Objective assessment of balance and mobility in elderly populations using body-worn sensors has recently become a prevalent theme in falls-related research. Recent research by the authors identified mean absolute-valued vertical angular velocity measured using shank mounted inertial sensors during a timed-up-and-go test as having a strong association with falls history in a group of elderly adults. This study aimed to investigate the clinical relevance of this parameter by exploring the relationship between it and minimum ground clearance (MGC) measured with an optical motion capture system. MGC is an important variable when considering trip-related falls risk. This paper also presents a method of estimating properties of MGC during walking, across a range of speeds and gait patterns, using body-worn inertial sensors. We found that mean MGC and coefficient of variation (CV) MGC are correlated with mean absolute-valued vertical angular velocity and acceleration as measured by shank or foot mounted inertial sensors. Regression models generated using inertial sensor derived variables were used to robustly estimate the mean MGC and CV MGC measured by an optical marker-tracking system. Foot-mounted sensors were found to yield slightly better results than sensors on the shank. Different walking speeds and gait patterns were not found to influence the accuracy of the models. We conclude that these findings have the potential to evaluate a walking trial using body-worn inertial sensors, which could then be used to identify individuals with increased risk of unprovoked collisions with the ground during locomotion.
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