Development of an Acceleration Based Fall Risk Detector — field  

Fall Risk Clinical Trial

Official title: Development of an Acceleration Based Fall Risk Detector

Status Recruiting

Clinical Trial Summary

Because the increasing fall problem, mainly due to an impaired gait and balance ability, this study will investigate fall risk by detecting fall related movement characteristics. Based on the promising results using accelerometry for accurate and objective gait analysis, fall risk will be measured using a triaxial accelerometer.

At the moment our group is performing a study titled 'identify subjects at risk for falling using accelerometry'. In this study, fall related movement characteristics (gait, balance, stumble reaction) are identified in healthy younger and older subjects under standardised laboratory circumstances. In this way, specific characteristics can be selected which are responsible for fall risk.

The aim of this study is investigating if the acceleration based fall risk detector can be applied in daily life with target groups.

Clinical Trial Description

A first step to field measurement with target group is the measurement of elderly with a certain fall risk in a simple field condition like a nursing home.

First fall risk is assessed in elderly using the Tinetti scale (score between 19-24) which is the gold standard for fall risk assessment . This scale consist of a gait and balance score. Only subjects who have a fall risk are included for further measurements.

1. A gait test will be performed to analyze movement parameters. Subjects have to walk 6 times a 20 meter distance at preferred speed while a small (56mmx61mmx15mm), light weight (5g) and ambulant accelerometer is attached on the sacrum with an elastic belt. The accelerometer measures accelerations of the body in three directions (antero-posterior, media-lateral and cranial-caudal) with a sample frequency of 100Hz.

2. The balance ability will be tested by performing 4 balance tasks while the same accelerometer measures the movements of the body. Subjects have to stand with feet closed on a normal or foam surface while having the eyes open and closed.

3. The Get Up and Go test is performed: subjects start in sitting position, have to rise, walk 3m, turn around, walk back and sit again. The time needed to perform this test is measured.

4. 20 subjects (remaining in Scharweyerveld and Zorgboog) are monitored for one day and 20 elderly women (>70y) (recruited at the F&O policlinic MUMC)are measured for 5 successive days, to investigate the mobility and more fall related movement parameters. The accelerometer is attached to the sacrum in the morning. First the other 2 measurements are performed, and then subjects wear the device during the whole day. The accelerometer is small, light and ambulant which is not interfering with daily activities. Subjects have to keep a diary to note all activities performed during that day. THis will be used to explain the acceleration signal.

For the subject recruited from the F&O poli, a fall diary is kept for one year were subjects have to note when a fall has happened. In addition muscle strength in measured in this population and a questionnaire concerning quality of life (Euroqol) is completed in this group.

All acceleration data will be analyzed using specific algorithms programmed in Matlab(c). Statistical analysis will be performed in SPSS using pearson correlation to investigate correlations between gait parameters, balance characteristics and the ability perform the Get Up and Go test. Pearson correlation will also be used to validate the objective gait and balance test with the Tinetti scale. Differences in function tests between elderly at risk (measured in this study) and healthy subjects (measured in a previous study under lab conditions) will be investigated using ANOVA (p< 0.005). ;

Study Design

Intervention Model: Single Group Assignment, Masking: Open Label, Primary Purpose: Prevention

Related Conditions & MeSH terms

• Fall Risk

• NCT number: NCT00767429
• Study type: Interventional
• Source: Maastricht University Medical Center
• Contact: Rachel Senden, drs
• Phone: 043 3881383
• Email: rachel.senden@bw.unimaas.nl
• Status: Recruiting
• Phase: N/A
• Start date: August 2008
• Completion date: October 2010