Authors
Fuying Dong, Chi Han, Pengchong Xu, Jasleen Chhatwal, Xinnian Jiang, Tengteng Wang, Abigail Hsu, Minzhu Baek, Di Wu, Rui Li, Yuanwen Jiang, Bozhi Tian, Jason Y Fang, Simiao Niu
Published in
Science advances. Volume 12. Issue 34. Pages eaeh9625. Aug 21, 2026. Epub Aug 19, 2026.
Abstract
Smart digital health has reshaped patient monitoring, but it faces a fundamental trade-off between device intelligence and continuous, energy-efficient monitoring. Inspired by self-sustaining intelligent biospecies, we develop a biomimetic, battery-free, and high-precision edge-AI system through a harvested-energy-constrained holistic co-design that couples ultralow-power edge-AI-empowered sensor hardware with biomechanical energy harvesting and cold-start power management. Our edge-AI-empowered motion sensor performs instantaneous, context-aware on-device inference and timely result updating from raw sensor data while consuming only 86 μW. A high-output energy harvester and tailored high-efficiency power management circuitry sustain energy levels exceeding system requirements, eliminating downtime associated with charging and enabling true 24/7, hassle-free monitoring. This breakthrough establishes a paradigm for system-level, edge-AI-empowered, and self-sustaining sensing, demonstrating that intelligence and energy autonomy can coexist within a single wearable platform and pointing to next-generation always-on, personalized digital health systems.
PMID:
42616884
Bibliographic data and abstract were imported from PubMed on 20 Aug 2026.
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