Access Type

Open Access Dissertation

Date of Award

1-1-2011

Degree Type

Dissertation

Degree Name

Ph.D.

Department

Electrical and Computer Engineering

First Advisor

Abhilash Pandya

Abstract

OPTIMAL SURGICAL PORT PLACEMENT AND AUTOMATED ROBOTIC POSITIONING FOR RAMAN AND OTHER BIOSENSORS

by

BRADY KING

January 2011

Advisors: Dr. Abhilash Pandya, Dr. Darin Ellis, Dr. Le Yi Wang, and Dr. Greg Auner

Major: Computer Engineering

Degree: Doctor of Philosophy

Medical biosensors can provide new information during minimally invasive and robotic surgical procedures. However, these biosensors have significant physical limitations that make it difficult to find optimal port locations and place them in vivo. This dissertation explores the application of robotics and virtual/augmented reality to biosensors to enable their optimal use in vivo.

In the first study, human performance in the task of port placement was evaluated to determine if computer intervention and assistance was needed. Using a virtual surgical environment, we present a number of targets on one or more tissue surfaces. A human factors study was conducted with 20 subjects that analyzed the subject's placement of a port with the goal of scanning as many targets as possible with a biosensor. The study showed performance to be less than optimal with significant degradation in several specific scenarios.

In the second study, an automated intelligent port placement system for biosensor use was developed. Patient data was displayed in an environment in which a surgeon could indicate areas of interest. The system utilized biosensor physical limitations and provided the best port location from which the biosensor could reach the targets on a collision-free path. The study showed that it is possible to find an optimal port location for proper biosensor data capture.

In the final study, a surgical robot was investigated for potential use in holding and positioning a biosensor in vivo. A full control suite was developed for an AESOP 1000, enabling the positioning of the biosensor without hand manipulation. It was found that the robot lacks the accuracy needed for proper biosensor utilization. Specific causes for the inaccuracies were identified for analysis and consideration in future robotic platforms.

Overall, the results show that the application of medical robotics and virtual/augmented reality is able to overcome of the significant physical limitations inherent to biosensor design that currently limit their use in surgery. We conjecture that a complete system, with a more accurate robot, could be used in vivo. We believe that results taken from the individual studies will result in improvements to pre-operative port placement and robotic design.

Download

Share

COinS