Balance Mat for Fall-Risk Screening

Falls are a major cause of injury and loss of independence in older adults, and objective postural sway testing can help identify balance decline before a fall occurs. The research standard for measuring sway is a force plate, which is accurate but expensive, bulky and largely confined to laboratory settings. Consequently, everyday clinical practice often relies on balance scales and observational tests that are less sensitive to small changes in sway and may miss early balance deficits.

This PhD research validates the Balance Mat, a portable device that uses a grid of optical fibres to detect how a person’s weight is distributed across their feet. The structured validation programme includes technical characterisation of the sensor, concurrent validation against a laboratory force plate, and discriminant validation to determine whether its sway measures differ between fallers and non-fallers. The final stage trains machine-learning models on sway measurements, questionnaire responses and falls history to classify each person as being at high or low risk of falling. Across these studies, the Balance Mat’s sway measures demonstrate good reliability and validity, while the classification model can distinguish between older adults at high and low fall risk. The research supports the development of an affordable, portable tool for clinical fall-risk screening.