Mobile Fall Risk Assessment Solution for Daily-Life Settings

Prevention of falls requires accurate means for fall risk assessment in order to identify persons at risk. This paper introduces a novel mobile fall risk assessment solution for daily-life settings. The solution contains an Android application that uses acceleration sensor data received via Bluetooth LE connection. The application guides through a simple walk test, analyzes the acceleration data measured from the acceleration sensor attached to the lower back and gives feedback about the fall risk for the user. Preliminary user tests with 12 healthy subjects were conducted to evaluate the feasibility of the solution. Each test subject performed three walks demonstrating normal, dragging and slow gait. The results showed that the acceleration features calculated by the application distinguish normal gait from dragging and slow gaits. Further collection of comprehensive data set with older adults is needed to adjust the application parameters appropriately for the target group.