Image-based Force Localization and Estimation of a Micro-scale Continuum Guidewire Robot.

Area of Science:

• Medical Robotics
• Biomechanical Engineering
• Surgical Navigation

Background:

• Intravascular procedures rely on guidewires, posing risks of vessel damage due to limited control.
• Current guidewire technology lacks precise force feedback, hindering accurate navigation and increasing complication risks.
• Robotic guidewires offer potential for improved steerability and intrinsic force sensing, but face challenges in sensor integration and force distribution interpretation.

Purpose of the Study:

• To develop and validate a method for estimating and localizing forces along a micro-scale robotic guidewire.
• To enhance the accuracy of force sensing by incorporating models for friction and hysteresis.
• To improve the safety and efficacy of intravascular interventions through advanced guidewire control.

Main Methods:

• Utilized image feedback and a Cosserat rod model for force estimation and localization.
• Developed a micro-scale tendon-driven guidewire robot.
• Incorporated models for friction and hysteresis into the force sensing framework.
• Tested the model on nitinol tubes under gravity loading.

Main Results:

• Achieved an average Root Mean Square Error (RMSE) of 0.46 mm for shape predictions.
• Friction and hysteresis compensation improved shape prediction RMSE to 1.22 mm for 180° bends, outperforming the uncompensated model (1.62 mm RMSE).
• Localized forces with an average error of 4.79 mm (5.15% of length) and estimated magnitudes with an average error of 13.03 mN.

Conclusions:

• The presented image-guided Cosserat rod model effectively estimates and localizes forces on a micro-scale robotic guidewire.
• Modeling friction and hysteresis significantly enhances the accuracy of shape and force predictions.
• This technology holds promise for improving control and safety in minimally invasive intravascular procedures.