Evidence map›Paper›PMID 33799641›Full record

ArticleSensors (Basel, Switzerland)2021

Adjustable Compliance Soft Sensor via an Elastically Inflatable Fluidic Dome.

Xingtian Zhang, Jun Kow, Dominic Jones, Greg de Boer, Ali Ghanbari, Ahmad Serjouei, Pete Culmer, Ali Alazmani

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. 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. Article
  2. Article
  3. 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

8 authors.

Xingtian ZhangSchool of Mechanical Engineering, University of Leeds, Leeds LS2 9JT, UK.ORCID 0000-0001-5369-1050
Jun KowSchool of Mechanical Engineering, University of Leeds, Leeds LS2 9JT, UK.
Dominic JonesSchool of Mechanical Engineering, University of Leeds, Leeds LS2 9JT, UK.ORCID 0000-0002-2961-8483
Greg de BoerSchool of Mechanical Engineering, University of Leeds, Leeds LS2 9JT, UK.ORCID 0000-0002-5647-1771
Ali GhanbariSchool of Mechanical Engineering, University of Leeds, Leeds LS2 9JT, UK.ORCID 0000-0003-1087-8426
Ahmad SerjoueiDepartment of Engineering, School of Science and Technology, Nottingham Trent University, Nottingham NG11 8NS, UK.ORCID 0000-0002-7250-4131
Pete CulmerSchool of Mechanical Engineering, University of Leeds, Leeds LS2 9JT, UK.
Ali AlazmaniSchool of Mechanical Engineering, University of Leeds, Leeds LS2 9JT, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Soft sensors are essential for robotic systems to safely interact with humans and the environment. Although significant research has been carried out in the field of soft tactile sensing, most of these sensors are restricted to a predefined geometry and a fixed measurement range, hence limiting their application. This paper introduces a novel approach to soft sensing by proposing a soft load-sensing unit with an adjustable mechanical compliance achieved using an elastically inflatable fluidic dome. The sensor consists of a three-dimensional Hall-effect sensor, above which is a magnet whose movement is modulated by an intermediate elastomeric dome structure. Sensor configurations were designed and fabricated using three different silicone rubbers to cover '00-10' and '20A' durometer shore hardness scales. We demonstrated that the compliance of the sensor could be dynamically tuned by changing the internal pressure of the inflatable fluidic dome in all configurations. We performed finite element simulations to determine the reaction force of the sensor under load as well as the stresses within the internal structural behavior, which are not possible to capture experimentally. The proposed soft sensor has the potential to be readily adapted for use in various soft robotic applications of differing size, compliance range, and safety requirements.

Indexed as

RoboticsTouchHardnessHumansadjustable compliancesoft roboticssoft sensortactile sensingvariable stiffness

Identifiers

PMID33799641
PMCPMC7999865

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Registered trials

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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.