UMass Amherst Researcher to Use Wearable Sleep Trackers, AI to Predict Early Signs of Alzheimer’s

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."