MCFBGs-based shape reconstruction capable for decoupling strain and temperature under minor temperature variations

Accurate needle navigation is crucial for the success of minimally invasive surgery. Recently, fiber optic sensors (FOSs) are being increasingly employed for precise shape measurement. However, FOSs are susceptible to minor temperature variations, which can detrimentally impact the navigation accuracy. This work proposes a sophisticated strain-temperature decoupling method for improving the accuracy of shape reconstruction due to minor temperature variations. Based on the fiber Bragg grating model for bending and temperature, the shape reconstruction of multi-core fiber (MCF) is established. A strain-temperature sensitivity matrix is introduced in the Frenet–Serret frame with an eight-node MCF sensor array. The experiments are conducted using an eight-node MCF sensor array, calibrated for shape measurement over a temperature range of 18–42 °C, i.e. surgical temperature conditions. Through compensation, the maximum relative error of the end coordinate is notably reduced from 2.20 to 0.65%. To verify the effectiveness of the mentioned method, a 3D shape reconstruction experiment is also carried, and the maximum is 0.2238 mm. The experimental results affirm the efficacy of the proposed approach in improving the reconstruction accuracy amidst minor temperature variations, thus offering valuable insights for achieving high precision in minimally invasive surgical environments.