Events

Publication: AI-Driven Sleep Staging Using Instantaneous Heart Rate and Accelerometry: Insights from an Apple Watch Study

Authors: Tzu-An Song, Yubo Zhang, Ziyuan Zhou, Luke Hou, Masoud Malekzadeh, Aida Behzad, Joyita Dutta Abstract Polysomnography, the gold standard for sleep evaluations, involves complex setup and data acquisition protocols and requires manual scoring of sleep data. Smartwatches and other multi-sensor consumer wearable devices with automated sleep staging capabilities offer a promising and scalable alternative for routine and long-term sleep evaluations in individuals. We conducted a multi-night study using a smartwatch for sleep assessment and created an AI-driven automated sleep staging framework based on instantaneous heart rate (IHR) and accelerometry data using sleep stage labels based on electroencephalography (EEG) as the reference. 47 healthy adults were recruited to record their sleep for up to seven consecutive nights using an Apple Watch Series 6 and a Dreem 2 Headband. Our sleep staging framework relies on a…

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Register – No One Left Behind: Building Low-Cost Wearables for Low-Income Communities, Longfei Shangguan (October 28, 2025 @4pm ET)

Zoom Registration: https://umass-amherst.zoom.us/meeting/register/4y4Tc9JsS6WTXxrNzTMgkA Abstract: Wearable devices such as Apple Watch and Fitbit wristband allow users to track their health statistics around the clock. They have become increasingly popular over the past few years. However, in the context of low-income areas of United States, these wearable devices are still pricey and thus constitute a critical bottleneck in their adoption. In this talk, I will present our past and ongoing works on repurposing electronic wastes, particularly everyday earphones into health trackers - from heart rate monitoring, heart sound recovery, all the way down to pulse wave velocity estimation in home settings. I will also discuss the potential of these technologies for filling the gap of remote health care. I believe this research creates a holistic approach toward recycling and repurposing electronic waste while fostering a sustainable and…

Continue ReadingRegister – No One Left Behind: Building Low-Cost Wearables for Low-Income Communities, Longfei Shangguan (October 28, 2025 @4pm ET)

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

https://www.youtube.com/watch?v=EUH-9jR48Fo 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, where he…

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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

2025 a2 National Symposium Plenary Talk: Griffin Weber, MD, PhD — Connecting Health Organizations with Federated Research Networks

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The integration and analysis of electronic health record (EHR) data across institutions present both significant challenges and transformative opportunities for biomedical research. This talk outlines the development and application of federated data networks such as I2B2 and SHRINE, which enable real-time, privacy-preserving queries across distributed EHR systems. These platforms support large-scale cohort discovery and have been instrumental in initiatives like the EnACT network and the COVID-19-focused 4CE consortium. In contrast, centralized repositories like the NIH’s N3C and Epic’s Cosmos database offer comprehensive datasets conducive to machine learning but may obscure site-specific variability. 

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2025 a2 National Symposium Plenary Talk: Jordan Smoller, MD — An Introduction to the All of Us Research Program

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The All of Us Research Program, a flagship initiative of the NIH, aims to build one of the most comprehensive and diverse biomedical data resources in the world by enrolling over one million participants across the United States. Dr. Jordan Smoller, a lead investigator in the program, outlines its structure, scope, and transformative potential for advancing precision medicine. With over 850,000 participants enrolled and more than 630,000 contributing data, the program integrates electronic health records (EHRs), genomic data, physical measurements, surveys, and wearable device data. 

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2025 a2 National Symposium Plenary Talk: Marzyeh Ghassemi, PhD– The Pulse of Ethical Machine Learning in Health

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As machine learning (ML) becomes increasingly integrated into healthcare, ensuring ethical, fair, and robust deployment is critical. Dr. Marzyeh Ghassemi and the Healthy ML Lab at MIT investigate the challenges and opportunities of applying ML in clinical settings, with a focus on fairness, privacy, and real-world impact. Through case studies in medical imaging and clinical prediction, her work highlights how models trained on large datasets can exhibit significant disparities in performance across demographic subgroups, including age, race, gender, and insurance status.

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