Hybrid attitude estimation for laparoscopic surgical tools: a preliminary study

Area of Science:

• Medical Robotics
• Surgical Navigation Systems
• Sensor Fusion

Background:

• Real-time tracking of surgical tools is crucial for effective laparoscopic surgery.
• Metal objects in the surgical field can distort electromagnetic navigation signals, hindering intraoperative accuracy.

Purpose of the Study:

• To develop a hybrid tracking system for continuous and accurate intraoperative localization of surgical tools.
• To overcome signal distortion issues in electromagnetic navigation during minimally invasive procedures.

Main Methods:

• A hybrid tracking system integrating a miniature inertial measurement unit (IMU) and an electromagnetic navigation (EMN) system was developed.
• An extended Kalman filter (EKF) was employed for sensor fusion, utilizing a quaternion-based formulation for system dynamics.
• The system aimed to provide continuous orientation information even in the presence of metallic interference.

Main Results:

• Preliminary experiments demonstrated the feasibility of the sensor fusion approach.
• The integration of low-cost inertial measurement unit data effectively compensated for distortions in the electromagnetic tracking signal.
• Continuous orientation tracking was achieved despite the presence of metal objects.

Conclusions:

• The proposed sensor fusion method offers a robust solution for real-time surgical tool tracking in laparoscopic surgery.
• Hybrid tracking systems combining IMUs and EMN can enhance the reliability and accuracy of navigation in challenging surgical environments.