Error Analysis of FBG-Based Shape Sensors for Medical Needle Tracking

Robotic needle steering requires accurate spatial information about the needle tip. Presumably, fiber Bragg gratings (FBGs) can provide this information at an appropriate update rate. We performed an extensive error analysis to quantify the accuracy of needle tip tracking with FBGs and to assess the suitability of this method for robotic needle steering. An FBG-based shape sensing model was determined and simulations were performed to quantify the effect of design parameters on the position accuracy. Inputs that were investigated include accuracy of wavelength measurement and sensor geometry as well as different sensor configurations and interpolation models. For the purpose of validation of the simulations, two needles with two different configurations of FBGs were built and evaluated. The simulations show that the accuracy of FBG-based shape sensing of a needle can be in the order of 10% of the deflection at the tip, depending on the configuration. However, tip deflections that are smaller than approximately 1 mm cannot be detected accurately. Calibration of the needle reduces the bias, but does not improve the accuracy, because of drift in read-out of the FGBs. The analysis shows that the combined sources of errors limit the accuracy of tip estimation to approximately 1 mm, although the accuracy is influenced by the sensor configuration as well. This accuracy is suitable for common medical applications like taking biopsies or performing ablation.