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Related Experiment Video

Updated: May 14, 2026

Using Motion Capture Technology in the Instrumented Timed Up and Go Test to Detect the Risk of Falling in Aged Adults

Using Motion Capture Technology in the Instrumented Timed Up and Go Test to Detect the Risk of Falling in Aged Adults

Published on: October 25, 2024

[Fall prediction model for community-dwelling elders based on gender].

¹Ewha Womans University, Seoul, Korea. yes100406@naver.com

Journal of Korean Academy of Nursing

|February 1, 2013

Summary

Gender influences fall risk in elders. For men, Activities of Daily Living & Instrumental ADL ability predicts falls. For women, fear of falling and ADL/IADL ability are key factors.

Area of Science:

Gerontology
Public Health
Epidemiology

Context:

Falls are a major concern for community-dwelling elders.
Understanding gender-specific fall predictors is crucial for targeted interventions.
Previous research has identified various risk factors for falls in older adults.

Purpose:

To explore gender-based factors associated with the number of falls in community-dwelling elders.
To identify specific predictive variables for fall frequency in older men and women.

Summary:

This study analyzed 8 predictive variables in 403 elders (206 males, 197 females) aged 60+.
For men, Activities of Daily Living (ADL) & Instrumental ADL (IADL) ability explained 16% of fall variance.
For women, fear of falling and ADL/IADL ability explained 15% of fall variance.

Keywords:

Elderly Falls Gender

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Design and Analysis for Fall Detection System Simplification

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

Related Experiment Videos

Last Updated: May 14, 2026

Using Motion Capture Technology in the Instrumented Timed Up and Go Test to Detect the Risk of Falling in Aged Adults

Using Motion Capture Technology in the Instrumented Timed Up and Go Test to Detect the Risk of Falling in Aged Adults

Published on: October 25, 2024

Design and Analysis for Fall Detection System Simplification

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

Impact:

Findings support a comprehensive, gender-based fall prediction model for community-dwelling elders.
Results can inform the development of tailored fall prevention and intervention programs.
Highlights the importance of considering gender in geriatric fall risk assessment.