Evidence map›Paper›PMID 37787938›Full record

ArticleInternational journal of computer assisted radiology and surgery2024

Improved precise guidewire delivery of a cardiovascular interventional surgery robot based on admittance control.

Shuang Wang, Zheng Liu, Yongfeng Cao, Ling Zhang, Le Xie

Abstract read
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In one paragraph

Article in International journal of computer assisted radiology and surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
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  3. Review
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.

Shuang WangInstitute of Forming Technology and Equipment, Shanghai Jiao Tong University, Shanghai, 200240, China.ORCID http://orcid.org/0000-0002-4823-3511
Zheng LiuInstitute of Forming Technology and Equipment, Shanghai Jiao Tong University, Shanghai, 200240, China.
Yongfeng CaoInstitute of Forming Technology and Equipment, Shanghai Jiao Tong University, Shanghai, 200240, China.
Ling ZhangInstitute of Forming Technology and Equipment, Shanghai Jiao Tong University, Shanghai, 200240, China.
Le XieInstitute of Forming Technology and Equipment, Shanghai Jiao Tong University, Shanghai, 200240, China. lexie@sjtu.edu.cn.

Funding

Cooperation Project of Xuhui District Artificial Intelligence Medical Institute 2021-008Foreign Cooperation Project of Fujian Province Science and Technology Program 2022I0041National Natural Science Foundation of China 61973211National Natural Science Foundation of China 62133009National Natural Science Foundation of China M-0221Quanzhou High-level Talent Innovation and Entrepreneurship 2021C003Rthe Joint Project of Xinhua Hospital-Institute of Medical Robotics of Shanghai Jiao Tong University 21XJMR03
6 · The paper itself

Abstract

purposeThe development of cardiovascular interventional surgery robots can realize master-slave interventional operations, which will effectively solve the problem of surgeons being injured by X-ray radiation. The delivery accuracy and safety of interventional instruments such as guidewire are the most important issues in the development of robotic systems. Most of the current control methods are position control or force feedback control, which cannot take into account delivery accuracy and safety.

methodsA cardiovascular interventional surgery robotic system integrated force sensors is developed. A novel force/position controller, which includes a radial basis function neural networks-based inner loop position controller and a force-based admittance outer loop controller, is proposed. Furthermore, a series of simulations and vascular model experiments are carried out to demonstrate the feasibility and accuracy of the proposed controller.

resultsThe designed cardiovascular interventional robot is flexible to enter the target vessel branch. Experimental results indicate that the proposed controller can effectively improve the delivery accuracy of the guidewire and reduce the contact force with the vessel wall.

conclusionsThe proposed controller based on radial basis function neural network and admittance control is effective in improving delivery accuracy and reducing contact force. The algorithm needs to be further validated in vivo experiments.

Indexed as

RoboticsRobotic Surgical ProceduresEquipment DesignHumansMechanical PhenomenaVascular Surgical ProceduresAdmittance controlCardiovascular interventional surgery robotPosition controlRadial Basis Function Neural Networks

Identifiers

PMID37787938

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.