Publikation: On seasonal functional modeling under strong dependence, with applications to mechanically ventilated breathing activity
Dateien
Datum
Autor:innen
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
DOI (zitierfähiger Link)
Internationale Patentnummer
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Sammlungen
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
Publikationstyp
Publikationsstatus
Erschienen in
Zusammenfassung
Breathing effort in mechanical ventilation is commonly estimated by airway pressure. More advanced methods involve transdiaphragmatic pressure measurements (Pdi) or surface electromyography (sEMG) of the respiratory muscles. To study whether inspiratory efforts may be predicted by the noninvasive sEMG method, a model is proposed for time series with a stochastically changing periodic component. The model can be interpreted as a functional time series or a process based on a state space representation, with a flexible temporal dependence structure in the parameter process and the residuals, including long memory, short memory or antipersistence. An application to Pdi and sEMG measurements shows the potential usefulness of the method in the context of monitoring patients undergoing mechanical ventilation.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
Schlagwörter
Konferenz
Rezension
Zitieren
ISO 690
BERAN, Jan, Jeremy NÄSCHER, Franziska FARQUHARSON, Max KUSTERMANN, Hans-Joachim KABITZ, Stephan WALTERSPACHER, 2023. On seasonal functional modeling under strong dependence, with applications to mechanically ventilated breathing activity. In: Journal of Statistical Planning and Inference. Elsevier Science. 2023, 222, pp. 38-65. ISSN 0378-3758. eISSN 1873-1171. Available under: doi: 10.1016/j.jspi.2022.05.007BibTex
@article{Beran2023seaso-58130, year={2023}, doi={10.1016/j.jspi.2022.05.007}, title={On seasonal functional modeling under strong dependence, with applications to mechanically ventilated breathing activity}, volume={222}, issn={0378-3758}, journal={Journal of Statistical Planning and Inference}, pages={38--65}, author={Beran, Jan and Näscher, Jeremy and Farquharson, Franziska and Kustermann, Max and Kabitz, Hans-Joachim and Walterspacher, Stephan} }
RDF
<rdf:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/58130"> <dc:creator>Kabitz, Hans-Joachim</dc:creator> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/58130"/> <dc:creator>Näscher, Jeremy</dc:creator> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dcterms:abstract xml:lang="eng">Breathing effort in mechanical ventilation is commonly estimated by airway pressure. More advanced methods involve transdiaphragmatic pressure measurements (Pdi) or surface electromyography (sEMG) of the respiratory muscles. To study whether inspiratory efforts may be predicted by the noninvasive sEMG method, a model is proposed for time series with a stochastically changing periodic component. The model can be interpreted as a functional time series or a process based on a state space representation, with a flexible temporal dependence structure in the parameter process and the residuals, including long memory, short memory or antipersistence. An application to Pdi and sEMG measurements shows the potential usefulness of the method in the context of monitoring patients undergoing mechanical ventilation.</dcterms:abstract> <dc:creator>Kustermann, Max</dc:creator> <dc:contributor>Kabitz, Hans-Joachim</dc:contributor> <dc:contributor>Kustermann, Max</dc:contributor> <dcterms:title>On seasonal functional modeling under strong dependence, with applications to mechanically ventilated breathing activity</dcterms:title> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-07-22T08:17:26Z</dcterms:available> <dc:contributor>Farquharson, Franziska</dc:contributor> <dc:creator>Beran, Jan</dc:creator> <dc:creator>Farquharson, Franziska</dc:creator> <dc:contributor>Näscher, Jeremy</dc:contributor> <dc:contributor>Walterspacher, Stephan</dc:contributor> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/39"/> <dc:creator>Walterspacher, Stephan</dc:creator> <dc:language>eng</dc:language> <dcterms:issued>2023</dcterms:issued> <dc:contributor>Beran, Jan</dc:contributor> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-07-22T08:17:26Z</dc:date> <foaf:homepage rdf:resource="http://localhost:8080/"/> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/39"/> </rdf:Description> </rdf:RDF>