Bionic Binaural Perception-Based Performance Enhancement for Orthopedic Surgical Systems

Bone milling is widely used in orthopaedic surgery. But the high-speed rotating ball-end milling tool (BMT) may cause damage during surgery. This article presents a method for sensing and controlling the milling state (angle and depth) of surgical robots based on acoustic signals. First, a theoretical model of acoustic signal and milling state is proposed. Second, a dual band-pass filter and feature extraction method are designed according to signal frequency domain characteristics. Then, a robotic platform is built to complete calibration experiments and obtain model function parameters. Finally, comparative experiments are conducted to validate the method. Experimental results show that adding angle control can improve milling depth accuracy and reduce bone compression force compared with only depth control. The method can effectively enhance surgical results.