In-silico simulation of obstetric forceps placement using the Hilber-Hughes-Taylor implicit integration method with contact constraints: Simulation of obstetric forceps placement

Lapeer, Rudy; Valladolid Garcia, Omar

In-silico simulation of obstetric forceps placement using the Hilber-Hughes-Taylor implicit integration method with contact constraints: Simulation of obstetric forceps placement

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Lapeer, Rudy and Valladolid Garcia, Omar (2025) In-silico simulation of obstetric forceps placement using the Hilber-Hughes-Taylor implicit integration method with contact constraints: Simulation of obstetric forceps placement. In: Lecture Notes in Bioengineering (LNBE). Lecture Notes in Bioengineering . Springer, AUS. (In Press)

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Abstract

Obstetric forceps are used as an instrumental delivery method when physiological childbirth fails to progress. The technique comprises the insertion of two stainless steel blades in the vagina that are subsequently coupled to make firm contact with the fetal head. In this paper, we assessed the effect of symmetric against asymmetric placement of the blades around the fetal head. Assessment was facilitated in-silico by creating mesh models of the fetal head and forceps and conducting implicit dynamic finite element analyses using the Hilber-Hughes-Taylor integration method, with imposed contact constraints between the virtual head and forceps. We observed that asymmetric forceps blade placement causes increased local deformations and strains that may potentially be harmful to the fetus. We conclude that forceps traction should not be applied when blades are asymmetrically placed around the fetal head.

Item Type:	Book Section
Additional Information:	THE PURE SYSTEM IS REFUSING MY PDF PROOF AND STATES THAT I SHOULD UPLOAD IT IN WORD FORMAT!? THERE IS NO WORD VERSION AS IT'S GENERATED IN LATEX ...
Uncontrolled Keywords:	finite element analysis (fea),finite element method (fem),assisted vaginal delivery (avd)
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Health Computing Faculty of Science > Research Groups > Data Science and AI
Related URLs:	https://cbm.mech.uwa.edu.au/CBM2025/
Depositing User:	LivePure Connector
Date Deposited:	12 Mar 2026 15:30
Last Modified:	12 Mar 2026 15:30
URI:	https://ueaeprints.uea.ac.uk/id/eprint/102330
DOI:

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