Pilot Outcomes

Poster Presentation: Military Health System Research Symposium (MHSRS) 2024

Title: Enhancing Mental and Cognitive Fitness Monitoring via Vocal Biomarkers: Applications for Military Personnel Authors: Erik Larsen, Olivia Murton, Xinyu Song, Dale Joachim, Lindsey Venesky, Sam Murdock, Bonnie Wong, Brad Dickerson Abstract:  Maintaining the mental and cognitive fitness of military personnel is critical to ensuring peak operational readiness. Traditional methods like self-reported questionnaires and clinical interviews are often hindered by subjectivity, time constraints, and the stigma surrounding mental health. Vocal biomarkers offer a breakthrough, enabling an unobtrusive, secure, and real-time assessment of mental and cognitive states using readily available smart devices.  Our research validates the effectiveness of vocal biomarkers in remotely monitoring mental and cognitive shifts, including those associated with depression, anxiety, PTSD, and cognitive impairment, as well as real-time cognitive effort. This technology, deployable across consumer electronics and wearables without the need for network…

Continue ReadingPoster Presentation: Military Health System Research Symposium (MHSRS) 2024

Grant Funding: R21 AG088872

Title: Characterizing autonomic impairments in Frontotemporal Dementia This R21 builds upon the tech ready cohort that was established by the pilot project funding. Public Health Relevance Statement: This proposal will test the accuracy and reliability of autonomic measurements in bvFTD patients. Measurements will be collected both with established equipment and via at-home devices to assess the validity of the latter. Finally, autonomic measurements will be correlated to socioemotional dysfunction in patients. Source: R21 AG088872 (NIH RePORTER)

Continue ReadingGrant Funding: R21 AG088872

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

NIH Research Highlight: 2024 NIH Alzheimer’s and Related Dementias Research Progress Report – Understanding Risk and Protective Factors for Dementia | Spotlight: Blood pressure and dementia risk

The pilot project led by Ed Wang was spotlighted in the 2024 NIH Alzheimer's and Related Dementias annual research project report in the section focused on understanding the associated risk dementia factor of uncontrolled high blood pressure. Results from this early pilot study demonstrate the potential of smartphone-based blood pressure devices, which in the near future could help improve the accessibility of long-term blood pressure monitoring. This improved improved access to low-cost blood pressure monitoring has the potential to reduce a major contributing factor to dementia risk. Source: 2024 NIH Alzheimer's and Related Dementias Research Progress Report: Advances and Achievements

Continue ReadingNIH Research Highlight: 2024 NIH Alzheimer’s and Related Dementias Research Progress Report – Understanding Risk and Protective Factors for Dementia | Spotlight: Blood pressure and dementia risk

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