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Falls pose a big danger to older adults, typically leading to accidents that result in different well being issues, decreased independence, and a decrease high quality of life. In addition they pose a substantial burden on the well being care system—fall-related accidents are related to an elevated use of providers, making them among the many costliest medical circumstances to deal with.
Now, within the proof-of-concept research, researchers from Penn’s College of Nursing and their colleagues have demonstrated the feasibility of utilizing an progressive, technology-supported, nursing-driven invention referred to as Sense4Safety to foretell fall danger. Their findings are revealed within the The Journals of Gerontology, Collection A: Organic Sciences and Medical Sciences.
“We’re focusing on falls because they are a critical issue for older adults—sometimes a fall is the beginning of a lot of other health-related complications or adverse events,” says Penn Integrates Information College Professor George Demiris of the College of Nursing and the Perelman College of Medication. He provides that they’re typically the outcomes of gathered vulnerabilities resembling cognitive standing, revenue, residing circumstances, the atmosphere, and well being.
“[A fall] is often a harbinger of an individual’s decline,” agrees Nancy A. Hodgson, Claire M. Fagin Management Professor in Penn Nursing. “And so, we are trying to predict upstream what’s happening—changes in gait or whatever’s going on before the fall event—so that we can intervene sooner and prevent whatever’s going to happen after that fall.”
On this research, they recruited 11 adults aged 65 years and older who had gentle cognitive impairment to obtain the intervention for 3 months.
“Executive functioning and processing speed are all essential for maintaining balance and navigating your home safely,” says Hodgson. “People with mild cognitive impairment might have trouble with things like judging distances or remembering to use an assistive device or processing multiple tasks like simultaneously walking and talking.”
“Older adults with mild cognitive impairment who live alone in low-income housing or are socially vulnerable are among the highest risks for falling,” provides Demiris. “So, we wanted to first see if [the intervention] would work in a population that would have the most to gain from a fall prevention strategy.”
Sense4Safety, the intervention developed by the analysis group, contains each passive monitoring by way of an in-home depth sensor and energetic engagement and training with a coach who has experience with train applications.
“Sense4Safety is a multicomponent intervention that looks at both getting technology-mediated assessments—so better understanding what’s going on in the home with the depth sensors—but also having a coach who can work with the older adult to figure out if there are environmental modifications that can be made,” explains Demiris. “For example, could we do something about the poor lighting in the hallway or the loose rug in the living room?”
The intervention additionally has a tailor-made train program—the Otago Train Program—which might be tailor-made for individuals’s skills.
“Adding an exercise component for community-dwelling older adults reduces the fall risk by more than a third,” says Hodgson. “Any well-designed exercise program that brings in balance and strength training can reduce the fall risk.”
The research finds that the majority contributors discovered the intervention to be helpful, offering them with a way of security and serving to them be extra conscious of their residence atmosphere. In addition they noticed worth within the behavioral parts—teaching periods, train, and training.
“We had one participant who consistently—when they got up—would sit down walking backwards without looking at where the chair was. They had two near falls because the chair had moved,” says Demiris. “So, looking at the video actually helped them realize how risky this was.”
Potential privateness points are addressed via knowledge processing—photos seem solely as silhouettes, and the algorithms used for the depth sensors are tuned for under the research participant.
“If a neighbor visits, their gait characteristics are not going to be captured,” explains Demiris, including that they selected this mannequin of passive monitoring as a result of they needed one thing that didn’t require contributors to should be taught any new {hardware} or software program.
“We wanted to use this technology because when it comes to fall prevention in this population, it is not easy to use wearables. With wearables, you have to remember to charge them, take them off, and put them back on, and you have to operate a system,” says Demiris.
He provides that they tried to incorporate the research contributors within the course of as effectively. “So fairly than simply saying, ‘Hey, we’ve this in your house, and we’ll let you realize if one thing occurs,’ we’ve been making an attempt to indicate them their very own knowledge.
“Part of our effort has been, can we create a more user-friendly dashboard that has gait-related information not for the clinician—which is the current dashboard we have—but also for the older adults themselves?”
For his or her subsequent step, the group hope to run a scientific trial with contributors randomly assigned to both the management group, who will simply obtain passive monitoring, or the invention group, who will obtain the Sense4Safety invention that features the teaching train and academic parts along with passive monitoring by way of depth sensors.
The researchers hope sooner or later that this intervention will probably be out there to populations at excessive danger for falls—older adults lately launched from the hospital, for instance.
“Preventing falls can not only be significant in improving quality of life for people, especially those living alone, but it can also be a significant cost saving for our health care system,” says Demiris.
Extra info:
George Demiris et al, Feasibility and Acceptability of a Expertise-Mediated Fall Threat Prevention Intervention for Older Adults With Delicate Cognitive Impairment, The Journals of Gerontology, Collection A: Organic Sciences and Medical Sciences (2025). DOI: 10.1093/gerona/glaf043
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Fall prevention program developed for older adults with gentle cognitive impairment (2025, August 4)
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