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100 Normative Gait Profiles with 5-year fall tracking: Benchmark Dataset for Southeast Asian Movement Science
Oliver Roberts1, Pablo Cruz Gonzalez1,2, Arun-Kumar Kaliya-Perumal1
1Rehabilitation Research Institute of Singapore, Nanyang Technological University, Singapore, Singapore.
Scientific Data
|March 18, 2026
Summary
This study introduces a large-scale dataset of fast-gait 10-meter walk tests from healthy older adults in Southeast Asia. It enhances mobility assessment with motion capture technology and includes a fall risk model.
Area of Science:
- Biomechanics
- Gerontology
- Data Science
Background:
- Gait assessment is crucial for evaluating mobility in older adults.
- The conventional 10-meter walk test provides limited biomechanical data.
- Motion capture technology can enhance gait analysis by providing granular data.
Purpose of the Study:
- To present the first large-scale dataset of fast-gait 10-meter walk tests from Southeast Asian older adults.
- To integrate motion capture technology for high-definition gait analysis.
- To report a five-year follow-up model of fall risk within the study cohort.
Main Methods:
- Collected data from 100 healthy older adults (50-80 years) in Southeast Asia.
- Utilized motion capture technology during the 10-meter walk test.
- Developed a five-year fall risk prediction model based on gait parameters.
Main Results:
- Established a unique, large-scale dataset of high-definition gait data from a diverse older adult population.
- Demonstrated the feasibility of integrating advanced motion capture into standard gait assessments.
- Provided a validated model for predicting fall risk over a five-year period.
Conclusions:
- The dataset serves as a valuable normative resource for clinical and research applications in mobility and aging.
- Enhanced gait analysis using motion capture offers deeper insights than conventional methods.
- The fall risk model has significant implications for preventative strategies in geriatric care.
