I-Corps: Digital Biomarkers Combined with Wearable Devices to Monitor Alzheimer’s Disease and other Neurological Disorders

The broader impact/commercial potential of this I-Corps project is the development of a cloud-based, predictive analytics platform to identify, develop, and validate digital biomarkers that identify early signs of neurodegeneration and other significant health-related concerns related to aging. Existing methods of collecting longitudinal data from aging populations for clinical and nonclinical research are slow, expensive, labor-intensive and often introduce flawed data.

This project may improve research with qualitative and quantitative behavioral and biophysical information using passive and unobtrusive patient-generated data aggregated in real-life environments using smartwatches. At scale, this platform may be used to build models that predict disease onset in at-risk populations and help millions of individuals around the world identify means to delay the onset or slow the progression of Alzheimer’s disease and related dementias.

In addition, this platform may enable pharmaceutical companies with licensed access to data to conduct focused clinical trials in aging populations. The proposed technology may improve health-related applications offered by wearable/smartwatch manufacturers, and may provide health-concerned individuals with personalized low-cost behavior modification intervention recommendations in order to delay, prevent, or slow the progression of neurogenerative diseases and other health issues.

This I-Corps project is based on the development of analytical models deployable within the cloud to identify, measure, and predict those behavioral and clinical features impacting people at high-risk for Alzheimer’s Disease and related dementias. The proposed technology is an end-to-end patient monitoring solution that benefits patients, caregivers and medical researchers by combining data from widely available consumer smartwatches with a cloud-based analytics and artificial intelligence platform to deliver improved health and behavior information.

This proposed software solution advances high-frequency data aggregation to a centralized cloud-based platform where it is possible to generate insights and identify, develop, and clinically validate digital biomarkers for Alzheimer’s disease, dementias, and other potential illnesses and comorbidities in aging populations. The development of this prototype artificial intelligence-driven platform may provide a solution to passively and unobtrusively capture patient-generated data beyond conventional clinical trials, in real-life settings, and advance capabilities to analyze digital health information from broad demographic populations.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.