Gait analysis and estimation of changes in fall risk factors.

Falls are a major problem for older adults. A continuous gait monitoring that provides fall risk assessment would allow timely interventions aiming for preventing falls. The objective of this work was to find out whether gait variables calculated from the acceleration signal measured during walk task in the baseline assessment can predict changes in commonly used fall risk assessment scales after 12 months follow-up. Forty two subjects were measured during walk test with a triaxial acceleration sensor worn on a waist belt at the lower back near the centre of mass. The fall risk was assessed using a test protocol, which included several assessment methods. Gait analysis was able to predict a decline in ABC, BBS and GDS total scores and slower time in STS-5 after twelve-months follow-up. A subsequent study is needed to confirm the model's suitability for data recorded in everyday lives.