The University of Southampton
University of Southampton Institutional Repository

A review of probabilistic analysis in orthopaedic biomechanics

A review of probabilistic analysis in orthopaedic biomechanics
A review of probabilistic analysis in orthopaedic biomechanics
Probabilistic analysis methods are being increasingly applied in the orthopaedics and biomechanics literature to account for uncertainty and variability in subject geometries, properties of various structures, kinematics and joint loading, as well as uncertainty in implant
alignment.

As a complement to experiments, finite element modelling, and statistical analysis, probabilistic analysis provides a method of characterizing the potential impact of variability in parameters on performance. This paper presents an overview of probabilistic analysis and a review of biomechanics literature utilizing probabilistic methods in structural reliability, kinematics, joint mechanics, musculoskeletal modelling, and patient-specific representations.

The aim of this review paper is to demonstrate the wide range of applications of probabilistic methods and to aid researchers and clinicians in better understanding probabilistic analyses.
probabilistic methods, biomechanics, joint mechanics, kinematics, total joint replacement, statistics, finite element analysis
0954-4119
Laz, P. J.
d0cc1ee2-ef24-469c-8c4b-403b14b22134
Browne, M.
6578cc37-7bd6-43b9-ae5c-77ccb7726397
Laz, P. J.
d0cc1ee2-ef24-469c-8c4b-403b14b22134
Browne, M.
6578cc37-7bd6-43b9-ae5c-77ccb7726397

Laz, P. J. and Browne, M. (2010) A review of probabilistic analysis in orthopaedic biomechanics. Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine, 224 (H). (doi:10.1243/09544119JEIM739). (In Press)

Record type: Article

Abstract

Probabilistic analysis methods are being increasingly applied in the orthopaedics and biomechanics literature to account for uncertainty and variability in subject geometries, properties of various structures, kinematics and joint loading, as well as uncertainty in implant
alignment.

As a complement to experiments, finite element modelling, and statistical analysis, probabilistic analysis provides a method of characterizing the potential impact of variability in parameters on performance. This paper presents an overview of probabilistic analysis and a review of biomechanics literature utilizing probabilistic methods in structural reliability, kinematics, joint mechanics, musculoskeletal modelling, and patient-specific representations.

The aim of this review paper is to demonstrate the wide range of applications of probabilistic methods and to aid researchers and clinicians in better understanding probabilistic analyses.

Text
001-017_jeim739_PROOF.pdf - Version of Record
Download (526kB)

More information

Accepted/In Press date: 2010
Additional Information: (Uncorrected Proof)
Keywords: probabilistic methods, biomechanics, joint mechanics, kinematics, total joint replacement, statistics, finite element analysis

Identifiers

Local EPrints ID: 143375
URI: http://eprints.soton.ac.uk/id/eprint/143375
ISSN: 0954-4119
PURE UUID: 6727e10f-a50b-4303-801d-ecde8207b45c
ORCID for M. Browne: ORCID iD orcid.org/0000-0001-5184-050X

Catalogue record

Date deposited: 08 Apr 2010 15:17
Last modified: 14 Mar 2024 02:39

Export record

Altmetrics

Contributors

Author: P. J. Laz
Author: M. Browne ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×