Evidence map›Paper›PMID 38577480›Full record

ArticleProceedings of IEEE Sensors. IEEE International Conference on Sensors2023

Data-driven Shape Sensing of Continuum Dexterous Manipulators Using Embedded Capacitive Sensor.

Qihang Li, Wenpeng Wang, Joshua Liu, Amit Jain, Mehran Armand

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Proceedings of IEEE Sensors. IEEE International Conference on Sensors, 2023. 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

5 authors.

Qihang LiLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, USA.
Wenpeng WangLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, USA.
Joshua LiuLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, USA.
Amit JainLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, USA.
Mehran ArmandLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, USA.

Funding

Image-Guided Workstation and Tools for the Treatment of Bone DefectsR01EB016703 · NIBIB · UNIVERSITY OF ARKANSAS AT FAYETTEVILLE · PI ARMAND, MEHRAN · 2013 to 2022
$3.4M
Robotic System for Spinal Decompression and Interbody FusionR01AR080315 · NIAMS · UNIVERSITY OF ARKANSAS AT FAYETTEVILLE · PI ARMAND, MEHRAN, JAIN, AMIT · 2022 to 2025
$1.7M
Robot-Assisted Femoroplasty with Intraoperative Biomechanical FeedbackR01EB023939 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI ARMAND, MEHRAN · 2017 to 2020
$1.6M
NIAMS NIH HHS R01 AR080315NIBIB NIH HHS R01 EB016703NIBIB NIH HHS R01 EB023939
6 · The paper itself

Abstract

We propose a novel inexpensive embedded capacitive sensor (ECS) for sensing the shape of Continuum Dexterous Manipulators (CDMs). Our approach addresses some limitations associated with the prevalent Fiber Bragg Grating (FBG) sensors, such as temperature sensitivity and high production costs. ECSs are calibrated using a vision-based system. The calibration of the ECS is performed by a recurrent neural network that uses the kinematic data collected from the vision-based system along with the uncalibrated data from ECSs. We evaluated the performance on a 3D printed prototype of a cable-driven CDM with multiple markers along its length. Using data from three ECSs along the length of the CDM, we computed the angle and position of its tip with respect to its base and compared the results to the measurements of the visual-based system. We found a 6.6% tip position error normalized to the length of the CDM. The work shows the early feasibility of using ECSs for shape sensing and feedback control of CDMs and discusses potential future improvements.

Indexed as

capacitive sensingcontinuum dexterous manipulatorsshape estimation

Identifiers

PMID38577480
PMCPMC10994196

What OpenQuestion holds

Textmetadata
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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.