Efficacy of quantifying marker-cluster rigidity in a multi-segment foot model: a Monte-Carlo based global sensitivity analysis and regression model

Po-Hsiang Chan, Julie Stebbins and Amy B. Zavatsky

Computer Methods in Biomechanics and Biomedical Engineering, 2022, vol. 25, issue 3, 308-319

Abstract: Marker-based clinical gait analysis and multi-segment foot models (MSFM) have been successfully used for the diagnosis and clinical management of various lower limb disorders. The accuracy and validity of the kinematics measured depend on the design of the model, as well as on the adherence to its inherent rigid body assumption. This study applies a Monte-Carlo based global sensitivity analysis to evaluate the efficacy of using ‘rigid body error (σRBE)’ in quantifying the rigidity of a MSFM marker-cluster. A regression model is proposed. It is concluded that σRBE is effective in quantifying rigidity.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/10255842.2021.1954170 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:gcmbxx:v:25:y:2022:i:3:p:308-319

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/gcmb20

DOI: 10.1080/10255842.2021.1954170

Access Statistics for this article

Computer Methods in Biomechanics and Biomedical Engineering is currently edited by Director of Biomaterials John Middleton

More articles in Computer Methods in Biomechanics and Biomedical Engineering from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().