1. ABOUT THE DATASET
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Title:	

Creator(s): David Lunn[1,2], Enrico de Pieri[3], Graham J Chapman[4], Stephen J Ferguson[5], Anthony C. Redmond[2]

Organisation(s): 1. Leeds Beckett University, 2. University of Leeds, 3. Zimmer Biomet, 4. University of Central Lancashire, 5. ETH Zurich

Rights-holder(s):Unless otherwise stated, Copyright 2025 Leeds Beckett University, University of Leeds, Zimmer Biomet, University of Central Lancashire, ETH Zurich

Publication Year: 2025

Description: This dataset comprises comprehensive motion capture and ground reaction force data from 137 post-operative total hip replacement (THR) patients. Data were collected between 2013 and 2015 using a 10-camera Vicon system and dual force plates during a range of activities of daily living (ADLs), including level walking, stair negotiation, sit-to-stand, lunge, and squat tasks. Marker trajectories and ground reaction forces were processed using standard biomechanical techniques and segmented into key movement events. The dataset has previously been used to identify biomechanical differences in THR patients by age, gender, BMI, and function, and to explore joint contact forces and their impact on bone loading. It is now released for wider use in musculoskeletal modelling, with potential application in AI and machine learning model development. This study was supported by the European Union’s Seventh Framework Programme (FP7/2007-2013) under grant agreement no. GA-310477 LifeLongJoints.


2. TERMS OF USE
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Copyright 2025 Leeds Beckett University, University of Leeds, Zimmer Biomet, University of Central Lancashire, ETH Zurich. Unless otherwise stated, this dataset is licensed under a Creative Commons Attribution 4.0 International Licence: https://creativecommons.org/licenses/by/4.0/.]


3. PROJECT AND FUNDING INFORMATION
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Title: LifeLongJoints


Funding organisation: European Union’s Seventh Framework Programme (FP7/2007-2013) 

Grant no.: GA-310477


4. CONTENTS
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See file_manifest.txt


5. Usage notes
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The recorded data are stored in c3d file format (https://www.c3d.org) and can easily be read using c3d toolboxes such as BTK (http://biomechanical-toolkit.github.io/). The software Mokka is a convenient tool for 3D visualisation (http://biomechanical-toolkit.github.io/mokka/index.html). Anthropometric and demographic parameters of each participant are in the excel file shared named Patient Information.xls.