E De Pieri1, D E Lunn2, G J Chapman3, K P Rasmussen4, S J Ferguson5, A C Redmond6. 1. Institute for Biomechanics, ETH Zurich, Zurich, Switzerland. Electronic address: enrico.depieri@hest.ethz.ch. 2. Institute for Rheumatic and Musculoskeletal Medicine, University of Leeds, Leeds, UK; NIHR Leeds Biomedical Research Centre, Leeds, UK. Electronic address: D.Lunn@leeds.ac.uk. 3. Institute for Rheumatic and Musculoskeletal Medicine, University of Leeds, Leeds, UK; NIHR Leeds Biomedical Research Centre, Leeds, UK. Electronic address: G.J.Chapman@leeds.ac.uk. 4. AnyBody Technology A/S, Aalborg, Denmark. Electronic address: kasperpihl.r@gmail.com. 5. Institute for Biomechanics, ETH Zurich, Zurich, Switzerland. Electronic address: sferguson@ethz.ch. 6. Institute for Rheumatic and Musculoskeletal Medicine, University of Leeds, Leeds, UK; NIHR Leeds Biomedical Research Centre, Leeds, UK. Electronic address: A.Redmond@leeds.ac.uk.
Abstract
OBJECTIVE: To examine hip contact force (HCF), calculated through multibody modelling, in a large total hip replacement (THR) cohort stratified by patient characteristics such as body mass index (BMI), age and function. METHOD: 132 THR patients undertook one motion capture session of gait analysis at a self-selected walking speed. HCFs were then calculated using the AnyBody Modelling System. Patients were stratified into three BMI groups, five age groups, and finally three functional groups determined by their self-selected gait speed. By means of statistical parametric mapping (SPM), statistical analyses of the 1-dimensional time series were performed to separately evaluate the influence of age, BMI and functionality on HCF. RESULTS: The mean predicted HCFs were comparable to HCFs measured with instrumented prostheses reported in the literature. The SPM analysis revealed a statistically significant positive linear correlation between BMI and HCF, indicating that obese patients are more likely to experience higher HCF during most of the stance phase, while a statistically significant negative correlation with age was found only during the late swing-phase. Patients with higher functional ability exhibited significantly increased peak HCF, while patients with lower functional ability demonstrated lower HCFs overall and a pathological flattening of the typical double hump force profile. CONCLUSION: HCFs experienced at the bearing surface are highly dependent on patient characteristics. BMI and functional ability were determined to have the biggest influence on contact forces. Current preclinical testing standards do not reflect this.
OBJECTIVE: To examine hip contact force (HCF), calculated through multibody modelling, in a large total hip replacement (THR) cohort stratified by patient characteristics such as body mass index (BMI), age and function. METHOD: 132 THR patients undertook one motion capture session of gait analysis at a self-selected walking speed. HCFs were then calculated using the AnyBody Modelling System. Patients were stratified into three BMI groups, five age groups, and finally three functional groups determined by their self-selected gait speed. By means of statistical parametric mapping (SPM), statistical analyses of the 1-dimensional time series were performed to separately evaluate the influence of age, BMI and functionality on HCF. RESULTS: The mean predicted HCFs were comparable to HCFs measured with instrumented prostheses reported in the literature. The SPM analysis revealed a statistically significant positive linear correlation between BMI and HCF, indicating that obesepatients are more likely to experience higher HCF during most of the stance phase, while a statistically significant negative correlation with age was found only during the late swing-phase. Patients with higher functional ability exhibited significantly increased peak HCF, while patients with lower functional ability demonstrated lower HCFs overall and a pathological flattening of the typical double hump force profile. CONCLUSION: HCFs experienced at the bearing surface are highly dependent on patient characteristics. BMI and functional ability were determined to have the biggest influence on contact forces. Current preclinical testing standards do not reflect this.
Authors: Simone Tassani; Laura Tio; Francisco Castro-Domínguez; Jordi Monfort; Juan Carlos Monllau; Miguel Angel González Ballester; Jérôme Noailly Journal: Front Bioeng Biotechnol Date: 2022-03-11