A study conducted as part of the NIH’s Women’s Health Initiative suggests that wearing a device measuring one’s walking patterns could help predict one’s fall risk and determine preventative measures to help reduce it.
The study included 67 women, all over the age of 60, who were tested on their walking ability and asked about the number of falls they had experienced in the past year. Participants also wore a small device with motion sensors that measured their walking patterns for 1 week.
Researchers suggest that data extracted automatically from the devices could accurately predict the participants’ risk of falling, as measured by physical examinations of unsteadiness in standing and walking. Their findings were published in Nature Digital Medicine.
“Our prediction showed that we could very accurately tell the difference between people that were really stable and people that were unstable in some way,” says Bruce Schatz, head of the Department of Medical Information Science in the University of Illinois College of Medicine at Urbana-Champaign and faculty member of the IGB’s Computing Genomes for Reproductive Health research theme, according to a media release from Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign.
Previous studies suggest that older individuals fall differently than younger individuals. Younger people fall if they misjudge something, such as a slippery surface. But older adults fall because their bodies are unstable, causing them to lose balance when walking or become unsteady when standing up and sitting down.
This difference gave Schatz and his team the idea that they might be able to measure this instability. The device they used, called an accelerometer, was able to measure the user’s walking patterns and how unsteady they were. They combined this measurement with the individual’s fall history to determine the risk of falling in the future.
Being able to predict the fall risk is significant because many older adults often don’t pay attention to the fact that they are unstable until after they fall. But if they know they’re at risk, they can do rehabilitation exercises to increase their strength and reduce their chance of falling, the release continues.
Schatz sees the successful outcome of this research as a sign that, in the future, more wearable devices, or even smartphone apps, will be able to measure walking patterns and warn users of their fall risk, the release explains.
“I work a lot with primary care physicians, and they love this (idea), because they only see people after they start falling,” Schatz states. “At that point, it’s already sort of too late.”
He adds that most people are aware that falling among older adults is a common problem, but have a sense of hopelessness about this issue—if it happens to so many older adults, then what can be done?
“There is a solution which is completely workable and isn’t very expensive, but requires different behavior,” Schatz shares in the release. “That message is not getting out.”
He predicts that the quality of life among older adults could improve as medicine and health care become more predictive and effective.
“The future is different,” Schatz concludes. “And it’s because of projects like this.”
[Source(s): Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Science Daily]