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Towards validation of robotic surgery training assessment across training platforms

Towards validation of robotic surgery training assessment across training platforms,10.1109/IROS.2011.6048437,Yixin Gao,Mert Sedef,Amod Jog,Peter Peng

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Towards validation of robotic surgery training assessment across training platforms  
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Robotic surgery is increasingly popular for a wide range of complex minimally invasive surgery procedures. To improve robotic surgery training, a skills trainer simulator called dV-Trainer has recently been introduced, and a da Vinci Skills Simulator is in advanced evaluation. These platforms report a range of time and motion based task metrics and literature has investigated the validity of these metrics in training studies. However, the lack of a cross-platform data collection system has so far prevented a cross-platform investigation. Using a new architecture for collecting cross-platform motion data, we present the first study investigating whether metrics previously validated in simulation environments also hold in training exercises with a real robotic system. Prelim- inary experiments for an anastomosis needle throwing task in both simulated and real robotic environments are presented, and corresponding performance metrics for both proficient and trainee users are reported.
Conference: International Conference on Intelligent RObots and Systems - IROS - IROS , pp. 2539-2544, 2011
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