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Motor Bur Milling State Identification via Fast Fourier Transform Analyzing Sound Signal in Cervical Spine Posterior
1Department of Orthopaedics Surgery, Tianjin Medical University General Hospital, Tianjin, China.
Orthopaedic Surgery
|November 18, 2021
Summary
Sound signals (SS) effectively differentiate motor bur milling states in cervical spine surgery. This research enhances safety in posterior decompression and robot-assisted spinal procedures by providing real-time feedback.
Area of Science:
- Spinal Surgery
- Surgical Robotics
- Biomedical Engineering
Background:
- Cervical spine posterior decompression surgery requires precise control to avoid complications.
- Robot-assisted surgery offers potential for enhanced precision but needs reliable real-time feedback.
- Current methods for monitoring surgical tool-tissue interaction during bone milling may lack sensitivity.
Purpose of the Study:
- To evaluate sound signal (SS) characteristics as a real-time feedback parameter for motor bur milling states in cervical spine surgery.
- To determine if SS can differentiate between milling cancellous bone (CA), ventral cortical bone (VCO), and penetrating ventral cortical bone (PVCO).
- To assess the potential of SS feedback for improving safety in cervical spine posterior decompression and robot-assisted surgeries.
Main Methods:
- Six porcine cervical spine specimens were used, with motor bur milling states defined as CA, VCO, and PVCO.
- Sound signals (SS) were collected using a miniature microphone during milling with 5-mm and 2-mm burs.
- Fast Fourier Transform (FFT) was applied to extract SS magnitudes at various frequencies (1-10 kHz) for statistical analysis using independent sample t-tests.
Main Results:
- Statistically significant differences in SS magnitudes were observed between CA and VCO states at 1, 2, and 3 kHz (P < 0.01).
- Highly significant differences (P < 0.001) in SS magnitudes were found between VCO and PVCO states across all tested frequencies.
- Minor variations in statistical significance were noted at specific frequencies for individual specimens when comparing CA and VCO.
Conclusions:
- Sound signal (SS) magnitudes, analyzed via FFT, serve as a sensitive and reliable indicator for distinguishing motor bur milling states (CA, VCO, PVCO).
- This finding supports the use of SS as a real-time feedback parameter to enhance intraoperative awareness.
- The study suggests that SS feedback can potentially improve the safety and precision of cervical spine posterior decompression, particularly in robot-assisted procedures.
