Evidence towards improved estimation of respiratory muscle effort from diaphragm mechanomyographic signals with cardiac vibration interference using sample entropy with fixed tolerance values.

The analysis of amplitude parameters of the diaphragm mechanomyographic (MMGdi) signal is a non-invasive technique to assess respiratory muscle effort and to detect and quantify the severity of respiratory muscle weakness. The amplitude of the MMGdi signal is usually evaluated using the average rect...

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Autores principales:	Leonardo Sarlabous, Abel Torres, José A Fiz, Raimon Jané
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/25058caaaebf4faaa5380cad8c5296f2
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spelling	oai:doaj.org-article:25058caaaebf4faaa5380cad8c5296f22021-11-18T08:32:02ZEvidence towards improved estimation of respiratory muscle effort from diaphragm mechanomyographic signals with cardiac vibration interference using sample entropy with fixed tolerance values.1932-620310.1371/journal.pone.0088902https://doaj.org/article/25058caaaebf4faaa5380cad8c5296f22014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24586436/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203The analysis of amplitude parameters of the diaphragm mechanomyographic (MMGdi) signal is a non-invasive technique to assess respiratory muscle effort and to detect and quantify the severity of respiratory muscle weakness. The amplitude of the MMGdi signal is usually evaluated using the average rectified value or the root mean square of the signal. However, these estimations are greatly affected by the presence of cardiac vibration or mechanocardiographic (MCG) noise. In this study, we present a method for improving the estimation of the respiratory muscle effort from MMGdi signals that is robust to the presence of MCG. This method is based on the calculation of the sample entropy using fixed tolerance values (fSampEn), that is, with tolerance values that are not normalized by the local standard deviation of the window analyzed. The behavior of the fSampEn parameter was tested in synthesized mechanomyographic signals, with different ratios between the amplitude of the MCG and clean mechanomyographic components. As an example of application of this technique, the use of fSampEn was explored also in recorded MMGdi signals, with different inspiratory loads. The results with both synthetic and recorded signals indicate that the entropy parameter is less affected by the MCG noise, especially at low signal-to-noise ratios. Therefore, we believe that the proposed fSampEn parameter could improve estimates of respiratory muscle effort from MMGdi signals with the presence of MCG interference.Leonardo SarlabousAbel TorresJosé A FizRaimon JanéPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 2, p e88902 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Leonardo Sarlabous Abel Torres José A Fiz Raimon Jané Evidence towards improved estimation of respiratory muscle effort from diaphragm mechanomyographic signals with cardiac vibration interference using sample entropy with fixed tolerance values.
description	The analysis of amplitude parameters of the diaphragm mechanomyographic (MMGdi) signal is a non-invasive technique to assess respiratory muscle effort and to detect and quantify the severity of respiratory muscle weakness. The amplitude of the MMGdi signal is usually evaluated using the average rectified value or the root mean square of the signal. However, these estimations are greatly affected by the presence of cardiac vibration or mechanocardiographic (MCG) noise. In this study, we present a method for improving the estimation of the respiratory muscle effort from MMGdi signals that is robust to the presence of MCG. This method is based on the calculation of the sample entropy using fixed tolerance values (fSampEn), that is, with tolerance values that are not normalized by the local standard deviation of the window analyzed. The behavior of the fSampEn parameter was tested in synthesized mechanomyographic signals, with different ratios between the amplitude of the MCG and clean mechanomyographic components. As an example of application of this technique, the use of fSampEn was explored also in recorded MMGdi signals, with different inspiratory loads. The results with both synthetic and recorded signals indicate that the entropy parameter is less affected by the MCG noise, especially at low signal-to-noise ratios. Therefore, we believe that the proposed fSampEn parameter could improve estimates of respiratory muscle effort from MMGdi signals with the presence of MCG interference.
format	article
author	Leonardo Sarlabous Abel Torres José A Fiz Raimon Jané
author_facet	Leonardo Sarlabous Abel Torres José A Fiz Raimon Jané
author_sort	Leonardo Sarlabous
title	Evidence towards improved estimation of respiratory muscle effort from diaphragm mechanomyographic signals with cardiac vibration interference using sample entropy with fixed tolerance values.
title_short	Evidence towards improved estimation of respiratory muscle effort from diaphragm mechanomyographic signals with cardiac vibration interference using sample entropy with fixed tolerance values.
title_full	Evidence towards improved estimation of respiratory muscle effort from diaphragm mechanomyographic signals with cardiac vibration interference using sample entropy with fixed tolerance values.
title_fullStr	Evidence towards improved estimation of respiratory muscle effort from diaphragm mechanomyographic signals with cardiac vibration interference using sample entropy with fixed tolerance values.
title_full_unstemmed	Evidence towards improved estimation of respiratory muscle effort from diaphragm mechanomyographic signals with cardiac vibration interference using sample entropy with fixed tolerance values.
title_sort	evidence towards improved estimation of respiratory muscle effort from diaphragm mechanomyographic signals with cardiac vibration interference using sample entropy with fixed tolerance values.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/25058caaaebf4faaa5380cad8c5296f2
work_keys_str_mv	AT leonardosarlabous evidencetowardsimprovedestimationofrespiratorymuscleeffortfromdiaphragmmechanomyographicsignalswithcardiacvibrationinterferenceusingsampleentropywithfixedtolerancevalues AT abeltorres evidencetowardsimprovedestimationofrespiratorymuscleeffortfromdiaphragmmechanomyographicsignalswithcardiacvibrationinterferenceusingsampleentropywithfixedtolerancevalues AT joseafiz evidencetowardsimprovedestimationofrespiratorymuscleeffortfromdiaphragmmechanomyographicsignalswithcardiacvibrationinterferenceusingsampleentropywithfixedtolerancevalues AT raimonjane evidencetowardsimprovedestimationofrespiratorymuscleeffortfromdiaphragmmechanomyographicsignalswithcardiacvibrationinterferenceusingsampleentropywithfixedtolerancevalues
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Evidence towards improved estimation of respiratory muscle effort from diaphragm mechanomyographic signals with cardiac vibration interference using sample entropy with fixed tolerance values.

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