2012 IEEE Engineering in Medicine and Biology Society. All rights reserved.
RMID: 0020122325
DOI: 10.1109/EMBC.2012.6346707
Description (link): http://embs.papercept.net/conferences/conferences/EMBC12/program/EMBC12_ContentListWeb_2.html
Published version: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6320834
Appears in Collections:Electrical and Electronic Engineering publications

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