Is it possible to predict falls in older adults using gait kinematics?

Abstract

Background: Gait kinematic parameters have been reported as an important clinical tool to assess the risk of falls in older adults. However, the ability of these parameters to predict falls in the older population is still unclear. Objective: To identify the ability that gait kinematic parameters present to predict fall in older adults. Methods: Data from 102 older adults, who live in a community setting, were considered for this study. For data collection, older subjects had to walk on a 14 meter-walkway in their preferred gait speed. The incidence of falls was recorded at baseline together with gait kinematics and then every three months during the period of the study. The ability of gait kinematic parameters to predict falls was tested using the ROC curve. Results: Stance time variability, swing time, and stride length presented a sensitivity to predict falls in older adults higher than 70%. Conclusion: Gait kinematic parameters, such as stance variability, swing time, and stride length may predict future falls in older adults.