Evidence map›Paper›PMID 39561150›Full record

ArticlePloS one2024

A high sensitivity, low cost and fully decoupled multi-axis capacitive tactile force sensor for robotic surgical systems.

Sajid Hussain, Muhammad Mubasher Saleem, Muhammad Rehan, Hassan Elahi, Mohsin Islam Tiwana

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Sajid HussainMicro/Nano Robotic Technologies Lab, Department of Mechatronics Engineering, National University of Sciences and Technology, Islamabad, Pakistan.ORCID 0000-0003-1677-5313
Muhammad Mubasher SaleemMicro/Nano Robotic Technologies Lab, Department of Mechatronics Engineering, National University of Sciences and Technology, Islamabad, Pakistan.
Muhammad RehanMicro/Nano Robotic Technologies Lab, Department of Mechatronics Engineering, National University of Sciences and Technology, Islamabad, Pakistan.ORCID 0000-0001-8497-1397
Hassan ElahiMicro/Nano Robotic Technologies Lab, Department of Mechatronics Engineering, National University of Sciences and Technology, Islamabad, Pakistan.ORCID 0000-0001-6836-604X
Mohsin Islam TiwanaMicro/Nano Robotic Technologies Lab, Department of Mechatronics Engineering, National University of Sciences and Technology, Islamabad, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper presents the design of a multi-axis capacitive tactile force sensor with a fully decoupled output response for input normal and shear forces. A patterned elastomer is used as a dielectric layer between capacitive electrodes of the sensor that allows to achieve relatively higher sensitivity. The sensor is fabricated utilizing a low-cost rapid prototyping technique and is characterized for normal and shear forces in the range of 0 ~ 10 N and 0 ~ 3.1 N respectively. The achieved force sensitivity for the normal axis is 2.03%/N and for shear axes is 1.67%/N. The difference between the estimated force from the sensor and actual force applied is negligible, which demonstrates the accuracy of the sensor. The reliability of the sensor is analysed by performing hysteresis and repeatability tests. The hysteresis error is found to be 4.94% and 4.69% for normal and shear forces respectively. The repeatability error of the sensor is less than 5%, which shows the stability of the sensor. The high sensitivity, linear output response, high force measurement range, reliability and low cost make the proposed tactile sensor suitable for the force feedback in the robotic surgical systems.

Indexed as

TouchElectric CapacitanceEquipment DesignHumansReproducibility of ResultsRoboticsRobotic Surgical Procedures

Identifiers

PMID39561150
PMCPMC11575781

What OpenQuestion holds

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LicenceCC BY
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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.