Healthcare leaders have spent years trying to figure out how to manage the rising cost of aging, especially when it comes to Alzheimer’s disease. According to the American Journal of Managed Care, the condition cost the United States about $781 billion in 2025, including $232 billion in direct medical and long-term care and more than $400 billion in unpaid support from families. Loved ones provide roughly 6.8 billion hours of care each year, valued at over $233 billion, while households absorb more than $52 billion in out-of-pocket expenses. As costs climb with disease severity, the push for earlier and more precise ways to detect decline has become an economic issue. Researchers like Sodiq Omobolaji Fakorede are working at the center of that shift, focusing on how the brain signals instability long before a fall or medical crisis occurs.
Fakorede believes the biggest obstacle has been technology. Scientists have been able to measure brain activity or movement, but rarely at the same time without interference. “The biggest barrier has been that to study the brain, we historically had to keep the body still,” he explained. By combining Mobile Brain and Body Imaging with machine learning, his work captures how cognition and movement interact in real time, offering a clearer window into why balance declines as people age or experience cognitive impairment.
That insight opens the door to a more proactive model of care, one that could reduce costs and improve outcomes. The healthcare system often steps in only after a serious injury, when recovery is expensive, and independence is harder to regain. Fakorede believes prevention changes everything. “Shifting to a predictive model changes the economics entirely,” he said. Earlier detection of neural warning signs could lead to targeted therapies that cost far less than surgery or long-term care, while helping older adults maintain autonomy longer.
Fakorede envisions platforms that convert complex neurological data into clear, trackable insights for clinicians and insurers. A future ‘Neuro-Stability Score’ could help providers monitor risk and trigger early interventions. “This turns complex, noisy biological data into a simple, actionable metric,” he said. In a healthcare environment increasingly focused on value and outcomes, that kind of metric could support broader adoption of preventative care models.
The number of Americans age 65 and older is expected to rise sharply over the next two decades, and fall risk increases alongside cognitive decline. Fakorede’s approach is not limited to people with Alzheimer’s disease. It applies to anyone experiencing changes in memory, attention, or balance, potentially supporting millions who want to remain independent as they age.
And that demand is shaping new market opportunities. Aging-in-place technology stands out as a fast-growing space. Fakorede sees predictive monitoring systems becoming a cornerstone of home health. “I see my research informing the next generation of home health monitoring, technology that acts as a ‘check engine light’ for the brain,” he said. For startups, insurers, and healthcare providers, tools that anticipate risk rather than respond to it could define the next wave of the longevity economy.
Policy discussions are beginning to reflect this shift as well. Fakorede argues that reimbursement structures still prioritize treatment over prevention, even though preventative approaches often reduce long-term costs. If cognitive-motor data can demonstrate measurable reductions in fall rates, it could strengthen the case for new reimbursement models that reward early intervention and data-driven care.
Beyond economics and policy, his work is reshaping how clinicians think about falls themselves. Instead of viewing them purely as physical events, Fakorede frames them as neurological signals. “My work argues, especially in aging and Alzheimer’s disease, that a fall is often a cognitive symptom,” he said. That perspective is influencing research priorities and training programs, encouraging a more integrated view of brain health and mobility.
The impact of this work could disrupt the aging economy. Fakorede’s research provides the scientific foundation that could help bring predictive neuro-rehabilitation tools to market, shaping a new category of health technology used by hospitals, insurers, home health providers, and aging-in-place platforms. As these solutions become more widely used, they could attract investment while supporting a new specialized workforce. His work points to a practical path for managing the financial realities of an aging population while improving the quality of life for millions of older adults. It’s the kind of research that has the potential to influence how an entire industry grows while making life better for millions.
