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dc.contributor.authorBlanco Almazán, María Dolores
dc.contributor.authorGroenendaal, Willemijn
dc.contributor.authorCatthoor, Francky
dc.contributor.authorJané Campos, Raimon
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Enginyeria Biomèdica
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.date.accessioned2020-02-26T09:19:36Z
dc.date.available2020-02-26T09:19:36Z
dc.date.issued2019-12-27
dc.identifier.citationBlanco-Almazán, D. [et al.]. Chest movement and respiratory volume both contribute to thoracic bioimpedance during loaded breathing. "Scientific reports", 27 Desembre 2019, núm. 9, p. 20232:1-20232:11.
dc.identifier.issn2045-2322
dc.identifier.urihttp://hdl.handle.net/2117/178671
dc.description.abstractBioimpedance has been widely studied as alternative to respiratory monitoring methods because of its linear relationship with respiratory volume during normal breathing. However, other body tissues and fluids contribute to the bioimpedance measurement. The objective of this study is to investigate the relevance of chest movement in thoracic bioimpedance contributions to evaluate the applicability of bioimpedance for respiratory monitoring. We measured airflow, bioimpedance at four electrode configurations and thoracic accelerometer data in 10 healthy subjects during inspiratory loading. This protocol permitted us to study the contributions during different levels of inspiratory muscle activity. We used chest movement and volume signals to characterize the bioimpedance signal using linear mixed-effect models and neural networks for each subject and level of muscle activity. The performance was evaluated using the Mean Average Percentage Errors for each respiratory cycle. The lowest errors corresponded to the combination of chest movement and volume for both linear models and neural networks. Particularly, neural networks presented lower errors (median below 4.29%). At high levels of muscle activity, the differences in model performance indicated an increased contribution of chest movement to the bioimpedance signal. Accordingly, chest movement contributed substantially to bioimpedance measurement and more notably at high muscle activity levels.
dc.language.isoeng
dc.publisherNature
dc.subjectÀrees temàtiques de la UPC::Informàtica::Automàtica i control
dc.subject.lcshBioengineering
dc.subject.lcshImpedance (Electricity)
dc.subject.lcshRespiration - Measurement
dc.titleChest movement and respiratory volume both contribute to thoracic bioimpedance during loaded breathing
dc.typeArticle
dc.subject.lemacImpedància (Electricitat)
dc.subject.lemacRespiració -- Mesurament
dc.subject.lemacBioenginyeria
dc.contributor.groupUniversitat Politècnica de Catalunya. BIOSPIN - Biomedical Signal Processing and Interpretation
dc.identifier.doi10.1038/s41598-019-56588-4
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://www.nature.com/articles/s41598-019-56588-4
dc.rights.accessOpen Access
local.identifier.drac26570551
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/1PE/DPI15-68820-R
local.citation.authorBlanco-Almazán, D.; Groenendaal, W.; Catthoor, F.; Jane, R.
local.citation.publicationNameScientific reports
local.citation.number9
local.citation.startingPage20232:1
local.citation.endingPage20232:11


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