Surgical Tool Handle Vibration-Based Drilling State Recognition During Hip Fracture Fixation

Area of Science:

• Robotics in Orthopedic Surgery
• Biomedical Engineering
• Surgical Navigation Systems

Background:

• Traditional manual drilling in hip fracture fixation poses risks of unstable fixation and vascular damage.
• Accurate intraoperative assessment of bone drilling states is crucial for successful surgical outcomes.

Purpose of the Study:

• To develop and evaluate a safe and user-friendly robot-assisted system for automated bone drilling during hip fracture fixation.
• To achieve real-time, high-accuracy identification of critical bone drilling states.

Main Methods:

• A robotic system was designed for automated femoral neck drilling in pig femurs.
• Vibrational data from a drill handle accelerometer were analyzed using Fast Fourier Transform (FFT).
• A neural network classifier was trained to distinguish five drilling states based on vibration frequency spectrum.

Main Results:

• Significant differences in harmonic distribution of drilling vibrations were observed across different drilling modes (p < 0.05).
• The system achieved average recognition accuracies exceeding 84% for identifying drilling states.
• High accuracies were reported for distinguishing specific states like 'in cancellous bone' (83.2-92.9%) and 'out the femoral neck' (88.4-98.2%).

Conclusions:

• The robot-assisted system accurately distinguishes critical bone drilling states in real-time.
• This technology offers a safer alternative to manual drilling, potentially preventing weak fixation and vascular injury.
• The findings support the clinical utility of automated drilling in hip fracture surgery.