A Motion Capture Dataset on Human Sitting to Walking Transitions.
Journal
Scientific data
ISSN: 2052-4463
Titre abrégé: Sci Data
Pays: England
ID NLM: 101640192
Informations de publication
Date de publication:
13 Aug 2024
13 Aug 2024
Historique:
received:
18
04
2024
accepted:
05
08
2024
medline:
14
8
2024
pubmed:
14
8
2024
entrez:
13
8
2024
Statut:
epublish
Résumé
Sit-to-walk (STW) is a crucial daily task that impacts mobility, independence, and thus quality of life. Existing repositories have limited STW data with small sample sizes (n = 10). Hence, this study presents a STW dataset obtained via the time-up-and-go test, for 65 healthy adults across three age groups - young (19-35 years), middle (36-55 years) and older (above 56 years). The dataset contains lower body motion capture, ground reaction force, surface electromyography, inertial measurement unit data, and responses for the knee injury and osteoarthritis outcome score survey. For validation, the within subjects intraclass correlation coefficients for the maximum and minimum lower body joint angles were calculated with values greater than 0.74, indicating good test-retest reliability. The joint angle trajectories and maximum voluntary contractions are comparable with existing literature, matching in overall trends and range. Accordingly, this dataset allows STW biomechanics, executions, and characteristics to be studied across age groups. Biomechanical trajectories of healthy adults serve as a benchmark in assessing neuromusculoskeletal impairments and when designing assistive technology for treatment or rehabilitation.
Identifiants
pubmed: 39138206
doi: 10.1038/s41597-024-03740-z
pii: 10.1038/s41597-024-03740-z
doi:
Types de publication
Dataset
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
878Subventions
Organisme : Ministry of Higher Education, Malaysia (MOHE)
ID : FRGS/1/2022/TK07/MUSM/02/2
Organisme : Ministry of Higher Education, Malaysia (MOHE)
ID : FRGS/1/2020/TK0/MUSM/02/2
Informations de copyright
© 2024. The Author(s).
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