Design and Performance Investigation of a Robot-Assisted Flexible Ureteroscopy System

Author:

Zhao Jianchang1ORCID,Li Jianmin12,Cui Liang3,Shi Chaoyang12ORCID,Wei Guowu4ORCID

Affiliation:

1. School of Mechanical Engineering, Tianjin University, Tianjin 300350, China

2. Key Laboratory of Mechanism Theory and Equipment Design, Ministry of Education, Tianjin 300350, China

3. Urology Department of Civil Aviation General Hospital, Beijing 100123, China

4. School of Science, Engineering and Environment, University of Salford, Salford, M5 4WT, UK

Abstract

Flexible ureteroscopy (FURS) has been developed and has become a preferred routine procedure for both diagnosis and treatment of kidney stones and other renal diseases inside the urinary tract. The traditional manual FURS procedure is highly skill-demanding and easily brings about physical fatigue and burnout for surgeons. The improper operational ergonomics and fragile instruments also hinder its further development and patient safety enhancement. A robotic system is presented in this paper to assist the FURS procedure. The system with a master-slave configuration is designed based on the requirement analysis in manual operation. A joint-to-joint mapping strategy and several control strategies are built to realize intuitive and safe operations. Both phantom and animal experiments validate that the robot has significant advantages over manual operations, including the easy-to-use manner, reduced intraoperative time, and improved surgical ergonomics. The proposed robotic system can solve the major drawbacks of manual FURS. The test results demonstrate that the robot has great potential for clinical applications.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Biomedical Engineering,Bioengineering,Medicine (miscellaneous),Biotechnology

Cited by 17 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3