Respiratory motion compensation for the robot-guided laser osteotome

Area of Science:

• Medical Robotics
• Surgical Technology
• Biomedical Engineering

Background:

• Respiration-induced thoracic motion causes inaccuracies in robot-guided laser osteotomy for median sternotomy.
• Current methods lack precision due to uncompensated patient movement during procedures.

Purpose of the Study:

• To introduce novel 3D functional cuts and a respiratory motion compensation algorithm for the computer-assisted and robot-guided laser osteotome, CARLO®.
• To enhance precision in robot-guided laser sternotomy by addressing respiratory motion.

Main Methods:

• Development of a trajectory planning algorithm for 3D functional cuts at constant velocity.
• Implementation of Gaussian process (GP) prediction to anticipate sternal pose for real-time laser source adjustment.
• Simulation-based analysis of the CARLO® device with and without the proposed algorithms.

Main Results:

• The median position error of the laser focal point was reduced from 0.22 mm to 0.19 mm with GP prediction.
• Simulation results demonstrated the effectiveness of the respiratory motion compensation algorithm.

Conclusions:

• The proposed algorithm effectively compensates for respiration-induced motion in robot-guided laser osteotomy.
• This advancement enables novel functional cutting patterns, potentially improving sternal stability, reducing patient pain, and shortening recovery times.
• The technology represents a significant step towards advanced osteotomy techniques beyond traditional linear cuts.