Interdisciplinary Program for Bioengineering, Graduate School, Seoul National University, Seoul, 03080, Republic of Korea.
Korea Electrotechnology Research Institute, Ansan, 15588, Republic of Korea.
Med Biol Eng Comput. 2019 Mar;57(3):601-614. doi: 10.1007/s11517-018-1902-4. Epub 2018 Oct 2.
Although robot-assisted surgeries offer various advantages, the discontinuous surgical operation flow resulting from switching the control between the patient-side manipulators and the endoscopic robot arm can be improved to enhance the efficiency further. Therefore, in this study, a head-mounted master interface (HMI) that can be implemented to an existing surgical robot system and allows continuous surgical operation flow using the head motion is proposed. The proposed system includes an HMI, a four degrees of freedom endoscope control system, a simple three-dimensional endoscope, and a da Vinci Research Kit. Eight volunteers performed seven head movements and their data from HMI was collected to perform support vector machine (SVM) classification. Further, ten-fold cross-validation was performed to optimize its parameters. Using the ten-fold cross-validation result, the SVM classifier with the Gaussian kernel (σ = 0.85) was chosen, which had an accuracy of 92.28%. An endoscopic control algorithm was developed using the SVM classification result. A peg transfer task was conducted to check the time-related effect of HMI's usability on the system, and the paired t test result showed that the task completion time was reduced. Further, the time delay of the system was measured to be 0.72 s. Graphical abstract A head-mounted master interface (HMI), which can be implemented to an existing surgical robot system, was developed to allow simultaneous surgical operation flow. The surgeon's head motion is detected through the proposed HMI and classified using a support vector machine to manipulate the endoscopic robotic arm. A classification accuracy of 92.28% was achieved.
虽然机器人辅助手术具有许多优势,但由于需要在患者侧操作器和内窥镜机器人臂之间切换控制,手术操作流程会不连续,可以进一步改进以提高效率。因此,在本研究中,提出了一种可以集成到现有手术机器人系统中的头戴式主接口(HMI),该接口可以通过头部运动实现连续手术操作流程。所提出的系统包括一个 HMI、一个四自由度内窥镜控制系统、一个简单的三维内窥镜和一个达芬奇研究套件。八名志愿者进行了七次头部运动,他们的 HMI 数据被收集以进行支持向量机(SVM)分类。进一步,进行了十折交叉验证以优化其参数。使用十折交叉验证结果,选择了具有高斯核(σ=0.85)的 SVM 分类器,其准确率为 92.28%。使用 SVM 分类结果开发了一种内窥镜控制算法。进行了一个 peg 转移任务,以检查 HMI 对系统可用性的时间相关影响,配对 t 检验结果表明任务完成时间缩短了。此外,还测量了系统的延迟时间为 0.72s。