NCT04723927

Development of Fall Prediction Model for Older Adults Based on Multi-faceted Data

Development of Fall Prediction Model for Older Adults by Analysis of Walking Patterns Based on Multi-faceted Biosignal Data

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 100 (actual)
• Sponsor: Samsung Medical Center · Academic / Other
• Sex: All
• Age: 65 Years – 84 Years
• Healthy volunteers: Accepted

Summary

This study aimed to develop a fall prediction model for older adults by measuring the multi-faceted biosignal data to classify the walking patterns and by identifying causal relationships with the variables that affect the fall.

Detailed description

This study aimed to develop a fall prediction model by measuring the multi-paceted biosignal data for the elderly's physical function and walking to classify the walking patterns of the elderly, and by identifying causal relationships and influences with the variables that affect the fall.

Conditions

• Gait

Interventions

Type	Name	Description
OTHER	Older adults	The data for motor function and gait pattern analysis was obtained.

Timeline

• Start date: 2021-02-25
• Primary completion: 2022-08-31
• Completion: 2022-08-31
• First posted: 2021-01-26
• Last updated: 2023-03-01

Locations

1 site across 1 country: South Korea