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

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.

Study Overview

• Status: Completed
• Conditions: Gait
• Intervention / Treatment: Other: Older adults

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.

• Study Type: Observational
• Enrollment (Actual): 100

Contacts and Locations

Study Locations

• Korea, Republic of
  • Seoul, Korea, Republic of, 06351
    • Samsung Medical Center

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 65 years to 84 years (Older Adult)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

Community seniors aged 65 to 84 years

Description

Inclusion Criteria:

• Community seniors aged 65 to 84 years
• A person who has no history of central nervous system disease

Exclusion Criteria:

• Older adults who are unable to walk independently due to vision loss, fractures, etc.
• An elderly person who had musculoskeletal history that could cause problems in the function of the lower extremities, such as fractures, within three months before recruitment;
• In case it is difficult to understand the task due to severe cognitive impairment (Korean simplified mental health examination, K-MMSE score 10 or less)
• In the event of a serious mental illness, such as schizophrenia or bipolar disorder;
• In case of severe dizziness and difficulty in pedestrian inspection
• Persons not eligible for examination

Study Plan

How is the study designed?

Design Details

• Observational Models: Case-Only
• Time Perspectives: Cross-Sectional

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Older adults; The data for motor function and gait pattern analysis was obtained.	Other: Older adults; The data for motor function and gait pattern analysis was obtained.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Gait analysis	Gait analysis is a process of measuring and evaluating the walking patterns of patients by using surface electromyograph and motion analysis system. All participants perform overground walking to assess the change of kinematic, kinetic and muscle activation using a motion analysis and surface EMG	1 hour

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Change on metabolic energy expenditure	All subjects underwent measurements respiratory metabolism energy during treadmill walking at a comfortable speed for 5 minutes. It assess the change of metabolic energy expenditure using a portable cardiopulmonary metabolic system (Cosmed K4b², Rome, Italy).	15 minutes
Change on muscle activity	All subjects underwent measurements of muscle activity during treadmill walking at a comfortable speed for 5 minutes	30 minutes
Change on brain activity	All subjects underwent measurements of brain activity by measuring fNIRS during treadmill walking at a comfortable speed and high speed for 5 minutes	30 minutes
Short Physical Performance Battery (SPPB)	The Short Physical Performance Battery (SPPB) is a series of tests used to evaluate lower extremity function and mobility in older people.	5 minutes
Four Square Step Test (FSST)	The Four Square Step Test (FSST) is used to assess dynamic stability and the ability of the subject to step over low objects forward, sideways, and backward.	5 minutes
The Timed Up and Go test (TUG)	The Timed Up and Go test (TUG) is a simple test used to assess a person's mobility and requires both static and dynamic balance. It uses the time that a person takes to rise from a chair, walk three meters, turn around, walk back to the chair, and sit down.	5 minutes
10 meter walk test (10MWT)	Measure of self selected speeds by measuring the time it takes an individual to walk 10 meters. To perform the test, patient walks 10 meters (33 ft) and the time is measured when the leading foot crosses the start line and the finish line. The instructions are: "Please walk this distance at your normal pace when I say go."	5 minutes
Modified Bathel index (MBI)	The MBI is a measure of activities of daily living, which shows the degree of independence of a patient from any assistance. It covers 10 domains of functioning (activities): bowel control, bladder control, as well as help with grooming, toilet use, feeding, transfers, walking, dressing, climbing stairs, and bathing.	5 minutes
6 minutes walking test (6MWT)	The six-minute walk test (6MWT) measures the distance an individual is able to walk over a total of six minutes on a hard, flat surface. The goal is for the individual to walk as far as possible in six minutes.	6 minutes
Fall Efficacy Scale (FES)	The Falls Efficacy Scale (FES) is a ten-item test rated on a 10-point scale from not confident at all to completely confident.	5 minutes

Collaborators and Investigators

• Sponsor: Samsung Medical Center

Study record dates

Study Major Dates

• Study Start (Actual): February 25, 2021
• Primary Completion (Actual): August 31, 2022
• Study Completion (Actual): August 31, 2022

Study Registration Dates

• First Submitted: January 22, 2021
• First Submitted That Met QC Criteria: January 22, 2021
• First Posted (Actual): January 26, 2021

Study Record Updates

• Last Update Posted (Actual): March 1, 2023
• Last Update Submitted That Met QC Criteria: February 27, 2023
• Last Verified: February 1, 2023

More Information

Terms related to this study

• Keywords: Muscle activity; Brain activity; Fall prediction model; Gait Pattern; Cardiopulmonary metabolic cost
• Other Study ID Numbers: 2020-09-172

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No