Evidence map›Paper›PMID 37880294›Full record

ArticleScientific reports2023

Touch, press and stroke: a soft capacitive sensor skin.

Mirza S Sarwar, Ryusuke Ishizaki, Kieran Morton, Claire Preston, Tan Nguyen, Xu Fan, Bertille Dupont, Leanna Hogarth, Takahide Yoshiike, Ruixin Qiu and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. 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

13 authors.

Mirza S SarwarElectrical and Computer Engineering, Advanced Materials and Process Engineering Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada. mirzas@ece.ubc.ca.
Ryusuke IshizakiFrontier Robotics, Innovative Research Excellence, Honda R&D Co., Ltd, 8-1 Honcho, Wako-shi, Saitama, 351-0188, Japan.
Kieran MortonElectrical and Computer Engineering, Advanced Materials and Process Engineering Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada.
Claire PrestonElectrical and Computer Engineering, Advanced Materials and Process Engineering Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada.
Tan NguyenElectrical and Computer Engineering, Advanced Materials and Process Engineering Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada.
Xu FanElectrical and Computer Engineering, Advanced Materials and Process Engineering Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada.
Bertille DupontElectrical and Computer Engineering, Advanced Materials and Process Engineering Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada.
Leanna HogarthElectrical and Computer Engineering, Advanced Materials and Process Engineering Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada.
Takahide YoshiikeFrontier Robotics, Innovative Research Excellence, Honda R&D Co., Ltd, 8-1 Honcho, Wako-shi, Saitama, 351-0188, Japan.
Ruixin QiuElectrical and Computer Engineering, Advanced Materials and Process Engineering Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada.
Yiting WuElectrical and Computer Engineering, Advanced Materials and Process Engineering Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada.
Shahriar MirabbasiElectrical and Computer Engineering, Advanced Materials and Process Engineering Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada.
John D W MaddenElectrical and Computer Engineering, Advanced Materials and Process Engineering Laboratory, University of British Columbia, Vancouver, V6T 1Z4, Canada. jmadden@ece.ubc.ca.ORCID http://orcid.org/0000-0002-0014-4712

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Soft sensors that can discriminate shear and normal force could help provide machines the fine control desirable for safe and effective physical interactions with people. A capacitive sensor is made for this purpose, composed of patterned elastomer and containing both fixed and sliding pillars that allow the sensor to deform and buckle, much like skin itself. The sensor differentiates between simultaneously applied normal force and shear using summation and differences of signals from four deformable capacitors. Cross talk from shear to normal force is less than 2.5%, and between shear axes is less than 10%. Normal and shear stress sensitivity is 0.49 kPa and 0.31 kPa respectively, with a minimum displacement resolution of 40 μm. In addition, finger proximity is detectable at a range of up to 15 mm. The operation is demonstrated on a simple gripper holding a cup. The combination of features and the straightforward fabrication method make this sensor a candidate for implementation as a sensing skin for humanoid robotics applications.

Indexed as

RoboticsHumansMechanical PhenomenaTouch

Identifiers

PMID37880294
PMCPMC10600100

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.