Predicting Falls With Precision
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Farwa Ali, M.B.B.S., is a neurologist dedicated to improving quality of life for older adults by advancing the understanding of gait and balance disorders. Her research explores how artificial intelligence (AI) and data science can be harnessed to predict falls, paving the way for earlier interventions and preventive strategies.
Dr. Ali sat down with Mayo Clinic Magazine to share the personal experience that inspired her work, key insights from her research, and her vision for using technology to protect the aging population. This interview has been edited for clarity and length.
What initially sparked your interest in this area of research?
My interest in fall mechanisms and prediction in aging individuals dates to a personal event. My mom, who is otherwise healthy, had a fall in her 60s. The fall resulted in fractures, which affected her confidence in balancing and many daily activities. I saw firsthand that one fall can be life-changing. This situation really motivated me as it hit close to home.
As a movement disorders provider, I am passionate about gait and balance because it affects every single human being as we get older and all my patients who suffer from neurological disorders. Over the age of 65, 1 in 4 people experience a fall annually. While gait and balance changes may be thought of as part of aging, they can be an early indicator of neurodegenerative disease and give us an opportunity to intervene and prevent falls before they occur.
My research is trying to answer some important questions: Can we predict falls before they happen? Can we predict what causes them? How can we prevent them?
— Farwa Ali, M.B.B.S.
Currently, our ability to predict falls before they occur is limited, and there are few treatments for gait and balance disorders. As a result, falls have a very significant healthcare impact. My research is trying to answer some important questions such as: Can we predict falls before they happen? Can we predict what causes them? How can we prevent them?
What are some key findings that have emerged from your research so far?
I have been able to partner with the Mayo Clinic Study of Aging to analyze several thousand gait samples, and we are working to gain a better understanding of how a patient’s clinical history and gait performance predict future falls.
We were pleased to publish some of these initial results in Nature Communications in early 2025. We found that individuals with worse gait performance had higher levels of Alzheimer's disease biomarkers, indicating that changes in gait can be an early sign of brain pathology, even before cognitive symptoms appear.
How does your research integrate AI?
We’re actively working to use AI and data science to predict incident falls in the aging population. In partnership with the Mayo Clinic Study of Aging, we are using large datasets to discover clues in a patient’s gait phenotype that can predict future risk of a fall before it actually occurs. We are also evaluating how this relates to early neurodegenerative diseases.
Why is your research important?
Falls are very common among older adults. The healthcare economic burden and individual and societal impact of falls are high and are projected to increase as the aging population grows. Older adults also have a higher burden of neurological diseases, such as stroke and Parkinson’s, that can cause disability due to both cognitive and motor issues. Identifying individuals at risk of falls from aging and neurodegeneration can allow early diagnosis and implementation of preventive strategies. Our goal is to develop a tool to predict falls before they happen so we can identify people who are at highest risk and institute appropriate preventive measures.
With generous support from benefactors, I have been able to advance my research by supporting a multidisciplinary team and work toward the aims of the project. I'm incredibly grateful for their investment in science and the betterment of humanity.
Dr. Ali is a recipient of the Tianqiao and Chrissy Chen Early-Career Development Award in Translational Research. The Chen Institute’s generous support accelerates projects that leverage AI and translate it into applications for patient care.
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