Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Data-driven modelling of pelvic floor muscles dynamics
Department of Engineering Sciences, Uppsala University, Sweden.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0002-4310-7938
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
Department of Psychology and Neuroscience, Clinical Psychological Science, Behavioural Medicine, Maastricht Universitair Medisch Centrum, Maastricht, The Netherlands.
Show others and affiliations
2018 (English)In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 51, no 27, p. 321-326Article in journal (Refereed) Published
Abstract [en]

This paper proposes individualized, dynamical and data-driven models that describe pelvic floor muscle responses in women that use vaginal dilation. Specifically, the models describe how the volume of an inflatable balloon inserted at the vaginal introitus dynamically affects the aggregated pressure exerted by the pelvic floor muscles of the person. The paper inspects the approximation capabilities of different model structures, such as Hammerstein-Wiener and NARX, for this specific application, and finds the specific model structures and orders that best describe the recorded measurement data. Hence, although the current dataset is drawn from a sample of healthy volunteers, this paper is an initial step towards better understanding women’s responses to vaginal dilation and facilitating individualised medical vaginal dilation treatment.

Place, publisher, year, edition, pages
2018. Vol. 51, no 27, p. 321-326
Keywords [en]
female sexual dysfunction, black box, nonlinear models, system identification
National Category
Control Engineering
Research subject
Control Engineering; Control Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-72983DOI: 10.1016/j.ifacol.2018.11.621OAI: oai:DiVA.org:ltu-72983DiVA, id: diva2:1290895
Note

Konferensartikel i tidskrift

Available from: 2019-02-21 Created: 2019-02-21 Last updated: 2019-02-21Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Authority records BETA

Varagnolo, Damiano

Search in DiVA

By author/editor
Varagnolo, Damiano
By organisation
Signals and Systems
In the same journal
IFAC-PapersOnLine
Control Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 1 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf