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A Johns Hopkins study using machine learning and mobile cognitive testing to predict post-COVID-19 cognitive decline and Alzheimer’s disease risk in older adults.
A study developing a mobile decision support tool to assist patients and caregivers during Alzheimer’s disease and related dementias (ADRD) care transitions.
A mobile software framework that uses smartphones and smartwatches as non-visual sensor hubs to transcribe daily activities for Alzheimer’s monitoring and healthy aging.
A program promoting strength training and powerlifting as a pathway to healthy aging and pain management.
ViBo Health is developing a tabletop metabolite scanner to enable real-time, non-invasive health tracking with actionable insights.
A project developing an AI assistant that uses caregiver observations to detect and communicate health changes in persons with Alzheimer’s disease and related dementias.
Development of a smart, multi-analyte, minimally invasive sensor platform for continuous health monitoring using semiconductor technology.
Development of AI-tailored non-pharmacologic interventions to improve quality of life in older adults at risk of Alzheimer’s disease and related dementias.
Blue Iris Labs is developing wearable and contactless light-exposure sensors with AI-driven analysis to support circadian health and care for people with Alzheimer’s disease and related dementias.
Johns Hopkins researchers aim to use multi-sensor wearables and machine learning to recognize activities of daily living (ADLs) and detect difficulties in performance.
Johns Hopkins researchers are developing a socially assistive robot with a companion Fitbit interaction app to support personalized, at-home physical activity for older adults.
EchoWear is developing an AI-assisted mobile cognitive screening tool with speech processing to help identify mild cognitive impairment and early dementia.
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