Towards Characterization and Adaptive Compensation of Backlash in a Novel Robotic Catheter System for Cardiovascular Interventions

Despite the success and prospects of the robotic catheter system for the cardiovascular access, loss of vision, and haptics have limited its global adoption. A direct implication is the great difficulty posed when trying to eliminate the backlash in catheters during vascular cannulations. As a resul...

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Bibliographic Details
Published in:IEEE transactions on biomedical circuits and systems 2018-08, Vol.12 (4), p.824-838
Main Authors: Omisore, Olatunji Mumini, Han, Shi Peng, Ren, Ling Xue, Wang, Guo Shuai, Ou, Fang Liang, Li, Hui, Wang, Lei
Format: Article
Language:English
Subjects:
adaptive compensation system
adaptive neuro-fuzzy inference system (ANFIS)
Adaptive systems
Artificial neural networks
backlash characterization
C++ (programming language)
Cardiovascular access
Catheterization
Catheters
Compensation
Contact force
Control systems
Equipment Design - methods
force modulation
Fuzzy logic
Fuzzy systems
Heart
Humans
Medical instruments
Medical personnel
medical robotics
Radiation
Robot sensing systems
robotic catheter system
Robotic surgery
Robotic Surgical Procedures - methods
Robotics
Robots
vascular catheterization
Visual C
Visual programming languages
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Summary:Despite the success and prospects of the robotic catheter system for the cardiovascular access, loss of vision, and haptics have limited its global adoption. A direct implication is the great difficulty posed when trying to eliminate the backlash in catheters during vascular cannulations. As a result, physicians and patients end up been exposed to high radiation for a long period of time. Existing control systems proposed for such interventional robots have not fully consider the hysteretic (backlash) behavior. In this study, a novel robotic catheter system is designed for accessing the human cardiac area through the radial vasculature, while single factor descriptive analysis is employed to characterize the backlash behavior during axial motions of the interventional robot. Based on the descriptive analysis, an adaptive system is proposed for the backlash compensation during the cardiovascular access. The adaptive system consists of a neuro-fuzzy module that predicts a backlash gap based on bounded motion signals, and contact force modulated from a modified error-based force control model. The proposed system is implemented in MATLAB and visual C++. Finally, an in vitro experiment with a human tubular model, shows that the proposed adaptive compensation system can minimize the backlash occurrence during cardiovascular access.
ISSN:1932-4545
1940-9990
DOI:10.1109/TBCAS.2018.2825359