A Robotic Mediation Device for Skill Assessment and Training During Colonoscopy

Colonoscopy demands multi-finger coordinated motion to achieve safe navigation. As a result, training for colonoscopists is challenging and skill assessment currently relies on subjective scoring by expert proctors. There is a need to provide tools for skill assessment and aid with training new interventionalists. This paper presents a new concept of an in-hand robotic mediation device that can be used for both skill assessment and training. The robotic device can be used to infer the kinematic motion as well as the power input of a user - both of which are proposed to be used for skill assessment and subtask skill classification. Preliminary results collected expert and novice users performing colonoscopy navigation are used to demonstrate this device as a skill assessment tool. A machine-learning model (classification and regression trees) is used for subtask classification of skill and evaluating the most important classification features. A user study demonstrates the effectiveness of this in hand haptic training and assessment tool. We believe that, in the future, this device will enable accelerated skill assessment and training and possible semi-automation of difficult maneuvers.