ArticleScientific data2024
A Biomechanical Dataset of 1,798 Healthy and Injured Subjects During Treadmill Walking and Running.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Establishment of Reference Values for Selected Spatiotemporal and Kinematic Running Parameters in Healthy Adult Recreational Runners from Barranquilla, Colombia.Journal of functional morphology and kinesiology · 2026Article
- A public dataset of treadmill walking kinematics and kinetics at steady speeds in healthy individuals.Data in brief · 2026Article
- The Use of Machine Learning to Estimate Ground Reaction Forces During Running: A Scoping Review of the Current Practices.Sensors (Basel, Switzerland) · 2026Article
- Whole-body optical marker and ground reaction force data of healthy humans performing non-cyclic activities.Scientific data · 2025Article
- Where is the Power in a Power Analysis?International journal of exercise science · 2025Article
- A Biomechanical Dataset of 1,798 Healthy and Injured Subjects During Treadmill Walking and Running.Scientific data · 2024Article
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Authors and funding
5 authors.
Funding
Abstract
Quantitative biomechanical gait analysis is an important clinical and research tool for injury and disease diagnosis and treatment. However, one major criticism is that gait analysis laboratories largely operate in isolation and there is a lack of benchmark datasets, which can be used to advance research and statistical methodologies. To address this, we present an open biomechanics dataset of n = 1798 healthy and injured, young and older adults during treadmill walking and/or running at a range of gait speeds. The full dataset is available on Figshare+ and data files are contained within a series of zipped folders with folder names representing the subject ID. Each subject ID folder contains walking and/or running data containing raw marker trajectory data along with metadata for each participant. Five tutorials are also provided, demonstrating aspects such as loading data files, sample analyses of discrete variables, and calculating joint angles from code along with covering more complex topics such as principal component analysis for dimensionality reduction, statistical parametric mapping, and conducting unsupervised clustering.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.