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Sloot, L. H.

Publications and source records attributed to Sloot, L. H..

2 recordsLinked to original sources

The size of the functional base of support decreases with age

Falls occur more often as we age. To identify people at risk of falling, balance analysis requires an accurate base-of-support model. We previously developed a functional base-of-support (fBOS) model for standing young adults and showed that its area is smaller than the footprint area. Our fBOS model is a polygon that contains centre-of-pressure (COP) trajectories recorded as standing participants move their COP in the largest possible loop while keeping their feet flat on the ground. Here we assess how the size of the fBOS changes with age by comparing 38 younger (YA), 14 middle-aged (MA), and 34 older adults (OA). The fBOS area is smaller in older adults: OA area is 58% of the YA area (p < 0.001), and 59% of the MA area (p = 0.001), with no difference between YA and MA. The reduction in fBOS area among the OA is primarily caused by a reduction in the length of the fBOS. In addition, among older adults smaller fBOS areas correlated with a lower score on the Short Physical Performance Battery ({tau}=0.28, p = 0.04), a reduced walking speed ({tau}=0.25, p = 0.04), and a higher frailty level (p = 0.09). So that others can extend our work, we have made our fBOS models available online.

bioengineering↗

A polygon model of the functional base-of-support improves the accuracy of balance analysis

Mathematical balance models have the potential to identify people at risk of falling. However, most balance models depend on a model of the base-of-support (BOS) of the feet to calculate how well someone is balancing. Here, we evaluate the functional base-of-support (fBOS) during standing: the convex polygon on the bottom of the foot that can support a large fraction of the bodys weight. First, we develop a geometric model of the fBOS by measuring the center-of-pressure (COP) and kinematic data of the feet of 27 younger adults instructed to move their body in large loops without taking a step. Next, we extract a planar convex polygon that contains the COP data. Finally, we compare the area of this fBOS model to a marker-based BOS model before evaluating if the fBOS differs across four common conditions: footwear, stance-width, foot dominance, and during single and double-stance. We found that the fBOS is much smaller (23% the size) than a markerbased BOS model. Our analysis suggests that using the fBOS, rather than a marker-based BOS, can improve the accuracy of the margin-of-stability by 20% of foot width and 16% of the length. In addition, we found that the fBOS area does not differ across footwear (p = 0.88), stancewidth (p = 0.88), and foot dominance (p = 0.68), but during single stance, the fBOS is 17% (p = 0.0003) larger than during double-stance. The variability of the fBOS area suggests that future studies should establish the repeatability and reliability of the assessment and systematically study the effects of different types of footwear. We have put the fBOS models, example data, and code in the public domain to help others build on our work.

bioengineering↗