Improvement in Neural Respiratory Drive Estimation From Diaphragm Electromyographic Signals Using Fixed Sample Entropy

Diaphragm electromyography is a valuable technique for the recording of electrical activity of the diaphragm. The analysis of diaphragm electromyographic (EMGdi) signal amplitude is an alternative approach for the quantification of the neural respiratory drive (NRD). The EMGdi signal is, however, co...

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Autores: Estrada, L, Torres, A, Sarlabous, L, Jané, R
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2016
País:España
Institución:Institut d'Investigació i Innovació Parc Taulí (I3PT)
Repositorio:r-I3PT. Repositorio Institucional Producción Científica del Institut d'Investigació i Innovació Parc Taulí
OAI Identifier:oai:i3pt.fundanetsuite.com:p5225
Acceso en línea:https://i3pt.portalinvestigacion.com/publicaciones/5225
Access Level:acceso abierto
Palabra clave:Diaphragm muscle
electromyography
fixed sample entropy (fSampEn)
neural respiratory drive
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spelling Improvement in Neural Respiratory Drive Estimation From Diaphragm Electromyographic Signals Using Fixed Sample EntropyEstrada, LTorres, ASarlabous, LJané, RDiaphragm muscleelectromyographyfixed sample entropy (fSampEn)neural respiratory driveDiaphragm electromyography is a valuable technique for the recording of electrical activity of the diaphragm. The analysis of diaphragm electromyographic (EMGdi) signal amplitude is an alternative approach for the quantification of the neural respiratory drive (NRD). The EMGdi signal is, however, corrupted by electrocardiographic (ECG) activity, and this presence of cardiac activity can make the EMGdi interpretation more difficult. Traditionally, the EMGdi amplitude has been estimated using the average rectified value (ARV) and the root mean square (RMS). In this study, surface EMGdi signals were analyzed using the fixed sample entropy (fSampEn) algorithm, and compared to the traditional ARV and RMS methods. The fSampEn is calculated using a tolerance value fixed and independent of the standard deviation of the analysis window. Thus, this method quantifies the amplitude of the complex components of stochastic signals (such as EMGdi), and being less affected by changes in amplitude due to less complex components (such as ECG). The proposed method was tested in synthetic and recorded EMGdi signals. fSampEn was less sensitive to the effect of cardiac activity on EMGdi signals with different levels of NRD than ARV and RMS amplitude parameters. The mean and standard deviation of the Pearson's correlation values between inspiratorymouth pressure (an indirect measure of the respiratory muscle activity) and fSampEn, ARV, and RMS parameters, estimated in the recorded EMGdi signal at tidal volume (without inspiratory load), were 0.38 +/- 0.12, 0.27 +/- 0.11, and 0.11 +/- 0.13, respectively. Whereas at 33 cmH(2)O (maximum inspiratory load) were 0.83 +/- 0.02, 0.76 +/- 0.07, and 0.61 +/- 0.19, respectively. Our findings suggest that the proposed method may improve the evaluation of NRD.IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2016info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://i3pt.portalinvestigacion.com/publicaciones/5225IEEE Journal of Biomedical and Health InformaticsISSN: 21682194ISSNe: 21682208reponame:r-I3PT. Repositorio Institucional Producción Científica del Institut d'Investigació i Innovació Parc Taulíinstname:Institut d'Investigació i Innovació Parc Taulí (I3PT)Inglésinfo:eu-repo/semantics/openAccessoai:i3pt.fundanetsuite.com:p52252026-06-21T15:30:37Z
dc.title.none.fl_str_mv Improvement in Neural Respiratory Drive Estimation From Diaphragm Electromyographic Signals Using Fixed Sample Entropy
title Improvement in Neural Respiratory Drive Estimation From Diaphragm Electromyographic Signals Using Fixed Sample Entropy
spellingShingle Improvement in Neural Respiratory Drive Estimation From Diaphragm Electromyographic Signals Using Fixed Sample Entropy
Estrada, L
Diaphragm muscle
electromyography
fixed sample entropy (fSampEn)
neural respiratory drive
title_short Improvement in Neural Respiratory Drive Estimation From Diaphragm Electromyographic Signals Using Fixed Sample Entropy
title_full Improvement in Neural Respiratory Drive Estimation From Diaphragm Electromyographic Signals Using Fixed Sample Entropy
title_fullStr Improvement in Neural Respiratory Drive Estimation From Diaphragm Electromyographic Signals Using Fixed Sample Entropy
title_full_unstemmed Improvement in Neural Respiratory Drive Estimation From Diaphragm Electromyographic Signals Using Fixed Sample Entropy
title_sort Improvement in Neural Respiratory Drive Estimation From Diaphragm Electromyographic Signals Using Fixed Sample Entropy
dc.creator.none.fl_str_mv Estrada, L
Torres, A
Sarlabous, L
Jané, R
author Estrada, L
author_facet Estrada, L
Torres, A
Sarlabous, L
Jané, R
author_role author
author2 Torres, A
Sarlabous, L
Jané, R
author2_role author
author
author
dc.subject.none.fl_str_mv Diaphragm muscle
electromyography
fixed sample entropy (fSampEn)
neural respiratory drive
topic Diaphragm muscle
electromyography
fixed sample entropy (fSampEn)
neural respiratory drive
description Diaphragm electromyography is a valuable technique for the recording of electrical activity of the diaphragm. The analysis of diaphragm electromyographic (EMGdi) signal amplitude is an alternative approach for the quantification of the neural respiratory drive (NRD). The EMGdi signal is, however, corrupted by electrocardiographic (ECG) activity, and this presence of cardiac activity can make the EMGdi interpretation more difficult. Traditionally, the EMGdi amplitude has been estimated using the average rectified value (ARV) and the root mean square (RMS). In this study, surface EMGdi signals were analyzed using the fixed sample entropy (fSampEn) algorithm, and compared to the traditional ARV and RMS methods. The fSampEn is calculated using a tolerance value fixed and independent of the standard deviation of the analysis window. Thus, this method quantifies the amplitude of the complex components of stochastic signals (such as EMGdi), and being less affected by changes in amplitude due to less complex components (such as ECG). The proposed method was tested in synthetic and recorded EMGdi signals. fSampEn was less sensitive to the effect of cardiac activity on EMGdi signals with different levels of NRD than ARV and RMS amplitude parameters. The mean and standard deviation of the Pearson's correlation values between inspiratorymouth pressure (an indirect measure of the respiratory muscle activity) and fSampEn, ARV, and RMS parameters, estimated in the recorded EMGdi signal at tidal volume (without inspiratory load), were 0.38 +/- 0.12, 0.27 +/- 0.11, and 0.11 +/- 0.13, respectively. Whereas at 33 cmH(2)O (maximum inspiratory load) were 0.83 +/- 0.02, 0.76 +/- 0.07, and 0.61 +/- 0.19, respectively. Our findings suggest that the proposed method may improve the evaluation of NRD.
publishDate 2016
dc.date.none.fl_str_mv 2016
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://i3pt.portalinvestigacion.com/publicaciones/5225
url https://i3pt.portalinvestigacion.com/publicaciones/5225
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
publisher.none.fl_str_mv IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.source.none.fl_str_mv IEEE Journal of Biomedical and Health Informatics
ISSN: 21682194
ISSNe: 21682208
reponame:r-I3PT. Repositorio Institucional Producción Científica del Institut d'Investigació i Innovació Parc Taulí
instname:Institut d'Investigació i Innovació Parc Taulí (I3PT)
instname_str Institut d'Investigació i Innovació Parc Taulí (I3PT)
reponame_str r-I3PT. Repositorio Institucional Producción Científica del Institut d'Investigació i Innovació Parc Taulí
collection r-I3PT. Repositorio Institucional Producción Científica del Institut d'Investigació i Innovació Parc Taulí
repository.name.fl_str_mv
repository.mail.fl_str_mv
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