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Precision forceps tracking and localisation using a Kalman filter for continuous curvilinear capsulorhexis.

Chuang Lin¹, Yu Zheng¹, Chenhan Guang¹

¹School of Mechanical Engineering and Automation, Beihang University, Beijing, China.

The International Journal of Medical Robotics + Computer Assisted Surgery : MRCAS

|June 9, 2022

Summary

This study introduces a Kalman filter-based method for precise robotic forceps tracking during continuous curvilinear capsulorhexis (CCC). The technique enhances surgical accuracy by fusing sensor and visual data for improved eye surgery performance.

Keywords:

Kalman filters data fusion real-time tracking

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Area of Science:

Ophthalmology
Robotics
Surgical Technology

Background:

Continuous curvilinear capsulorhexis (CCC) involves microscale manipulation of delicate eye tissues.
Surgeon's limited perceptual accuracy hinders precise forceps positioning during CCC.
Robotic assistance offers a promising solution to enhance CCC performance.

Purpose of the Study:

To develop a real-time, high-precision forceps tracking method for robotic capsulorhexis.
To extract expert surgical trajectories for autonomous or assisted robotic CCC.
To improve the accuracy and reliability of robotic eye surgery.

Main Methods:

A forceps tracking method utilizing Kalman filters for precise positioning.
Fusion of inertial sensor data and visual observation data for depth information.
Reduction of cumulative errors in inertial sensor data through data fusion.

Main Results:

Experimental validation on an eye phantom demonstrated the method's effectiveness.
The proposed method achieved an average processing speed of 62.8 frames per second.
Accurate forceps tip localization within 25 μm was achieved.

Conclusions:

The developed method accurately locates the surgical tool tip.
Efficient extraction of expert surgical trajectories for robotic planning was confirmed.