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Orthopaedic Proceedings
Vol. 105-B, Issue SUPP_16 | Pages 34 - 34
17 Nov 2023
Elliott M Rodrigues R Hamilton R Postans N Metcalfe A Jones R McGregor A Arvanitis T Holt C
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Abstract

Objectives

Biomechanics is an essential form of measurement in the understanding of the development and progression of osteoarthritis (OA). However, the number of participants in biomechanical studies are often small and there is limited ways to share or combine data from across institutions or studies. This is essential for applying modern machine learning methods, where large, complex datasets can be used to identify patterns in the data. Using these data-driven approaches, it could be possible to better predict the optimal interventions for patients at an early stage, potentially avoiding pain and inappropriate surgery or rehabilitation. In this project we developed a prototype database platform for combining and sharing biomechanics datasets. The database includes methods for importing and standardising data and associated variables, to create a seamless, searchable combined dataset of both healthy and knee OA biomechanics.

Methods

Data was curated through calls to members of the OATech Network+ (https://www.oatechnetwork.org/). The requirements were 3D motion capture data from previous studies that related to analysing the biomechanics of knee OA, including participants with OA at any stage of progression plus healthy controls. As a minimum we required kinematic data of the lower limbs, plus associated kinetic data (i.e. ground reaction forces). Any additional, complementary data such as EMG could also be provided. Relevant ethical approvals had to be in place that allowed re-use of the data for other research purposes. The datasets were uploaded to a University hosted cloud platform. The database platform was developed using Javascript and hosted on a Windows server, located and managed within the department.


Orthopaedic Proceedings
Vol. 94-B, Issue SUPP_XXIX | Pages 72 - 72
1 Jul 2012
Metcalfe A Stewart C Postans N Barlow D Whatling G Holt C Roberts A
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Introduction

Patients with knee osteoarthritis frequently complain that they develop pain in other joints due to over-loading during gait. However, there have been no previous studies examining the effect of knee arthritis on the other weight bearing joints. The aim of this study was to examine the loading of the hips and contra-lateral knee during gait in a cohort of patients pre- and post knee replacement.

Methods

Twenty patients with single joint osteoarthritis awaiting knee replacement and 20 healthy volunteers were recruited. Gait analysis during level gait and at self selected speed was performed using a 12 camera Vicon motion analysis system. The ground reaction force was collected using EMG electrodes attached to the medial and lateral hamstrings and quadriceps bilaterally. Patients were invited to return 12 months post-operatively. Data was analysed using the Vicon plug-in-gait model and statistical testing was performed with SPSS v16.0 using ANCOVA to account for gait speed.


Orthopaedic Proceedings
Vol. 94-B, Issue SUPP_XVIII | Pages 41 - 41
1 May 2012
Metcalfe A Stewart C Postans N Dodds A Smith H Holt C Roberts A
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Introduction

Patients with knee osteoarthritis (OA) often tell us that they put extra load on the joints of the opposite leg as they walk. Multiple joint OA is common and has previously been related to gait changes due to hip OA (Shakoor et al 2002). The aim of this study was to determine whether patients with medial compartment knee OA have abnormal biomechanics of the unaffected knee and both hips during normal level gait.

Methods

Twenty patients (11 male, 9 female), with severe medial compartment knee OA and no other joint pain were recruited. The control group comprised 20 adults without musculoskeletal pain. Patients were reviewed, x-rays were examined and WOMAC and Oxford knee scores were completed. A 12 camera Vicon (Vicon, Oxford) system was used to collect kinematic data (100Hz) on level walking and the ground reaction force was recorded using three AMTI force plates (1000Hz). Surface electrodes were placed over medial and lateral quadriceps and hamstrings bilaterally to record EMG data (1000Hz). Kinematics and kinetics were calculated using the Vicon ‘plug-in-gait’ model. A co-contraction index was calculated for the EMG signals on each side of the knee, representing the magnitude of the combined readings relative to their maximum contraction during the gait cycle. Statistical comparisons were performed using t-tests with Bonferroni's correction for two variables and ANOVA for more than two variables (SPSS v16).