Publication: Physically intelligent capsule robots with embodied memory and logic in the gastrointestinal tract
| dc.contributor.coauthor | Liu, X. | |
| dc.contributor.coauthor | Ma, J. | |
| dc.contributor.coauthor | Zhao, Y. | |
| dc.contributor.coauthor | Yang, C. | |
| dc.contributor.coauthor | Chan, K. F. | |
| dc.contributor.coauthor | Chiu, P. W. Y. | |
| dc.contributor.coauthor | Shao, L. | |
| dc.contributor.coauthor | Zhang, W. | |
| dc.contributor.coauthor | Zhang, L. | |
| dc.contributor.coauthor | He, Q. | |
| dc.contributor.department | School of Medicine | |
| dc.contributor.department | Department of Mechanical Engineering | |
| dc.contributor.kuauthor | Sitti, Metin | |
| dc.contributor.kuauthor | Chen, Huyue | |
| dc.contributor.schoolcollegeinstitute | SCHOOL OF MEDICINE | |
| dc.contributor.schoolcollegeinstitute | College of Engineering | |
| dc.date.accessioned | 2026-07-22T13:08:45Z | |
| dc.date.issued | 2026 | |
| dc.description.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. | |
| dc.description.harvestedfrom | Manual | |
| dc.description.indexedby | WOS | |
| dc.description.indexedby | Scopus | |
| dc.description.indexedby | PubMed | |
| dc.description.publisherscope | International | |
| dc.description.readpublish | N/A | |
| dc.description.sponsoredbyTubitakEu | EU | |
| dc.description.sponsorship | M.S. thanks the European Research Council Advanced Grant SoMMoR project with grant no. 834531 and Max Planck Society, L.Z. thanks the Research Grants Council (RGC) project with grant no. 2122-4S03 and Strategic Topics Grant with grant no. 1/E-401/23-N, Q.H. thanks the RGC project with grant no. 24202024, K.-F.C. thanks the RGC project with grant no. 14203123, and X.L. thanks the NSFC project with grant no. 524B2073 for financial support. We thank Multi-Scale Medical Robotics Center (InnoHK, Hong Kong Science Park) for in vivo animal trials, L. Jin (CityUHK) and Z. Meng (NTU) for the guidance of metamaterial analysis, J. Liu (CityUHK) and Z. Chen (KU) for the guidance of hydrogel synthesis, H. Yang (CUHK) for the guidance of the control system, J. Guo (CUHK) for cell viability tests, and C. Portela (MIT), A. Abramson (Gatech), and M. Zhang (NUS) for their valuable insights. | |
| dc.description.version | Published Version | |
| dc.identifier.ScopusPercentile | 94 | |
| dc.identifier.ScopusQuartile | Q1 | |
| dc.identifier.WoSPercentile | 90.4 | |
| dc.identifier.WoSQuartile | Q1 | |
| dc.identifier.doi | 10.1073/pnas.2605060123 | |
| dc.identifier.eissn | 1091-6490 | |
| dc.identifier.embargo | N/A | |
| dc.identifier.grantno | 834531 | |
| dc.identifier.grantno | 2122-4S03 | |
| dc.identifier.grantno | 24202024 | |
| dc.identifier.grantno | 14203123 | |
| dc.identifier.grantno | 524B2073 | |
| dc.identifier.issn | 0027-8424 | |
| dc.identifier.issue | 28 | |
| dc.identifier.pubmed | 42418480 | |
| dc.identifier.scopus | 2-s2.0-105044658070 | |
| dc.identifier.uri | http://doi.org/10.1073/pnas.2605060123 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14288/33791 | |
| dc.identifier.volume | 123 | |
| dc.identifier.wos | 001815107800007 | |
| dc.keywords | Physical intelligence | |
| dc.keywords | Mechanical metamaterials | |
| dc.keywords | Soft materials | |
| dc.keywords | Magnetic robots | |
| dc.keywords | Biomedical engineering | |
| dc.language | eng | |
| dc.publisher | National Academy of Sciences | |
| dc.relation.affiliation | Koç University | |
| dc.relation.collection | Koç University Institutional Repository | |
| dc.relation.ispartof | Proceedings of the National Academy of Sciences | |
| dc.subject | Physical sciences | |
| dc.subject | Engineering | |
| dc.subject | Biomedical engineering | |
| dc.subject | Mechanical engineering | |
| dc.subject | Physics and astronomy | |
| dc.subject | Condensed matter physics | |
| dc.title | Physically intelligent capsule robots with embodied memory and logic in the gastrointestinal tract | |
| dc.type | Journal Article | |
| dspace.entity.type | Publication | |
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