An estimated 6.5 million Americans are now living with Alzheimer's disease. Even as the memory loss, disorientation, and other symptoms characteristic of this form of dementia worsen over time, many patients also experience moments of stunning clarity—a phenomenon that is not clearly understood.
Lucidity, a mobile application and ecosystem being developed by a team led by Kishore Kuchibhotla, an assistant professor of psychological and brain sciences at Johns Hopkins Krieger School of Arts and Sciences, may help. Using the tablet-based application, caregivers help patients take a battery of simple cognitive tests and also use the tablet's microphone and camera to record patients multiple times per week, including when they are lucid. During these activities, the app's sensor module captures key health data. The goal is to then apply data mining and artificial intelligence to these individualized datasets to identify factors that drive patients' cognitive fluctuations and even predict triggers for lucid episodes.
"Our insight is simple: patients with Alzheimer's disease and other forms of dementia do not just get progressively worse," Kuchibhotla says. "There are moments of clarity or periods of higher cognition embedded in the slow, progressive decline. What drives these fluctuations? How frequent are they? And, from a therapeutic perspective, can we identify environmental or internal factors that drive them? These fluctuations have been nearly impossible to study in the clinic and are a perfect use case for mobile technologies in the home. We also hope that the data and insights gleaned will lead to the development of virtual reality programs that could actually improve patients' cognition."
Lucidity is one of 14 pilot projects to receive funding from the Johns Hopkins Artificial Intelligence and Technology Collaboratory for Aging Research, or JH AITC, a multicenter effort focusing on the use of artificial intelligence to improve the long-term health and independence of older people.
Totaling nearly $3 million, this first round of awards will support a diverse set of research projects including a virtual reality platform to reduce social isolation; an AI-powered handlebar device to help seniors improve their balance; and advanced algorithms to screen for cataracts and other age-related ailments.
"I am thrilled to see these important projects get underway," said Jeremy Walston, a professor of geriatric medicine in the Johns Hopkins School of Medicine and co-director of JH AITC. "The integration of engineering and AI approaches into the care of older adults represents an exciting new frontier for the improvement of their health and well-being. In addition, the engagement of the business community in these efforts will help accelerate the availability of these novel paradigms to those who need them the most."
Launched in 2021 with a $20 million grant from the National Institute on Aging, the JH AITC is a a hub for aging innovation and cross-disciplinary collaboration across the Hopkins community. Walston says a primary goal of the AITC is to connect this research network with outside stakeholders, including older Americans and caregivers, technology developers, and industry partners.
The JH AITC selects projects to fund with up to $200,000 in direct costs over a one-year period, during which awardees also receive access to resources and mentorship from Hopkins experts in fields including computer science, nursing, medicine, and technology commercialization.
Other projects funded this round include:
Sequoia Neurovitality, which aims to slow cognitive decline in older adults by enhancing deep sleep with acoustic stimulation through a smart headband. Poor sleep is a known risk factor for cognitive decline, Alzheimer's disease, and other chronic diseases. The product is being developed by co-founders Joshua Blair and Spencer Shumway, recent graduates of the Johns Hopkins Center for Bioengineering Innovation and Design, or CBID, part of Johns Hopkins Department of Biomedical Engineering.
Sovrinti, a patented set of home sensors that can identify subtle changes in the ability and behaviors of seniors as they go about their activities of daily living. The Sovrinti system uses the power of smart home devices and data analytics to identify specific areas requiring care-team attention before a situation becomes acute and costly. The system works out of sight and requires no interaction with technology, so the older adult can go about their daily routines as usual.
Visilant, a smartphone-based telemedicine platform that can be used by caregivers, senior living facilities, or primary care providers to screen patients for cataracts. It will also connect them to treatment facilities and manage post-op care. The project is being led by Kunal Parikh, a research associate from the Wilmer Eye Institute and CBID.
In a collaboration with WellSaid, researchers from the Whiting School of Engineering's Center for Language and Speech Processing will develop, test, and validate machine learning models that use cognitive performance tests administered by virtual voice assistant Alexa in the homes of older adults to accurately predict cognitive status.
These projects come at a time of crucial need, when the number of older adults in the U.S. is rapidly growing. The founders of JH AITC say its goal is to bring together innovators and experts to yield results unlikely to be achieved by any one group alone.
"AI-driven algorithms for elderly care will not only address the needs of the aging population but will also contribute to tackling foundational issues such as addressing data shift, bias, interpretability, and learning from small data, as well as privacy-preserving learning. The AITC effort at JHU is bi-directional in that foundational and applied research will reinforce each other," said JH AITC co-director Rama Chellappa, Bloomberg Distinguished Professor of electrical and computer engineering and biomedical engineering at Johns Hopkins Whiting School of Engineering and School of Medicine.