Vibration-Based Milling Condition Monitoring in Robot-Assisted Spine Surgery

Abstract

In order to enhance the safety of the milling operation, we develop a condition monitoring method by means of analyzing the bone vibration signal in robot-assisted spine surgery. Since the behavior of the bone being cut changes with the tissue removal, an analytical method is proposed for modeling of varying bone dynamics, and then, it is proved that the vibration amplitude of the bone indicates its status change. During the real milling process, the vibration signal of the bone is recorded by a noncontact laser displacement sensor, and we only pay attention to the harmonic component whose frequency is an integer times of the spindle frequency of the milling device. The wavelet packet transform and the adaptive linear element are performed to estimate the harmonic amplitude from the signal to correlate milling condition. Considering that the bone vibration also varies with the milling force, the relative magnitude of the force is measured from the wavelet coefficients in low-frequency subband, and subsequently, the estimated harmonic amplitude is compensated to reduce the influence of the force. The robot milling experiments in sheep spines are carried on to verify the effectiveness of the condition monitoring procedure. The experimental results are in substantial accordance with the conclusions from the dynamic model, and thus, the robot can improve the safety of the operation with the proposed method.