Physically intelligent capsule robots with embodied memory and logic in the gastrointestinal tract
Abstract
Miniaturized medical robots offer a promising solution for minimally invasive measurements and interventions in the gastrointestinal (GI) tract. Clinical assessment of GI disorders is commonly guided by threshold-based physiological indicators, including pressure, temperature, and pH, which motivate event-triggered strategies for personalized medicine. However, identifying homeostatic dysregulation and enabling in-situ therapy remains challenging, because ingestible robotic systems must tightly integrate sensing, decision-making, and actuation under severe constraints of size, power, and biosafety. Inspired by the autonomy of microorganisms that operate without neural processing, this work introduces physically intelligent capsule robots (PI Capbots) that enable homeostatic monitoring and targeted delivery within the GI tract, without relying on centralized electronic control. Through embodied stimuli-responsive memory and logic, PI Capbots effectively distill rich, detailed, and redundant physiological information into a small set of decoupled and event-triggered outputs suitable for operations in in vivo environments. In each PI Capbot, multistable metamaterials encode intraluminal pressure as mechanical memory, programmable hydrogels implement orthogonal sensing and logic operations, and helical fibers enable multimodal locomotion. Ex vivo and in vivo studies in large animal models demonstrate the efficacy, robustness, and reproducibility of PI Capbots, highlighting its potential for their translational medical applications.
Article Details
Journal Info
Proceedings of the National Academy of Sciences
National Academy of Sciences
Authors (12)
Huyue Chen
Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong
Xurui Liu
Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong
Jiahai Ma
Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong
Yishen Zhao
Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong
Chaoyu Yang
Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong
Kai-Fung Chan
Chow Yuk Ho Technology Centre for Innovative Medicine, The Chinese University of Hong Kong
Philip Wai Yan Chiu
Chow Yuk Ho Technology Centre for Innovative Medicine, The Chinese University of Hong Kong
Lei Shao
Global College, Shanghai Jiao Tong University
Wenming Zhang
State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University
Li Zhang
Qiguang He
Department Mechanical and Automation Engineering
Metin Sitti