One-Legged Stand Test: Synchronized Motion Capture, Force Plate, and Radar Dataset for Fall-Risk

Area of Science:

• Biomechanics
• Digital Health
• Radar Signal Processing

Background:

• The One-Legged Stand Test (OLST) is a clinically validated assessment for fall risk.
• Synchronized, multi-modal data acquisition is crucial for detailed biomechanical analysis.

Purpose of the Study:

• To present a novel, synchronized dataset for fall risk assessment research.
• To support the development of digital biomarkers using advanced sensing technologies.
• To facilitate research in biomechanics and radar signal processing.

Main Methods:

• Collected synchronized motion capture, force plate, and 24 GHz FMCW radar data from 32 healthy participants (younger and older adults).
• Participants performed the One-Legged Stand Test (OLST).
• Labeled key events (foot-lift, stability phases, foot-touchdown) using motion capture and force plate data.

Main Results:

• A comprehensive dataset featuring synchronized biomechanical and radar recordings is now available.
• Labeled events provide precise temporal markers for stability analysis.
• The dataset includes data from both young (≤32y) and old (≥64y) healthy individuals.

Conclusions:

• This dataset provides a valuable resource for advancing fall risk characterization.
• It enables novel research at the intersection of biomechanics, radar technology, and digital health.
• Provided Python utilities facilitate data accessibility and analysis for researchers.