Yayun Du of Vanderbilt University

Continuous health monitoring is moving beyond single-signal wearables toward multimodal bioelectronic systems that capture synchronized physiological, mechanical, and biochemical information in real-world settings. This talk will present recent progress in translational wearable bioelectronics for clinically integrated monitoring across cardiovascular, neurological, and sleep-related applications. I will discuss soft and wireless sensing platforms that combine modalities such as EEG, IMU, ECG, SCG, PCG, PPG sensors to enable continuous assessment of human health. Representative examples include wearable sleep staging and disorder detection, neural–motion sensing for seizure and neonatal monitoring, cuffless blood pressure monitoring, and multimodal cardiac sensing for valve disease assessment. Across these applications, the talk will highlight key engineering challenges, including low-power circuit design, robust skin or body interfaces, multimodal synchronization, signal quality assessment, and explainable AI models that transform continuous physiological signals into clinically meaningful information. The talk will also discuss how these systems can be integrated into real clinical workflows through clinician-facing software, longitudinal monitoring, and deployment in neonatal and adult cohorts. Finally, I will outline future directions toward closed-loop, adaptive bioelectronic systems that combine continuous sensing, real-time analytics, and personalized intervention for next-generation digital medicine.

Biography:

Yayun Du is an Assistant Professor of Electrical and Computer Engineering at Vanderbilt University, where she leads the SYMBIO-X Lab at the interface of multimodal wearable bioelectronics, low-power wireless systems, and edge-AI analytics. Her group develops conformal sensing platforms for continuous physiological monitoring, including EEG–IMU systems for sleep and seizure-related monitoring, ECG–SCG–PCG platforms for cardiovascular assessment, and wearable multimodal systems for ambulatory health monitoring. Her team also builds synchronized firmware, secure data pipelines, and clinician-facing tools for longitudinal and explainable monitoring.

Dr. Du’s devices have advanced to IRB-approved studies in neonatal and adult settings, with applications spanning sleep, cardiovascular, neurological, and behavioral health monitoring. Prior to Vanderbilt, she was a postdoctoral scholar in the Rogers Research Group at Northwestern University. She serves as an Associate Editor for the IEEE International Conference on Robotics and Automation (ICRA 2025), a Track Chair for the IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS 2026), and a Technical Committee member for the International Conference on Machine Learning and Human–Machine Interaction (MLHMI 2027). Her work has been published across biomedical engineering, cardiovascular digital health, soft bioelectronics, robotics, and wearable sensing, including in PNAS, JACC Advances, ACS Nano, Advanced Sensor Research, and leading IEEE venues. She was named an MIT CEE Rising Star and was awarded a Humboldt Fellowship from the Alexander von Humboldt Foundation. The mission of her lab is to translate continuous multimodal biosignal fusion into actionable, patient-centered care.

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