Evaluation of functional deficits and falls risk in the elderly--methods for preventing falls.

Falls in the elderly have a profound impact on their quality of life through injury, increased fear of falling, reduced confidence to perform daily tasks and loss of independence. Falls come at a substantial economic cost. Tools to quantify falls risk and evaluate functional deficits allow interventions to be targeted to those at increased risk of falling and tailored to correct deficits with the aim of reducing falls rate and reducing ones risk of falling. We describe a system to evaluate falls risk and functional deficits in the elderly. The system is based on the evaluation of performance in a simple set of controlled movements known as the directed routine (DR). We present preliminary results of the DR in a cohort of 68 subjects using features extracted from the DR. Linear least-squares models were trained to estimate falls risk, knee-extension strength, proprioception, mediolateral body sway, anteroposterior body sway and contrast sensitivity. The model estimates provided good to fair correlations with (r=0.76 p<0.001), (r=0.65 p<0.001), (r=0.35 p<0.01), (r=0.53 p<0.001), (r=0.48 p<0.001) and (r=0.37 p<0.01) respectively.

A wearable triaxial accelerometry system for longitudinal assessment of falls risk.

Falls-related injuries in the elderly population are a major cause of morbidity and represent one of the most significant contributors to hospitalizations and rising health care expense in developed countries. Many laboratory-based studies have described falls detection systems using wearable accelerometry. However, only a limited number of reports have tried to address the difficult issues of falls detection and falls prevention in unsupervised or free-living environments. We describe a waist-mounted triaxial accelerometry (Triax) system with a remote data collection capability to provide unsupervised monitoring of the elderly. The basis of the monitoring is a self-administered directed-routine (DR) comprising three separate tests measured by way of the Triax. We present an initial evaluation of the DR results in 36 patients to detect early changes in functional ability and facilitate falls risk stratification. Extracted features considered alone show a correlation with falls risk of approximately rho=0.5. Estimation of falls risk using a linear least squares model provides a root-mean-squared error of 0.69 (rho=0.58, p<0.0002).

Falls management: detection and prevention, using a waist-mounted triaxial accelerometer.

We describe a distributed falls management system capable of real-time falls detection in an unsupervised living context and remote longitudinal tracking of falls risk parameters using a waist-mounted triaxial accelerometer. A self-administrable falls risk assessment is used to facilitate falls prevention. A web-interface allows clinicians to monitor the status of individuals and track their compliance with exercise interventions. Early identification of increased falls risk allows targeted interventions to be promptly administered. Real-time detection of falls allows immediate emergency response protocols to be deployed, reducing morbidity and increasing the independence of the community-dwelling elderly community.