Development of an Acceleration Based Fall Risk Detector
Development of an Acceleration Based Fall Risk Detector
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.
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.
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).
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Exclusion Criteria:
rachel.senden@bw.unimaas.nl043 3881383
Bakel, Bakel 5760 AA, Netherlands
marieke.lucassen@student.unimaas.nl
Maastricht, Limburg 6229 ER, Netherlands
rachel.senden@bw.unimaas.nl0433881383
rachel.senden@bw.unimaas.nl
K.Huntjes@AH.unimaas.nl
Lieve.Vanrusselt@mosaezorggroep.nl