Evidence map›Paper›PMID 40040218›Full record

ArticleAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference2024

Bedside Admittance Control of a Dual-Segment Soft Robot for Catheter-Based Interventions.

Noah Barnes, Shaopeng Jiang, Lingyun Di, Hannah Qu, Miroslaw Janowski, Charles I Berul, Adira Colton, Olivia Young, Ryan D Sochol, Jeremy D Brown and 1 more

Abstract read
In one paragraph

Article in Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 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
0cells of the map it votes in
0citing 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

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

11 authors.

Noah Barnes
Shaopeng Jiang
Lingyun Di
Hannah Qu
Miroslaw Janowski
Charles I Berul
Adira Colton
Olivia Young
Ryan D Sochol
Jeremy D Brown
Axel Krieger

Funding

3D-Nanoprinted Soft Robotic Microcatheters with Integrated Microfluidic Circuitry for Cerebrovascular SurgeryR01EB033354 · NIBIB · UNIV OF MARYLAND, COLLEGE PARK · PI SOCHOL, RYAN DANIEL · 2022 to 2025
$2.7M
NIBIB NIH HHS R01 EB033354
6 · The paper itself

Abstract

Robotic catheters enable precise steering of their distal tip while inside the body's blood vessels, and with this ability comes the need for control systems that fit into the clinical workflow. In this study, we propose a novel bedside admittance controller composed of a force/torque sensor with a 3D-printed handle and a low-profile table mount. The controller is intended to be placed at the insertion site to the body and allows simultaneous insertion and steering of a dual-segment fluid-actuated soft robot catheter. This teleoperated system is characterized and evaluated in a simulated cardiac ablation task using a two dimensional 3D-printed atrium-like cavity. Four novices controlled the soft robot catheter with an average position error of 0.4 mm and angle error of 4.6 degrees, as compared to position error of 1.0 mm and angle error of 18.2 degrees attained by an expert cardiologist using a standard ablation catheter. The controller enables intuitive control of a dual channel soft robot and the preliminary results indicate the potential advantage of such an approach in catheter-based interventions with increasingly complex catheter robots.

Indexed as

Catheter AblationCathetersPoint-of-Care SystemsRoboticsRobotic Surgical ProceduresEquipment DesignHumans

Identifiers

PMID40040218
PMCPMC11956434

What OpenQuestion holds

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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.