Breakthrough detection is a crucial task to reduce the risks of damaging soft tissue bone drilling operations during orthopedic surgery. Conventional drills are not equipped with this function while the recent literature has offered this capability with high cost and complex modification needs. In this study, a new breakthrough detection approach based on closed-loop control characteristics of the drilling operation is proposed. A feature set containing closed-loop signals and force sensor data is created to train K-Nearest and Ensemble Classifier for breakthrough detection tasks with drilling the synthetic bone model and animal bone with a robot manipulator. The best accuracy of breakthrough detection with only closed-loop control signal attributes is achieved as 96.9 ± 0.8% for the synthetic bone model and 98.1 ± 0.2% for sheep femur bone. Breakthrough detection delay which included sampling and operation time of the method guarantees that the drill bit would stop with acceptable breakthrough range of 1.0413 mm. The proposed method can be used to detect breakthrough and also to estimate the state of the drill bit in robotic orthopedic bone drilling processes using only closed-loop signals so that it would be no need to use extra high-cost sensors.

中文翻译：

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一种采用闭环控制方法的机器人整形外科手术中骨钻突破检测的新方法。

突破性检测是降低骨科手术期间破坏软组织骨钻孔操作风险的关键任务。常规钻机不具备此功能，而最近的文献提供了具有高成本和复杂修改需求的功能。提出了一种基于钻井作业闭环控制特性的突破检测方法。创建了一个包含闭环信号和力传感器数据的功能集，以训练K-最近和集成分类器来完成突破性的检测任务，并使用机器人操纵器钻取合成骨骼模型和动物骨骼。仅具有闭环控制信号属性的突破检测的最佳精度对于合成骨模型为96.9±0.8％，对于绵羊股骨为98.1±0.2％。该方法包括采样和操作时间在内的穿透检测延迟可确保钻头以1.0413毫米的可接受穿透范围停止。所提出的方法可以用于检测突破，也可以仅使用闭环信号来估计机器人整形外科骨钻孔过程中的钻头状态，因此无需使用额外的高成本传感器。