A Motion Capture Dataset on Human Sitting to Walking Transitions

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.

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Publication Details

Journal
Scientific Data
Published
2024-08-13
DOI
https://doi.org/10.1038/s41597-024-03740-z
Citations
14
Primary Topic
Balance, Gait, and Falls Prevention
Type
article
Field-Weighted Citation Impact
16.03

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article

A Motion Capture Dataset on Human Sitting to Walking Transitions

Zakia Hussain, Chamalka Kenneth Perera, Siti Anom Ahmad, Alpha Agape Gopalai et al.
14 citations
Scientific Data
Balance, Gait, and Falls Prevention
16.03
article

A Motion Capture Dataset on Human Sitting to Walking Transitions

Zakia Hussain, Chamalka Kenneth Perera, Siti Anom Ahmad, Alpha Agape Gopalai, Min Khant, Darwin Gouwanda
article en
14 citations

Abstract

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.

Scientific DataVol. 11(1)
Monash University Malaysia (MY), Universiti Putra Malaysia (MY)
Ministry of Higher Education, Malaysia
Openalex Percentile: Top 1%
Balance, Gait, and Falls Prevention
16.03
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A Motion Capture Dataset on Human Sitting to Walking Transitions — Zakia Hussain, Chamalka Kenneth Perera, et al. · Scientific Data (2024) | TGRS Research Map | TGRS