Wearable Heart Failure Socks for Exacerbation and Treatment Monitoring

Pamela Z. Cacchione, University of Pennsylvania. Li Shen, University of Pennsylvania. Heart Failure Monitoring Socks will be used in hospitalized persons with heart failure to gather data on heart failure exacerbations and responses to treatment. We will use this data to develop predictive models for edema and fatigue due to heart failure.

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AI-Driven Earpiece Wearable to Enhance Symptom Management, Self-Care, and Caregiver Support in AD/ADRD Patients

Selina Zhu, Lumia Health. Paolo Bonato, Spaulding Rehabilitation Hospital This pilot will test the Lumia ear wearable in people with Alzheimer’s disease and related dementias (AD/ADRD), allowing users to track blood flow to the head and report symptoms through a voice-controlled AI assistant. The study will focus on usability and adapting Lumia’s technology for older adults with cognitive impairments.

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Measuring Heart Rate using Biomagnetism-based Wearable Devices

Longfei Shangguan, University of Pittsburgh This project will aim to develop an innovative wearable system that leverages biomagnetism to deliver more accurate heart rate and respiration monitoring across diverse skin tones.

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Accelerating Balance Recovery Using Adaptive EVS Therapy

John Ralston, Neursantys Inc. VP Nguyen, UMass Amherst This project will develop ML-driven methods to adapt EVS stimulus parameters to each patient’s unique sensory and motor impairment profile to increase the effectiveness of NEURVESTA’s current treatment protocol.

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An academic-industrial partnership for AI-based sleep staging in the elderly using an EEG headband and a smartwatch

Joyita Dutta, UMass Amherst. This project will develop AI techniques for at-home sleep staging in seniors using multimodal data from EEG headband and smartwatch devices.

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AI-Supported In-Home Brain Assessments for Older Adults and Persons with Alzheimer’s Disease

Quan Zhang, Massachusetts General Hospital. This project will create an adapted version of NINscan, a Near-Infrared Neuromonitoring Device, with the goal of enabling older adults and AD patients to collect high quality brain and physiological data at home.

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Preventing falls before they occur: validating a wearable sensor for Orthostatic Vital Signs

Amar Basu, Wayne State University, Michael Busa, UMass Amherst. This project will evaluate TRACE, a novel wearable sensor for monitoring orthostatic vital signs continuously at home, whenever an individual stands up.

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