Register – Intelligent Mobile Systems for an Aging World, Justin Chan (September 23, 2025 @4pm ET)

Zoom Registration: https://umass-amherst.zoom.us/meeting/register/Hw27HSCgThCh41eN466wiQ Abstract: By 2050, older adults will make up about 22% of the global population, driving an urgent need for accessible and reliable health technologies. In this talk, I will present our work on intelligent mobile systems designed for older adults. The first enables low-cost health screening using everyday earphones and wireless earbuds. The second is an ambient sensing system that uses smart devices to detect emergent, life-threatening events such as cardiac arrest. The third leverages compact AI-enabled radios for cardiovascular monitoring, including blood pressure. Through these examples, I will show how computational and sensing techniques that generalize across hardware and operate in real-world environments can address pressing societal challenges. Biography: Justin Chan, PhD, Assistant Professor at Carnegie Mellon University Justin is an assistant professor in CS and ECE at Carnegie Mellon University,…

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Publication: Developing an Equitable Machine Learning-Based Music Intervention for Older Adults At Risk for Alzheimer Disease: Protocol for Algorithm Development and Validation

Authors: Chelsea S Brown, Luna Dziewietin, Virginia Partridge, Jennifer Rae Myers Abstract Background: Given the high prevalence and cost of Alzheimer disease (AD), it is crucial to develop equitable interventions to address lifestyle factors associated with AD incidence (eg, depression). While lifestyle interventions show promise for reducing cognitive decline, culturally sensitive interventions are needed to ensure acceptability and engagement. Given the increased risk for AD and health care barriers among rural-residing older adults, tailoring interventions to align with rural culture and distinct needs is important to improve accessibility and adherence. Objective: This protocol aims to develop an intelligent recommendation system capable of identifying the optimal therapeutic music components to elicit engagement and resonate with diverse rural-residing older adults at risk for AD. Aim 1 is to develop culturally inclusive user personas for rural-residing older adults to understand…

Continue ReadingPublication: Developing an Equitable Machine Learning-Based Music Intervention for Older Adults At Risk for Alzheimer Disease: Protocol for Algorithm Development and Validation

Publication: Passive Measures of Physical Activity and Cadence as Early Indicators of Cognitive Impairment: Observational Study

Authors: Huitong Ding, Stefaniya Brown, David R Paquette, Taylor A Orwig, Nicole Spartano, Honghuang Lin Abstract Background: Emerging research shows regular physical activity reduces cognitive decline risk, but most studies rely on self-reported measures, which are limited by recall bias, subjectivity, and a lack of continuous monitoring capability. Objective: This study aimed to explore passive physical activity measures as early indicators of cognitive impairment by examining their association with cognitive impairment incidence and neuropsychological (NP) test performance. Methods: We included participants from the Framingham Heart Study (FHS), a community-based cohort with longitudinal cognitive impairment surveillance. Participants wore an Actical accelerometer for at least 3 days, excluding bathing. Thirty physical activity measures were grouped into intensity-specific durations, step and cadence summaries, and peak cadence. Cox proportional hazard models were applied to assess their associations with incident…

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Oral Presentation: Alzheimer’s Association International Conference 2025 – Technology And Dementia Preconference

Jennifer Flexman presented "Improving Access to Dementia Care though AI-Powered Cognitive Rehabilitation Therapy" at the Technology And Dementia Preconference during Session 5: Data Blitz.

Continue ReadingOral Presentation: Alzheimer’s Association International Conference 2025 – Technology And Dementia Preconference

Award: Jiani Zeng, co-founder and CPO of Butlr wins 2025 McKnight’s Women of Distinction award in the Commercial Excellence category

The technology designed by Zeng has been key in improving senior living and care operations, helping staff members effectively monitor residents through motion detection, enabling them to respond quickly to acute health risks without compromising resident privacy.Forster Stubbs, McKnight Senior Living The work of Jiani Zeng, a Chinese designer, researcher, and co-founder and chief product officer of Butlr Technologies, often takes place in the background, but the results always end up at the forefront. Thanks in part to her efforts, Butlr is the first company to fuse artificial intelligence and body heat sensing technology to provide insights into how humans use indoor space for living and working while ensuring anonymity. This technology has significant applications in the senior living and care sector and helped earn Zeng a 2025 McKnight’s Women of Distinction award in the Commercial Excellence…

Continue ReadingAward: Jiani Zeng, co-founder and CPO of Butlr wins 2025 McKnight’s Women of Distinction award in the Commercial Excellence category