Year 3 Pilots

Grant Funding: NIA SBIR Phase I (R43AG090129)

Title: AVA AI Video-Based Mobile Application for Reliable, Accessible, and Low-Cost Fall Risk Assessments of Older Adults Public Health Relevance Statement: This project presents AVA, a video-based mobile app for at-home fall risk assessment of older adults, only using a smartphone to enable a much higher access, low-cost solution with full privacy protection. AVA empowers caregivers to assess the gait, balance, and strength of their older adults independently without the direct supervision of healthcare professionals. The Phase I study focuses on validating AVA's AI-based assessment technology and its usability in diverse home and independent living settings which can lead to revolutionizing current fall risk assessment practices. Source: R43AG090129 (NIH RePORTER)

Continue ReadingGrant Funding: NIA SBIR Phase I (R43AG090129)

Grant Funding: 2024 Innovation Award Competition: Center for Advancing Point of Care Technologies in Heart, Lung, Blood and Sleep Disorders (CAPCaT)

Billion Labs Inc is a recipient of the 2024 CAPCaT Innovation Award to further advance the design of the user interface for their VibroBP smartphone app for measuring blood pressure. The award covers $100,000 in direct costs for the 12-month long project. The CAPCaT is a partnership between UMass Chan Medical School and UMass Lowell. The center's mission is to support development and testing of promising, point-of-care technologies that can be rapidly deployed to enhance the diagnosis, monitoring, management and treatment of heart, lung, blood and sleep disorders. The center has an additional interest in projects that incorporate complementary and integrative health approaches. CAPCaT is supported by the National Heart, Lung, and Blood Institute via U54HL143541. Source: https://www.universityofcalifornia.edu/news/blood-pressure-readings-your-fingertips (Press Release)

Continue ReadingGrant Funding: 2024 Innovation Award Competition: Center for Advancing Point of Care Technologies in Heart, Lung, Blood and Sleep Disorders (CAPCaT)

Publication: Data-driven discovery of movement-linked heterogeneity in neurodegenerative diseases. Nature Machine Intelligence

Authors: Mark Endo, Favour Nerrise, Qingyu Zhao, Edith V Sullivan, Li Fei-Fei, Victor W Henderson, Kilian M Pohl, Kathleen L Poston, Ehsan Adeli Abstract Neurodegenerative diseases manifest different motor and cognitive signs and symptoms that are highly heterogeneous. Parsing these heterogeneities may lead to an improved understanding of underlying disease mechanisms; however current methods are dependent on clinical assessments and somewhat arbitrary choice of behavioral tests. Herein, we present a data-driven subtyping approach using video-captured human motion and brain functional connectivity (FC) from resting-state (rs)-fMRI. We applied our framework to a cohort of individuals at different stages of Parkinson's disease (PD). The process mapped the data to low-dimensional measures by projecting them onto a canonical correlation space that identified three PD subtypes: Subtype I was characterized by motor difficulties and poor visuospatial abilities; Subtype II exhibited difficulties in non-motor…

Continue ReadingPublication: Data-driven discovery of movement-linked heterogeneity in neurodegenerative diseases. Nature Machine Intelligence

Oral Presentation: Alzheimer’s Association International Conference

Title: Automated Physical Performance Battery as a Digital Marker for Alzheimer's Disease and Mild Cognitive ImpairmentPresenter: Ehsan Adeli (PI) Abstract: Historically, screening for incidence of AD-related MCI or conversion from MCI to AD dementia has relied on cognitive, activities of daily living, and brain imaging measures. Limitations of this diagnostic approach include dependency on education and language, time-consuming and costly measures, and long-term monitoring. Emerging studies suggest that non-tremor motor dysfunction in dementias is known to be highly associated with AD biomarkers, with signs of cognitive decline visible in gait and hand movement at various stages of the illness. With the evidence that gait and physical disturbances are early predictors of cognitive impairment and that their trajectories could readily be tracked, we utilize recent advances in computer vision (CV) to quantify mobility in a data-driven…

Continue ReadingOral Presentation: Alzheimer’s Association International Conference

Oral Presentation: Alzheimer’s Association International Conference 2024

Dr. Jennifer Myers presented "An Equitable ML-based Music Intervention for At-risk Older Adults," at the Alzheimer’s Association International Conference (Preconference) in Philadelphia, PA. The presentation was part of the Introduction To The Artificial Intelligence And Technology Collaboratories (AITC) For Aging Research Program Pilot Project Showcase

Continue ReadingOral Presentation: Alzheimer’s Association International Conference 2024