IAS Distinguished Lecture on Intelligent Wearables at the Edge: Unlocking Personalized and Accessible Healthcare

Abstract

The rapid convergence of intelligent wearables and edge AI is transforming how health data is captured, processed, and translated into clinical value. By enabling real‑time, energy‑efficient computation directly on the device, edge‑AI wearables open the door to more personalized, continuous, and accessible healthcare.

This lecture presents two complementary architectural strategies driving this shift in healthcare devices. First, uses emerging computing paradigms, such as in‑memory computing and open‑hardware microarchitectures to bring computation closer to the sensor, reducing latency and energy use for continuous monitoring and timely patient‑specific insights. Second, adopts full‑system co‑design to build heterogeneous medical System‑on‑Chip (SoC) platforms tailored to the patient and the monitored bio‑signals. These SoC architectures, inspired by the specialization found in the human brain, combine analog and digital components with biomedical accelerators to deliver efficient, robust performance for signal processing, sensor fusion, and advanced on‑device deep learning.

The lecture concludes by demonstrating how combining these two approaches within new open‑hardware SoC frameworks enables rapid development of medical‑grade wearables capable of complex medical analysis entirely at the edge, while supporting enhanced privacy‑preserving concepts (e.g., federated learning) in the context of continuous monitoring to chronic disease management across cardiovascular, neurological, and musculoskeletal healthcare.


About the Speaker

Prof. David ATIENZA ALONSO is a Professor of Electrical and Computer Engineering at École Polytechnique Fédérale de Lausanne (EPFL), Switzerland. He leads the Embedded Systems Laboratory (ESL) and serves as Associate Vice President of Research Centers and Technology Platforms for the 2024–2028 term. His research focuses on system-level design methodologies for multi-processor system-on-chip (MPSoC) systems targeting low-power, energy-efficient computing. Prof. Atienza Alonso recently contributes to new architectures for MPSoCs targeting edge AI systems, as well as HW/SW co-design and AI-based multi-level optimization for sustainable computing in the Internet of Things (IoT) context.

Prof. Atienza Alonso has co-authored more than 450 papers, one book, and holds 14 patents in these areas. His work has been recognized with numerous awards, including the IEEE/ACM HW/SW Co-Design Conference (CODES-ISSS) 2024 Test-of-Time Award for the most influential paper in the last 15 years, the ICCAD 10-Year Retrospective Most Influential Paper Award (2020), the Design Automation Conference (DAC) Under-40 Innovators Award (2018), and IEEE CEDA and ACM SIGDA Early Career Awards on EDA tools and systems research. He has served as Editor-in-Chief of IEEE Transactions on CAD (T-CAD) and ACM Computing Surveys. Prof. Atienza Alonso is a Fellow of IEEE and a Fellow of ACM; he chaired the European Design Automation Association (EDAA) from 2022 to 2024 and was the President of IEEE CEDA from 2017 to 2018. He also founded two EPFL spin-offs commercializing medical wearables: SmartCardia, focused on cardiovascular wearables for home-based monitoring, and Sensemodi, which provides personalized monitoring using multi-sensing wearable technologies for knee chondropathy and respiratory diseases monitoring. 


For Attendees' Attention

Seating is on a first come, first served basis.