Evidence map›Paper›PMID 42418480›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2026

Physically intelligent capsule robots with embodied memory and logic in the gastrointestinal tract.

Huyue Chen, Xurui Liu, Jiahai Ma, Yishen Zhao, Chaoyu Yang, Kai-Fung Chan, Philip Wai Yan Chiu, Lei Shao, Wenming Zhang, Li Zhang and 2 more

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Huyue Chen *Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong 999077, China.ORCID 0000-0001-9730-9546
Xurui Liu *Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong 999077, China.ORCID 0009-0004-7139-8519
Jiahai MaDepartment of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong 999077, China.
Yishen ZhaoDepartment of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong 999077, China.
Chaoyu YangDepartment of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong 999077, China.ORCID 0000-0002-4958-0160
Kai-Fung ChanChow Yuk Ho Technology Centre for Innovative Medicine, The Chinese University of Hong Kong, Hong Kong 999077, China.
Philip Wai Yan ChiuChow Yuk Ho Technology Centre for Innovative Medicine, The Chinese University of Hong Kong, Hong Kong 999077, China.
Lei ShaoGlobal College, Shanghai Jiao Tong University, Shanghai 200240, China.
Wenming ZhangState Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240, China.ORCID 0000-0001-6743-1006
Li ZhangDepartment of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong 999077, China.ORCID 0000-0003-1152-8962
Qiguang HeDepartment of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong 999077, China.ORCID 0000-0001-7103-4273
Metin SittiSchool of Medicine and College of Engineering, Koç University, Istanbul 34450, Türkiye.

Funding

EC | European Research Council (ERC) 834531MOST | National Natural Science Foundation of China (NSFC) 524B2073Research Grants Council, University Grants Committee () 14203123Research Grants Council, University Grants Committee () 2122-4S03Research Grants Council, University Grants Committee () 24202024
6 · The paper itself

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.

Indexed as

Gastrointestinal TractRoboticsAnimalsAutonomous RobotsEquipment DesignHumansIntelligent SystemsLogicbiomedical engineeringmagnetic robotsmechanical metamaterialsphysical intelligencesoft materials

Identifiers

PMID42418480
PMCPMC13367816

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.