2012 Poster Sessions : An Experimental Platform for Haptic Feedback in Robotic Catheterization Tasks

Student Name : Michael Yip
Advisor : Kenneth Salisbury
Research Areas: Artificial Intelligence
Abstract:
A popular method for treating cardiac arrhythmias such as atrial fibrillation have been to snake ablation catheters into the beating heart to target and remove erroneous electrical pathways causing improper contractions. As the catheter is passed into the body, the loss of visual feedback, tactile and haptic feedback, and narrowing obstructions makes the control the catheter position a difficult task.

The instrumentation and robotic actuation of surgical catheters can be useful for a number of reasons: estimating the physical configuration of a catheter under various geometric constraints from the environment, understanding the interaction forces exerted between a catheter and its environment, and more intuitive, reproducible control of a catheter. Companies such as Hansen Medical (Sensei X, Robotic Catheter System) have provided robotic catheter solutions that electrophysiologist find useful and desirable for treating atrial fibrillation. However, these teleoperated systems are expensive and do not distal end position or force sensing, which could be critically important into assessing the stress caused by the catheter, tissue ablation success, and decreasing the chance of perforation leading to mortality.

We have developed a general purpose flexible robot platform for investigating instrumentation and model-based methods for estimating robot configurations and interaction forces. Different instrumentation methods versus mechanics model-based approaches are being evaluated and compared based on their cost, size, sensitivity, accuracy, etc. The robot is teleoperated and, using instrumentation and mechanics models for configuration and force sensing, provides haptic feedback to the master by simultaneously mapping the environmental forces while exploring the workspace. These methods can be generally applicable to all types of flexible robotics.

Bio:
Michael Yip is a Ph.D. Candidate in Bioengineering with David Camarillo and Ken Salisbury in the Camarillo lab and the BioRobotics Lab, respectively. Michael's research focus is on electromechanical design, robotics, medical image analysis and computer vision in the context of medicine. He has a B.A.Sc. in Mechatronics Engineering from University of Waterloo and a M.A.Sc. in Electrical Engineering from University of British Columbia.