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…
Many embodiments of the invention include systems and methods for evaluating motion from a video, the method includes identifying a target individual in a set of one or more frames in a video, analyzing the set of frames to determine a set of pose parameters, generating a 3D body mesh based on the pose parameters, identifying joint positions for the target individual in the set of frames based on the generated 3D body mesh, predicting a motion evaluation score based on the identified join positions, providing an output based on the motion evaluation score. U.S. Patent 11,918,370 Issued March 5, 2024
PCT filed for VibroBP: U.S. Provisional Application No. 63/385,383 - Colin Barry et al. - Mobile Device Based Oscillometric Blood Pressure Measurement [SD2023-139-1; 009062-8487.WO00]
The base gait forecasting and estimation transformer model that is leveraged for this pilot is available open-source. Source: https://github.com/markendo/GaitForeMer