Jennifer Flexman, Moneta Health. Michael Busa, UMass Amherst. This project will develop AI algorithms used by Moneta™ digital therapy assistant to monitor the speech of individuals with mild cognitive impairment and early dementia during cognitive rehabilitation therapy.
Xian Du, Joohyun Chung, UMass Amherst. Shishir Prasad, BD. In this project, we will develop the approach for the continuous monitoring of long-term care (LTC) resident’s behavioral and physiological signals over extended durations using cameras and wearable sensors.
Ipsit Vahia, Rachel Sava, McLean Hospital. Joseph Chung, Rippl. The CAREALL pilot project explored the use of large language models (LLMs) to support caregivers of individuals with dementia.
What they said: Moneta Health is like physical therapy for the brain, delivered through a traditional phone call for maximum accessibility. It’s an elegantly simple sounding idea, but the Moneta team has a few important things going for them that make us particularly excited to support them. In Campbell and Flexman, they have a powerful combination of experience, combining digital health operational ability with engineering and deep knowledge of neurodegeneration. They’re also very smart in their go-to-market strategy. By showing strong early results in terms of improving cognitive function and patient quality of life (with more trials to come), they’re securing big name referring partners. They’re also tapping into known reimbursement codes, so that they can generate revenue to feed product development. And, as we have found to be so important in this market of…
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.
Honghuang Lin, UMass Chan Medical School. This pilot project explored the use of wearable accelerometers to passively monitor walking cadence as a potential early indicator of cognitive decline in older adults.
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.