机器人导尿术中外科医生自然技能的探讨
Exploration of Surgeons' Natural Skills for Robotic Catheterization
摘要：
尽管机器人导管系统最近已成为进行心血管介入的安全方式，但仍有许多重要挑战有待研究。其中之一是探索外科医生在使用机器人系统进行血管导管插入术期间的自然技能。在这项研究中，外科医生的自然手部动作进行了调查，以确定四个基本的运动用于血管内导管插入术。对照实验设置为获取表面肌电图（sEMG）信号从六个肌肉受神经支配时，与导管技术的主题，使开放设置的四个动作。k-means和k-NN模型在平均EMG和均方根特征上实现，以唯一地识别运动。结果表明，sEMG分析对设计安全有效的机器人导管插入的智能机器人控制的巨大潜力。
英文摘要：
Despite having the robotic catheter systems which have recently emerged as safe way of performing cardiovascular interventions, a number of important challenges are yet to be investigated. One of them is exploration of surgeons' natural skills during vascular catheterization with robotic systems. In this study, surgeons' natural hand motions were investigated for identification of four basic movements used for intravascular catheterization. Controlled experiment was setup to acquire surface electromyography (sEMG) signals from six muscles that are innervated when a subject with catheterization skills made the four movements in open settings. k-means and k-NN models were implemented over average EMG and root means square features to uniquely identify the movements. The result shows great potentials of sEMG analysis towards designing intelligent cyborg control for safe and efficient robotic catheterization.
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