Innovative Fall Prevention Program Supports Older Adults with Mild Cognitive Impairment

Falls are a leading health concern for older adults, often resulting in injuries that can cause serious health complications, reduce independence, and diminish quality of life. These incidents also place a significant burden on healthcare systems, as fall-related injuries lead to increased medical service usage and higher treatment costs. Recently, a new approach utilizing advanced technology and personalized interventions has shown promise in reducing fall risks among this vulnerable population.

Researchers from the University of Pennsylvania's School of Nursing conducted a proof-of-concept study demonstrating the feasibility of Sense4Safety, an innovative, nursing-driven, technology-supported system designed to predict and prevent falls in older adults with mild cognitive impairment (MCI). The study, published in The Journals of Gerontology, Series A, highlights how combining passive in-home monitoring with targeted coaching can help identify early signs of fall risk and facilitate timely interventions.

Dr. George Demiris, a professor at Penn, emphasized the importance of targeting fall prevention in older populations, noting that falls often precede other health complications. The study focused on individuals living alone in low-income housing, a group at heightened risk due to vulnerabilities such as cognitive decline, environmental hazards, and limited support.

The Sense4Safety system integrates passive monitoring through depth sensors installed in the home, which gather gait and movement data while preserving privacy by rendering images as silhouettes. Alongside this, participants received personalized coaching that included education on environmental adjustments—like improving lighting or removing loose rugs—and tailored exercise programs known to reduce fall risk, such as the Otago Exercise Program.

Most participants found the program beneficial, feeling safer at home and more aware of environmental risks. The coaching sessions and behavioral insights helped some individuals recognize risky behaviors, such as sitting down without checking nearby chairs, potentially preventing near-falls.

One key advantage of the system is its focus on ease of use. Unlike wearable devices, the passive sensors require no user interaction, charging, or software operation, making it suitable for older adults who may struggle with technology. Privacy concerns are mitigated through data processing that ensures gait data is anonymized and only relevant information is collected.

The research team also involved participants in understanding their own data, fostering greater engagement. Future studies intend to compare a control group receiving only passive monitoring with an intervention group receiving additional coaching and education, aiming to validate the program’s effectiveness.

Ultimately, this technology could be scaled up for broader use, especially for seniors recently discharged from hospitals or those at high risk for falls. Implementing such preventive strategies can significantly improve older adults’ quality of life while reducing healthcare costs associated with fall injuries.

source: https://medicalxpress.com/news/2025-08-fall-older-adults-mild-cognitive.html