Sound Feedback Fuzzy Control for Optimizing Bone Milling Operation During Robot-Assisted Laminectomy

This article aims to optimize robotic actions for bone milling during laminectomy. The layer-by-layer spinal lamina milling operation during robot-assisted laminectomy is analyzed in detail to summarize related control tasks. A milling sound signal processing method based on band filters and the two-order Prony algorithm is proposed to overcome the frequency disturbance of the surgical power device's rotation motion caused by bone milling to accurately extract harmonic amplitudes. A depth estimation model based on the total value of major harmonics is fitted to monitor the actual depth when the ball end is cutting into an easily displaced bone. A milling feed speed optimization method based on the sound signal feedback and a fuzzy controller is designed to balance the efficiency and safety of bone milling. Milling experiments are carried out on artificial bone blocks and fresh swine cervical vertebrae. The results show that the depth monitoring accuracy is about 0.08 mm and the feed speed can be optimized effectively to match the actual bone mineral density and axial depth of cut. The proposed method can improve the depth accuracy and output a safe and fastest feed speed.