Paper Info
Title
A learning based training and skill assessment platform with haptic guidance for endovascular catheterization.
Abstract
Increasing demands in endovascular intervention have motivated technical skill training and competency-based measures of performance. However, there are no well-established online metrics for technical skill assessment; few studies have explored operator behavioral patterns from catheter motion and operator hand motions. This paper proposes a platform for active online training and objective assessment of endovascular skills, through learning optimum catheter motions from multiple demonstrations. An ungrounded hand-held haptic device for providing intuitive haptic guidance to novice users based on this learnt information is also proposed. Statistical models are implemented to extract the underlying catheter motion patterns, and utilize them for performance evaluation and haptic guidance. The results show significant improvements in endovascular navigation for inexperienced operators. Finer catheter motions were achieved with the provided haptic guidance. The results suggest that the proposed platform can be integrated into current clinical training setups, and motivate the improvement of endovascular training platforms with better realism.
Year
DOI
Venue
2017
10.1109/ICRA.2017.7989273
ICRA
Field
DocType
Volume
Behavioral pattern,Simulation,Control engineering,Human–computer interaction,Solid modeling,Engineering,Hidden Markov model,Haptic technology
Conference
2017
Issue
Citations 
PageRank 
1
1
0.37
References 
Authors
19
7
Name
Order
Citations
PageRank
Wenqiang Chi132.78
Hedyeh Rafii-Tari2364.63
Christopher J. Payne3809.37
Jindong Liu420729.44
Celia Riga5187.39
Colin D. Bicknell6103.61
Guang-Zhong Yang72812297.66