Design and analysis of a fiber-optic sensing system for shape reconstruction of a minimally invasive surgical needle

Issatayeva A. Amantayeva A. Blanc W. Tosi D. Molardi C.
December 2021 Nature Research

Scientific Reports
2021 #11 Issue 1

This paper presents the performance analysis of the system for real-time reconstruction of the shape of the rigid medical needle used for minimally invasive surgeries. The system is based on four optical fibers glued along the needle at 90 degrees from each other to measure distributed strain along the needle from four different sides. The distributed measurement is achieved by the interrogator which detects the light scattered from each section of the fiber connected to it and calculates the strain exposed to the fiber from the spectral shift of that backscattered light. This working principle has a limitation of discriminating only a single fiber because of the overlap of backscattering light from several fibers. In order to use four sensing fibers, the Scattering-Level Multiplexing (SLMux) methodology is applied. SLMux is based on fibers with different scattering levels: standard single-mode fibers (SMF) and MgO-nanoparticles doped fibers with a 35–40 dB higher scattering power. Doped fibers are used as sensing fibers and SMFs are used to spatially separate one sensing fiber from another by selecting appropriate lengths of SMFs. The system with four fibers allows obtaining two pairs of opposite fibers used to reconstruct the needle shape along two perpendicular axes. The performance analysis is conducted by moving the needle tip from 0 to 1 cm by 0.1 cm to four main directions (corresponding to the locations of fibers) and to four intermediate directions (between neighboring fibers). The system accuracy for small bending (0.1–0.5 cm) is 90% and for large bending (0.6–1 cm) is approximately 92%.

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Department of Computer and Electrical Engineering, Nazarbayev University, Nur-Sultan, 010000, Kazakhstan
Université Côte d’Azur, INPHYNI-CNRS UMR 7010, Nice, 06108, France
National Laboratory of Astana, Laboratory of Biosensors and Bioinstruments, Nur-Sultan, 010000, Kazakhstan

Department of Computer and Electrical Engineering
Université Côte d’Azur
National Laboratory of Astana

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