Gait analysis dataset of healthy volunteers and patients before and 6 months after total hip arthroplasty

Abstract

AbstractClinical gait analysis is a promising approach for quantifying gait deviations and assessing the impairments altering gait in patients with osteoarthritis. There is a lack of consensus on the identification of kinematic outcomes that could be used for the diagnosis and follow up in patients. The proposed dataset has been established on 80 asymptomatic participants and 106 patients with unilateral hip osteoarthritis before and 6 months after arthroplasty. All volunteers walked along a 6 meters straight line at their self-selected speed. Three dimensional trajectories of 35 reflective markers were simultaneously recorded and Plugin Gait Bones, angles, Center of Mass trajectories and ground reaction forces were computed. Gait video recordings, when available, anthropometric and demographic descriptions are also available. A minimum of 10 trials have been made available in the weka file format and C3D file to enhance the use of machine learning algorithms. We aim to share this dataset to facilitate the identification of new movement-related kinematic outcomes for improving the diagnosis and follow up in patients with hip OA.