News Release

UMass Amherst researcher to use wearable sleep trackers, AI to predict early signs of Alzheimer’s

The work, supported by a $3.9 million grant from the National Institutes of Health, could serve as an ‘early warning system’ for flagging at-risk individuals

Grant and Award Announcement

University of Massachusetts Amherst

The National Institutes of Health has awarded Joyita Dutta, professor of biomedical engineering at the University of Massachusetts Amherst, $3.9 million over five years to study if wearable sleep trackers can predict blood biomarkers of Alzheimer’s disease in at-risk individuals.  

 

Sleep disruption is one of the hallmarks of Alzheimer’s disease, even before cognitive symptoms manifest. However, gold-standard sleep assessments are expensive and usually only provide data from a single night. With the goal of expanding early Alzheimer’s diagnosis, Dutta will assess if unobtrusive sleep trackers can log sleep patterns that correlate with future cognitive decline, as indicated by blood biomarkers. 

 

Although she doesn’t see wearable devices as a substitute for clinical approaches to detect Alzheimer’s disease or cognitive change, they could be a tool for flagging at-risk individuals and serve as an early warning system. “Many people already wear smartwatches to sleep these days,” she says. “Imagine receiving an alert from your smartwatch advising you to see a neurologist. That could be the direction we are headed.” 

 

Her study will evaluate the sleep patterns of people with a genetic predisposition to developing Alzheimer’s disease, but no observable signs of cognitive impairment. Instead of completing a one-night sleep study, the participants also will wear three types of sleep trackers for a week: the Apple Watch, the Oura Ring and CGX Patch, a wearable electroencephalogram (EEG) that is essentially a sticky forehead patch with metal electrodes that measure brain activity.  

 

The data from these wearables will be compared to new blood tests measuring amyloid and tau proteins, key early biomarkers of Alzheimer’s disease. This assessment will be repeated after two years to detect possible changes. 

 

 “Our previous work includes developing AI-based predictive models connecting sleep patterns to cognitive impairment. This grant allows us to take that research to the next level,” says Dutta. “The project will enable the integration of a wealth of new data — genetic information, wearables-derived metrics, and blood-based biomarkers to create a more comprehensive picture of the sleep-dementia axis.” 

 

Although blood tests for Alzheimer’s disease are becoming increasingly accurate, identifying who should undergo these tests and be referred to a neurologist remains a challenge. Dutta notes that “Wearables are here to stay. They could fill this gap in diagnostics enabling early detection of Alzheimer’s disease.” 


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