A Training-Evaluation Method for Nursing Telerobot Operator with Unsupervised Trajectory Segmentation

Jiexin Xie, Deliang Zhu, Jiaxin Wang, Shijie Guo

Abstract: To cope with the difficulty of training and eval-uation for nursing telerobot operator. This paper proposes a training-evaluation method for operator with unsupervised trajectory segmentation. To evaluate the dexterity and proce-dural knowledge of the operators objectively, we propose a new unsupervised model TSC-CRP that can automatically segment trajectory from nursing robotic training sessions. By comparing the segmented sub-trajectories and the standard sub-trajectory process, the method can provide objective evaluation and meaningful feedback without the intervention from experts. Experiments show that TSC-CRP has higher segmentation accuracy than other unsupervised methods, and it can identify the operators with different skill levels. In practical, the proposed training-evaluation system allows to provide an in-depth analysis of operator action to assess their skills precisely.