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.

Analysis of the process parameters affecting the bone burring process: An in‐vitro porcine study

“…To date, studies that have characterized and/or optimized the bone burring process focused either on bone temperature, tool vibration, or burring force independent of one another. However, many of the process parameters that were assumed as fixed/constant in the past are in fact adjustable and thereby have an inherent variable nature. To our knowledge, this is the first report of bone temperature, tool vibration, and burring force being quantified concurrently, and analyzed within a common factorial analysis.…”

“…Initial interest has been in quantifying the experimental thermal generation associated with the operations that include removal of bone [1][2][3][4][17][18][19] . Recent studies have also reported burring forces and tool vibrations with a common theme toward the development of closed-loop controllers for robotic surgical procedures [20][21][22][23] . However, these studies did not investigate the interactions of process parameters to find an optimum combination that simultaneously optimizes both bone temperature and burring vibration.…”

Force Perception and Bone Recognition of Vertebral Lamina Milling by Robot-Assisted Ultrasonic Bone Scalpel Based on Backpropagation Neural Network

“…In addition, the surgery can be significantly essential to obtain more information on the operation status during robot-assisted surgery and recognize the tissue in contact with the robotic arm end. the milling parts, and current change of the drill were obtained and monitored to indirectly reflect the mechanical information during bone milling and realize bone tissue recognition [20]- [23]. However, these studies did not consider the different operative methods, speed, and parameter settings of the power equipment, which eventually affect the perception of the milling force.…”

Experimental analysis of the process parameters affecting bone burring operations

“…In addition to cutting forces, burring vibrations represent another important variable to be included in automated burring control loops, particularly since they will significantly affect the overall precision of the process. Dai et al 19,20 proved the feasibility of a vibration-feedback controller in improving the safety of the robot-assisted bone milling/surgery. Another somewhat indirect attempt to experimentally quantify burring vibrations has been made by Denis et al, 11 who concluded that surface flatness could be regarded as a by-product of the dynamic effects of the tool.…”