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dc.contributor.authorEstrada, Luis
dc.contributor.authorTorres Cebrián, Abel
dc.contributor.authorSarlabous Uranga, Leonardo
dc.contributor.authorJané Campos, Raimon
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.identifier.citationEstrada, L., Torres, A., Sarlabous, L., Jane, R. EMG-Derived Respiration Signal using the Fixed Sample Entropy during an Inspiratory Load Protocol. A: IEEE Engineering in Medicine and Biology Society. "2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2015)". Milan: Institute of Electrical and Electronics Engineers (IEEE), 2015, p. 1703-1706.
dc.description.abstractExtracting clinical information from one single measurement represents a step forward in the assessment of the respiratory muscle function. This attracting idea entails the reduction of the instrumentation and fosters to develop new medical integrated technologies. We present the use of the fixed sample entropy (fSampEn) as a more direct method to non-invasively derive the breathing activity from the diaphragm electromyographic (EMGdi) signal, and thus to extract the respiratory rate, an important vital sign which is cumbersome and time-consuming to be measured by clinicians. fSampEn is a method to evaluate the EMGdi activity that is less sensitive to the cardiac activity (ECG) and its application has proven to be useful to evaluate the load of the respiratory muscles. The behavior of the proposed method was tested in signals from two subjects that performed an inspiratory load protocol, which consists of increments in the inspiratory mouth pressure (Pmouth). Two respiratory signals were derived and compared to the Pmouth signal: the ECG-derived respiration (EDR) signal from the lead-I configuration, and the EMG-derived respiration (EMGDR) signal by applying the fSampEn method over the EMGdi signal. The similitude and the lag between signals were calculated through the cross-correlation between each derived respiratory signal and the Pmouth. The EMGDR signal showed higher correlation and lower lag values (= 0.91 and = 0.70 s, respectively) than the EDR signal (= 0.83 and = 0.99 s, respectively). Additionally, the respiratory rate was estimated with the Pmouth, EDR and EMGDR signals showing very similar values. The results from this preliminary work suggest that the fSampEn method can be used to derive the respiration waveform from the respiratory muscle electrical activity.
dc.format.extent4 p.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Enginyeria biomèdica
dc.subject.lcshRespiratory insufficiency
dc.subject.lcshLungs -- Diseases, Obstructive
dc.subject.lcshBiomedical engineering
dc.subject.otherBand-pass filters
dc.subject.otherEMG-derived respiration signal
dc.subject.otherBreathing activity
dc.subject.otherDiaphragm electromyographic signal
dc.subject.otherFixed sample entropy
dc.subject.otherInspiratory load protocol
dc.subject.otherInspiratory mouth pressure
dc.subject.otherLead-I configuration
dc.subject.otherRespiration waveform
dc.subject.otherRespiratory muscle electrical activity
dc.subject.otherRespiratory rate extraction
dc.titleEMG-Derived Respiration Signal using the Fixed Sample Entropy during an Inspiratory Load Protocol
dc.typeConference lecture
dc.subject.lemacInsuficiència respiratòria
dc.subject.lemacPulmons -- Malalties obstructives
dc.subject.lemacEnginyeria biomèdica
dc.contributor.groupUniversitat Politècnica de Catalunya. BIOSPIN - Biomedical Signal Processing and Interpretation
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
dc.description.versionPostprint (author's final draft)
upcommons.citation.authorEstrada, L.; Torres, A.; Sarlabous, L.; Jane, R.
upcommons.citation.contributorIEEE Engineering in Medicine and Biology Society
upcommons.citation.publicationName2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2015)

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