Design and development of systems and methods for interventional surgical robot

Interventional procedures are used for diagnosis and/or treatment that involves entry into the body through incision or puncture. Endovascular procedure using guidewire/catheter and needle biopsy procedures are two common surgeries that are performed interventionally using image guidance. Inadequate visual and force feedback, while navigating surgical tools during endovascular (guidewire/catheter) procedures, elevates the risk of surgical error. Further, long-term exposure to x-ray and radiation is a potential occupational hazard for health care providers. Current endovascular robotic systems have helped in reducing the exposure of radiation while improving the precision with which the devices can be placed inside the body. However, the current systems do not provide accurate force feedback or utilize a surgeon’s intuitive surgical skills during manipulation from the master console. Needle biopsy procedures are most frequently performed in hospitals for fluid extractions, biopsies, diagnosis, therapies, and surgeries. Researchers have attempted to model needle insertion into soft tissue using mathematical modeling, yet, wide variability in human anatomy and complexity of access have not been implemented. The goal of this dissertation is to improve two interventional surgical procedures. (i) Endovascular robotic procedures: a novel endovascular robotic system with teleoperation control is designed and developed to addresses two issue; overcome the barrier of transferring surgical skills on a robotic console and; overcome lack of realistic force estimation and feedback mechanism in the robot surgical systems with passive surgical tools, (ii) Needle biopsy procedures: research work focuses on an intelligent robotic system to assist with breast biopsy procedures using; a new ultrasound-guided in-situ needle biopsy robotic medical assistance system, and; a robotic system that uses deep learning techniques to provide needle-tissue interaction force parameter for situation awareness during the procedure.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Systems & Entrepreneurial Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2020

Author dc:creator

• Sankaran, Naveen Kumar

Contributors dc:contributor

• Kesavadas, Thenkurussi
• Sreenivas, Ramavarapu S
• Ferreira, Placid Mathew
• Krishnan, Girish

• Medical robotics, Intelligent robotic system

Statement dc:rights

• Copyright 2020 Naveen Kumar Sankaran

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/107843

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/107843