Mostra el registre d'ítem simple
Onset and offset estimation of the neural inspiratory time in surface diaphragm electromyography: a pilot study in healthy subjects
dc.contributor.author | Estrada Petrocelli, Luis |
dc.contributor.author | Torres Cebrián, Abel |
dc.contributor.author | Sarlabous Uranga, Leonardo |
dc.contributor.author | Jané Campos, Raimon |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial |
dc.date.accessioned | 2018-03-16T13:32:19Z |
dc.date.issued | 2018-01-01 |
dc.identifier.citation | Estrada, L., Torres, A., Sarlabous, L., Jane, R. Onset and offset estimation of the neural inspiratory time in surface diaphragm electromyography: a pilot study in healthy subjects. "IEEE Journal of Biomedical and Health Informatics", 1 Gener 2018, vol. 22, núm. 1, p. 67. |
dc.identifier.issn | 2168-2194 |
dc.identifier.uri | http://hdl.handle.net/2117/115292 |
dc.description.abstract | © 2013 IEEE. This study evaluates the onset and offset of neural inspiratory time estimated from surface diaphragm electromyographic (EMGdi) recordings. EMGdi and airflow signals were recorded in ten healthy subjects according to two respiratory protocols based on respiratory rate (RR) increments, from 15 to 40 breaths per minute (bpm), and fractional inspiratory time (Ti/Ttot) decrements, from 0.54 to 0.18. The analysis of EMGdi signal amplitude is an alternative approach for the quantification of neural respiratory drive. The EMGdi amplitude was estimated using the fixed sample entropy computed over a 250 ms moving window of the EMGdi signal (EMGdifse). The neural onset was detected through a dynamic threshold over the EMGdifse using the kernel density estimation method, while neural offset was detected by finding when the EMGdifse had decreased to 70% of the peak value reached during inspiration. The Bland-Altman analysis between airflow and neural onsets showed a global bias of 46 ms in the RR protocol and 22 ms in the Ti/Ttot protocol. The Bland-Altman analysis between airflow and neural offsets reveals a global bias of 11 ms in the RR protocol and -2 ms in the Ti/T tot protocol. The relationship between pairs of RR values (Pearson's correlation coefficient of 0.99, Bland-=Altman limits of -2.39 to 2.41 bpm, and mean bias of 0.01 bpm) and between pairs of Ti/Ttot values (Pearson's correlation coefficient of 0.86, Bland-Altman limits of -0.11 to 0.10, and mean bias of -0.01) showed a good agreement. In conclusion, we propose a method for determining neural onset and neural offset based on noninvasive recordings of the electrical activity of the diaphragm that requires no filtering of cardiac muscle interference. |
dc.format.extent | 1 p. |
dc.language.iso | eng |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Spain |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.subject | Àrees temàtiques de la UPC::Enginyeria biomèdica |
dc.subject.lcsh | Biomedical engineering |
dc.subject.other | Fixed sample entropy (fSampEn) |
dc.subject.other | inspiratory time |
dc.subject.other | kernel density estimation (KDE) |
dc.subject.other | neural inspiratory time |
dc.subject.other | neural respiratory drive (NRD) |
dc.subject.other | surface diaphragm electromyographic (EMGdi) signal |
dc.title | Onset and offset estimation of the neural inspiratory time in surface diaphragm electromyography: a pilot study in healthy subjects |
dc.type | Article |
dc.subject.lemac | Enginyeria biomèdica |
dc.contributor.group | Universitat Politècnica de Catalunya. BIOSPIN - Biomedical Signal Processing and Interpretation |
dc.identifier.doi | 10.1109/JBHI.2017.2672800 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://ieeexplore.ieee.org/document/7862161/ |
dc.rights.access | Restricted access - publisher's policy |
local.identifier.drac | 21870351 |
dc.description.version | Postprint (published version) |
dc.date.lift | 10000-01-01 |
local.citation.author | Estrada, L.; Torres, A.; Sarlabous, L.; Jane, R. |
local.citation.publicationName | IEEE Journal of Biomedical and Health Informatics |
local.citation.volume | 22 |
local.citation.number | 1 |
local.citation.startingPage | 67 |
local.citation.endingPage | 67 |
Fitxers d'aquest items
Aquest ítem apareix a les col·leccions següents
-
Articles de revista [1.392]
-
Articles de revista [39]