Send to:

Choose Destination
See comment in PubMed Commons below
Physiol Meas. 2012 Dec;33(12):2049-63. doi: 10.1088/0967-3334/33/12/2049. Epub 2012 Nov 15.

Quantitative falls risk estimation through multi-sensor assessment of standing balance.

Author information

  • 1Technology Research for Independent Living (TRIL), Dublin, Ireland.


Falls are the most common cause of injury and hospitalization and one of the principal causes of death and disability in older adults worldwide. Measures of postural stability have been associated with the incidence of falls in older adults. The aim of this study was to develop a model that accurately classifies fallers and non-fallers using novel multi-sensor quantitative balance metrics that can be easily deployed into a home or clinic setting. We compared the classification accuracy of our model with an established method for falls risk assessment, the Berg balance scale. Data were acquired using two sensor modalities--a pressure sensitive platform sensor and a body-worn inertial sensor, mounted on the lower back--from 120 community dwelling older adults (65 with a history of falls, 55 without, mean age 73.7 ± 5.8 years, 63 female) while performing a number of standing balance tasks in a geriatric research clinic. Results obtained using a support vector machine yielded a mean classification accuracy of 71.52% (95% CI: 68.82-74.28) in classifying falls history, obtained using one model classifying all data points. Considering male and female participant data separately yielded classification accuracies of 72.80% (95% CI: 68.85-77.17) and 73.33% (95% CI: 69.88-76.81) respectively, leading to a mean classification accuracy of 73.07% in identifying participants with a history of falls. Results compare favourably to those obtained using the Berg balance scale (mean classification accuracy: 59.42% (95% CI: 56.96-61.88)). Results from the present study could lead to a robust method for assessing falls risk in both supervised and unsupervised environments.

[PubMed - indexed for MEDLINE]
PubMed Commons home

PubMed Commons

How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for IOP Publishing Ltd.
    Loading ...
    Write to the Help Desk