PDF(Pubmed)
Abstract：
OBJECTIVE: Practical applications of nerve decompression using neurosurgical robots remain unexplored. Our ongoing research and development initiatives, utilizing industrial robots, aim to establish a secure and efficient neurosurgical robotic system. The principal objective of this study was to automate bone grinding, which is a pivotal component of neurosurgical procedures.
METHODS: To achieve this goal, we integrated an endoscope system into a manipulator and conducted precision bone machining using a neurosurgical drill, recording the grinding resistance values across 3 axes. Our study encompassed 2 core tasks: linear grinding, such as laminectomy, and cylindrical grinding, such as foraminotomy, with each task yielding unique measurement data.
RESULTS: In linear grinding, we observed a proportional increase in grinding resistance values in the machining direction with acceleration. This observation suggests that 3-axis resistance measurements are a valuable tool for gauging and predicting deep cortical penetration. However, problems occurred in cylindrical grinding, and a significant error of 10% was detected. The analysis revealed that multiple factors, including the tool tip efficiency, machining speed, teaching methods, and deflection in the robot arm and jig joints, contributed to this error.
CONCLUSIONS: We successfully measured the resistance exerted on the tool tip during bone machining with a robotic arm across 3 axes. The resistance ranged from 3 to 8 Nm, with the measurement conducted at a processing speed approximately twice that of manual surgery performed by a surgeon. During the simulation of foraminotomy under endoscopic grinding conditions, we encountered a -10% error margin.
METHODS: To achieve this goal, we integrated an endoscope system into a manipulator and conducted precision bone machining using a neurosurgical drill, recording the grinding resistance values across 3 axes. Our study encompassed 2 core tasks: linear grinding, such as laminectomy, and cylindrical grinding, such as foraminotomy, with each task yielding unique measurement data.
RESULTS: In linear grinding, we observed a proportional increase in grinding resistance values in the machining direction with acceleration. This observation suggests that 3-axis resistance measurements are a valuable tool for gauging and predicting deep cortical penetration. However, problems occurred in cylindrical grinding, and a significant error of 10% was detected. The analysis revealed that multiple factors, including the tool tip efficiency, machining speed, teaching methods, and deflection in the robot arm and jig joints, contributed to this error.
CONCLUSIONS: We successfully measured the resistance exerted on the tool tip during bone machining with a robotic arm across 3 axes. The resistance ranged from 3 to 8 Nm, with the measurement conducted at a processing speed approximately twice that of manual surgery performed by a surgeon. During the simulation of foraminotomy under endoscopic grinding conditions, we encountered a -10% error margin.
摘要：
目的：使用神经外科机器人进行神经减压的实际应用尚待探索。我们正在进行的研究和发展计划，利用工业机器人，旨在建立安全高效的神经外科机器人系统。这项研究的主要目的是使骨研磨自动化，这是神经外科手术的关键组成部分。
方法：为了实现这一目标，我们将内窥镜系统集成到机械手中，并使用神经外科钻进行精密骨骼加工，记录3个轴的磨削电阻值。我们的研究包括2个核心任务：线性研磨，比如椎板切除术，和圆柱形研磨，比如椎间孔切开术，每个任务都会产生唯一的测量数据。
结果：在线性研磨中，我们观察到随着加速度在加工方向上的磨削电阻值成比例地增加。此观察结果表明，3轴电阻测量是测量和预测深层皮质渗透的有价值的工具。然而,外圆磨削中出现的问题，检测到10%的显著误差。分析表明，多种因素，包括刀尖效率，加工速度,教学方法,以及机器人手臂和夹具关节的偏转，导致了这个错误。
结论：我们成功地测量了在跨3个轴的机械臂进行骨骼加工期间施加在工具尖端上的阻力。电阻范围从3到8Nm，以大约两倍于外科医生进行的手动手术的处理速度进行测量。在内窥镜磨削条件下模拟椎间孔切开术期间，我们遇到了-10%的误差。
方法：为了实现这一目标，我们将内窥镜系统集成到机械手中，并使用神经外科钻进行精密骨骼加工，记录3个轴的磨削电阻值。我们的研究包括2个核心任务：线性研磨，比如椎板切除术，和圆柱形研磨，比如椎间孔切开术，每个任务都会产生唯一的测量数据。
结果：在线性研磨中，我们观察到随着加速度在加工方向上的磨削电阻值成比例地增加。此观察结果表明，3轴电阻测量是测量和预测深层皮质渗透的有价值的工具。然而,外圆磨削中出现的问题，检测到10%的显著误差。分析表明，多种因素，包括刀尖效率，加工速度,教学方法,以及机器人手臂和夹具关节的偏转，导致了这个错误。
结论：我们成功地测量了在跨3个轴的机械臂进行骨骼加工期间施加在工具尖端上的阻力。电阻范围从3到8Nm，以大约两倍于外科医生进行的手动手术的处理速度进行测量。在内窥镜磨削条件下模拟椎间孔切开术期间，我们遇到了-10%的误差。
