Evidence map›Paper›PMID 32864173›Full record

ReviewBiomedical engineering letters2020

Biomedical soft robots: current status and perspective.

T Ashuri, A Armani, R Jalilzadeh Hamidi, T Reasnor, S Ahmadi, K Iqbal

Abstract readReview
In one paragraph

Review in Biomedical engineering letters, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Magnetic Fluid-Driven Vine Robots for Minimally Invasive Tissue Biopsy Sampling.Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) · 2025
    Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Toward Development of Novel Remote Ultrasound Robotic System Using Soft Robotics Technology.Journal of engineering and science in medical diagnostics and therapy · 2024
    Article
  15. Review
  16. Review
  17. A review on self-healing featured soft robotics.Frontiers in robotics and AI · 2023
    Review
  18. Article
  19. Article
  20. 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

6 authors.

T AshuriDepartment of Mechanical Engineering, Arkansas Tech University, 1811 N Boulder Ave, Russellville, AR 72801 USA.ORCID 0000-0003-1536-933X
A ArmaniDepartment of Mechanical Engineering, San Jose State University, 1 Washington Square, San Jose, CA 95112 USA.
R Jalilzadeh HamidiDepartment of Electrical Engineering, Arkansas Tech University, 1811 N Boulder Ave, Russellville, AR 72801 USA.
T ReasnorDepartment of Mechanical Engineering, Arkansas Tech University, 1811 N Boulder Ave, Russellville, AR 72801 USA.
S AhmadiDepartment of Orthopedic Surgery, University of Arkansas for Medical Sciences, 10815 Colonel Glenn Rd, Little Rock, AR 72204 USA.
K IqbalDepartment of Systems Engineering, University of Arkansas at Little Rock, 2801 S University Ave, Little Rock, AR 72204 USA.

Funding

Understanding Hesitant AdoptersP20GM103429 · NIGMS · UNIV OF ARKANSAS FOR MED SCIS · PI Lawrence E Cornett, JERRY WARE · 2012 to 2026
$60.9M
NIGMS NIH HHS P20 GM103429
6 · The paper itself

Abstract

This paper reviews the current status of soft robots in biomedical field. Soft robots are made of materials that have comparable modulus of elasticity to that of biological systems. Several advantages of soft robots over rigid robots are safe human interaction, ease of adaptation with wearable electronics and simpler gripping. We review design factors of soft robots including modeling, controls, actuation, fabrication and application, as well as their limitations and future work. For modeling, we survey kinematic, multibody and numerical finite element methods. Finite element methods are better suited for the analysis of soft robots, since they can accurately model nonlinearities in geometry and materials. However, their real-time integration with controls is challenging. We categorize the controls of soft robots as model-based and model-free. Model-free controllers do not rely on an explicit analytical or numerical model of the soft robot to perform actuation. Actuation is the ability to exert a force using actuators such as shape memory alloys, fluid gels, elastomers and piezoelectrics. Nonlinear geometry and materials of soft robots restrict using conventional rigid body controls. The fabrication techniques used for soft robots differ significantly from that of rigid robots. We survey a wide range of techniques used for fabrication of soft robots from simple molding to more advanced additive manufacturing methods such as 3D printing. We discuss the applications and limitations of biomedical soft robots covering aspects such as functionality, ease of use and cost. The paper concludes with the future discoveries in the emerging field of soft robots.

Indexed as

Biomedical robotsBiomimeticModeling of soft robotRobotic fabricationSoft actuatorSoft robot

Identifiers

PMID32864173
PMCPMC7438463

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.