| Autor: |
Reed Ferber, Allan Brett, Reginaldo K. Fukuchi, Blayne Hettinga, Sean T. Osis |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Scientific Data, Vol 11, Iss 1, Pp 1-6 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2052-4463 |
| DOI: |
10.1038/s41597-024-04011-7 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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Full text from SpringerLink