Evidence map›Paper›PMID 41320722›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Biohybrid Tendons Enhance the Power-to-Weight Ratio and Modularity of Muscle-Powered Robots.

Nicolas Castro, Ronald Heisser, Maheera Bawa, Bastien Aymon, Sarah Wu, Annika Marschner, Sonika Kohli, Angel Bu, Laura Rosado, Martin Culpepper and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Nicolas CastroDepartment of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02472, USA.
Ronald HeisserDepartment of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02472, USA.
Maheera BawaDepartment of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02472, USA.
Bastien AymonDepartment of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02472, USA.
Sarah WuDepartment of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02472, USA.
Annika MarschnerDepartment of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02472, USA.
Sonika KohliDepartment of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02472, USA.
Angel BuDepartment of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02472, USA.
Laura RosadoDepartment of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02472, USA.
Martin CulpepperDepartment of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02472, USA.
Xuanhe ZhaoDepartment of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02472, USA.
Ritu RamanDepartment of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02472, USA.ORCID https://orcid.org/0000-0001-8657-9815

Funding

Army Research Office W911NF-22-1-0126P00003National Science Foundation
6 · The paper itself

Abstract

Biohybrid robots powered by tissue engineered skeletal muscle have historically relied on architectures in which muscle actuators are placed directly on skeletons, thus limiting the accessible design space for such machines. By contrast, native musculoskeletal architecture relies on tendons to bridge the interface between muscles and skeletons, enabling precise, space-efficient, and energy-efficient force transmission. In this study, a mathematical model of the muscle-tendon-skeleton interface is used to design a biohybrid muscle-tendon unit composed of tissue engineered muscle coupled to adhesive tough hydrogel tendons. It is demonstrated that tuning tendon stiffness and pre-tension optimizes actuator performance, and tuning skeleton stiffness modulates force transmission from muscles to skeletons, with fatigue characteristics measured over > 7000 cycles. Furthermore, an ≈11X improvement in power-to-weight ratio of muscle-tendon units is demonstrated compared to previous demonstrations of robots powered by muscles alone. This work validates a robust approach for designing, manufacturing, and deploying muscle-tendon actuators that promises to enhance the modularity and efficiency of biohybrid robots.

Indexed as

Muscle, SkeletalRoboticsTendonsTissue EngineeringAnimalsBiomechanical PhenomenaEquipment DesignHumansbioactuatorbiohybrid roboticsskeletal musclesoft roboticstissue engineering

Identifiers

PMID41320722
PMCPMC13042981

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.