Evidence map›Paper›PMID 38721040›Full record

ArticleCyborg and bionic systems (Washington, D.C.)2024

Contractile and Tensile Measurement of Molecular Artificial Muscles for Biohybrid Robotics.

Yingzhe Wang, Kaoru Uesugi, Takahiro Nitta, Yuichi Hiratsuka, Keisuke Morishima

Abstract read
In one paragraph

Article in Cyborg and bionic systems (Washington, D.C.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
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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

5 authors.

Yingzhe WangDepartment of Mechanical Engineering, Osaka University, Osaka 565-0871, Japan.ORCID https://orcid.org/0000-0002-8866-8851
Kaoru UesugiDepartment of Mechanical Systems Engineering, Ibaraki University, Ibaraki 316-8511, Japan.
Takahiro NittaApplied Physics Course/Department of Mathematical and Design Engineering, Gifu University, Gifu 501-1193, Japan.ORCID https://orcid.org/0000-0001-7667-080X
Yuichi HiratsukaSchool of Materials Science, Japan Advanced Institute of Science and Technology (JAIST), Ishikawa 923-1292, Japan.ORCID https://orcid.org/0000-0002-0237-081X
Keisuke MorishimaDepartment of Mechanical Engineering, Osaka University, Osaka 565-0871, Japan.ORCID https://orcid.org/0000-0003-1146-3900

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A printable artificial muscle assembled from biomolecular motors, which we have recently developed, showed great potential in overcoming the design limitations of conventional biohybrid robots as a new bio-actuator. Characterizing its contractility for extending its applicability is important. However, conventional measurement methods are composed of complex operations with poor reproducibility, flexibility, and real-time responsiveness. This study presents a new method for measuring the contractile force generated by artificial muscles. A measurement system was constructed, wherein artificial muscles were patterned by UV laser scanning in an oil-sealed microchamber, and the contractile force was measured in real time using a microforce sensor extended by a 3D-printed microcantilever. The measurement accuracy of the sensor was ensured through calibration and correction. For demonstration purposes, a series of contractile measurements were carried out using the proposed system. The relationship between contractile force and the dimensions of the activation space of the artificial muscles, as well as the tensile properties of the contracted muscle chain were evaluated. The results will help characterize the contractile properties of the artificial muscle and lay the foundations for its further application in biohybrid robotics.

Identifiers

PMID38721040
PMCPMC11077706

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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.