Evidence map›Paper›PMID 39349426›Full record

ArticleNature communications2024

A fabrication strategy for millimeter-scale, self-sensing soft-rigid hybrid robots.

Hun Chan Lee, Nash Elder, Matthew Leal, Sarah Stantial, Elenis Vergara Martinez, Sneha Jos, Hyunje Cho, Sheila Russo

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Soft robotic devices for cardiovascular medicine.Nature reviews. Cardiology · 2026
    Review
  2. Article
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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

8 authors.

Hun Chan LeeDepartment of Mechanical Engineering, Boston University, Boston, MA, USA.ORCID http://orcid.org/0000-0003-3515-6884
Nash ElderDepartment of Mechanical Engineering, Boston University, Boston, MA, USA.ORCID http://orcid.org/0009-0004-9075-7046
Matthew LealDepartment of Biomedical Engineering, Boston University, Boston, MA, USA.ORCID http://orcid.org/0009-0008-2592-3932
Sarah StantialDepartment of Mechanical Engineering, Boston University, Boston, MA, USA.
Elenis Vergara MartinezDepartment of Biomedical Engineering, Florida International University, Miami, FL, USA.ORCID http://orcid.org/0009-0007-3260-8482
Sneha JosDepartment of Physics, Boston University, Boston, MA, USA.ORCID http://orcid.org/0009-0006-1170-7695
Hyunje ChoDepartment of Mechanical Engineering, Boston University, Boston, MA, USA.ORCID http://orcid.org/0009-0001-6873-783X
Sheila RussoDepartment of Mechanical Engineering, Boston University, Boston, MA, USA. russos@bu.edu.ORCID http://orcid.org/0000-0002-5490-3155

Funding

Project-005UL1TR001430 · NCATS · BOSTON UNIVERSITY MEDICAL CAMPUS · PI BAIR-MERRITT, MEGAN H, CENTER, DAVID M. · 2015 to 2024
$52.3M
NCATS NIH HHS UL1 TR001430U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences (NCATS) 1UL1TR001430
6 · The paper itself

Abstract

Soft robots typically involve manual assembly of core hardware components like actuators, sensors, and controllers. This increases fabrication time and reduces consistency, especially in small-scale soft robots. We present a scalable monolithic fabrication method for millimeter-scale soft-rigid hybrid robots, simplifying the integration of core hardware components. Actuation is provided by soft-foldable polytetrafluoroethylene film-based actuators powered by ionic fluid injection. The desired motion is encoded by integrating a mechanical controller, comprised of rigid-flexible materials. The robot's motion can be self-sensed using an ionic resistive sensor by detecting electrical resistance changes across its body. Our approach is demonstrated by fabricating three distinct soft-rigid hybrid robotic modules, each with unique degrees of freedom: translational, bending, and roto-translational motions. These modules connect to form a soft-rigid hybrid continuum robot with real-time shape-sensing capabilities. We showcase the robot's capabilities by performing object pick-and-place, needle steering and tissue puncturing, and optical fiber steering tasks.

Identifiers

PMID39349426
PMCPMC11442515

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.