One of the volunteers walking on the treadmill. Photo credit: Michael Raitor.

One of the volunteers walking on the treadmill. Photo credit: Michael Raitor.

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As we get older, our bodies stop performing as they once did. We aren't as strong as we once were, we don't see as well and we start to be less mobile. These changes inevitably lead to almost a third of people over the age 65 falling each year, resulting in injuries and occasionally death. In the United States alone, it costs the healthcare system billions of dollars annually. However, while aging is a certainty, falling may be preventable. ‘One big challenge is that small balance impairments can go unnoticed until someone actually falls. So, we wanted to ask: can we detect these impairments before someone gets hurt?’ explains Jiaen Wu of Stanford University, USA. Wu partnered with Michael Raitor, Guan Tan, Kristan Staudenmayer, Scott Delp, Karen Liu and Steven Collins, also of Stanford University, to see if there were measurements that clinicians could make early on that would help them determine who is at risk of falling in the future.

To begin to answer this question, the team fitted 10 healthy volunteers between the ages of 24 and 31 with a harness around their waist attached in the front, back and sides to ropes and markers that would allow an array of 11 cameras to track the movement of various body parts as they walked comfortably on a treadmill at 1.25 m s−1. The researchers measured various aspects of the participants’ walking, such as how predictable their foot placement was and how far their center of mass moved sideways. Then, Wu and colleagues repeated the measurements, but this time the walkers were asked to wear ankle braces, an eye mask or pneumatic jets, all of which encumbered their walking in similar ways to the changes that accompany aging. This time, it became more difficult to predict how wide each step would be – or even when the next step would take place – while the walkers were wearing their impediments, suggesting that making their surroundings more difficult to see or making it more difficult to move their limbs properly threw off their balance.

When the scientists compared each person's measurements from their normal walking with their hampered walking, not all the metrics were good at predicting balance issues. In fact, only three of the six measurements made before the impairments were any good at foretelling if someone was at risk for a fall: how variable the participants’ step width was, how different the timing of each step was and where they placed their feet. Each of these measurements was over 86% effective at predicting balance issues. In addition, Wu and colleagues also unexpectedly pulled on the ropes attached to the walker's harness to see how they recovered from the sudden loss of balance. Surprisingly, adding this small amount of recovery information to the volunteer's measurements didn't really help as much as the team expected. ‘We thought that seeing how people recover from a pull would reveal more about their balance ability, but in this study, the normal walking data were just as informative in most cases,’ says Wu.

When the researchers compared each person's walking measurements with the average of the whole group, they found that this was worse at predicting if a single person would have balance issues than simply comparing each person's measurements before and after they were impaired. Normally, doctors only test someone's way of walking when they start having mobility issues. Wu and colleagues suggest that measuring someone's walking before they attain old age could give clinicians an early warning, hopefully preventing falls before they happen, potentially saving lives and saving health care systems billions as well.

Wu
,
J.
,
Raitor
,
M.
,
Tan
,
G. R.
,
Staudenmayer
,
K. L.
,
Delp
,
S. L.
,
Liu
,
K.
and
Collins
,
S. H.
(
2025
).
Detecting artificially impaired balance in human locomotion: metrics, perturbation effects and detection thresholds
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J. Exp. Biol.
228
,
jeb249339
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