Femtosecond laser processing of evanescence field coupled waveguides in single mode glass fibers for optical 3D shape sensing and navigation

Waltermann, Christian; Baumann, Anna Lena; Bethmann, Konrad; Doering, Alexander; Koch, Jan; Angelmahr, Martin; Schade, Wolfgang

doi:10.1117/12.2183334

Cited by 4 publications

(2 citation statements)

References 11 publications

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“…an average error of 1.13 mm for a 38 cm long sensor [19]). However, the cost of such systems is quite high, as a multichannel interrogator and a fan-out device would be needed for reading the signal from each core [24,25].…”

Section: Introductionmentioning

confidence: 99%

Shape sensing of optical fiber Bragg gratings based on deep learning

Roodsari

Huck-Horvath

Freund

et al. 2023

Mach. Learn.: Sci. Technol.

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Continuum robots in robot-assisted minimally invasive surgeries provide adequate access to target anatomies that are not directly reachable through small incisions. Achieving precise and reliable shape estimation of such snake-like manipulators necessitates an accurate navigation system, that requires no line-of-sight and is immune to electromagnetic noise. Fiber Bragg Grating (FBG) shape sensing, particularly eccentric FBG (eFBG), is a promising and cost-effective solution for this task. However, in eFBG sensors, the spectral intensity of the Bragg wavelengths that carries the strain information can be affected by undesired bending-induced phenomena, making standard characterization techniques less suitable for these sensors. We showed in our previous work that a deep learning model has the potential to extract the strain information from the eFBG sensor's spectrum and accurately predict its shape. In this paper, we conducted a more thorough investigation to find a suitable architectural design of the deep learning model to further increase shape prediction accuracy. We used the Hyperband algorithm to search for optimal hyperparameters in two steps. First, we limited the search space to layer settings of the network, from which, the best-performing configuration was selected. Then, we modified the search space for tuning the training and loss calculation hyperparameters. We also analyzed various data transformations on the network's input and output variables, as data rescaling can directly influence the model's performance. Additionally, we performed discriminative training using the Siamese network architecture that employs two CNNs with identical parameters to learn similarity metrics between the spectra of similar target values. The best-performing network architecture among all evaluated configurations can predict the shape of a 30cm long sensor with a median tip error of 3.11mm in a curvature range of 1.4m−1 to 35.3m−1.

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Section: Introductionmentioning

confidence: 99%

Shape sensing of optical fiber Bragg gratings based on deep learning

Roodsari

Huck-Horvath

Freund

et al. 2023

Mach. Learn.: Sci. Technol.

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“…However, due to the short distance between the sensing elements and the neutral axis (often less than 100 μm), the sensor can only detect deformations with bending radii below 10 cm [8], and therefore, are limited to the applications where only large deflections are expected. At the same time, the cost of such systems is high [9] due to the optical frequency domain reflectometer (OFDR) used for FBG interrogation [10] and a fan-out device to read out the signal from the cores [11].…”

Section: Introductionmentioning

confidence: 99%

Fabrication and Characterization of a Flexible FBG-Based Shape Sensor Using Single-Mode Fibers

Roodsari

Freund

Zam

et al. 2022

IEEE Trans. Biomed. Eng.

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Minimally invasive surgical procedures have become the preferable option, as the recovery period and the risk of infections are significantly lower than traditional surgeries. However, the main challenge in using flexible tools for minimal surgical interventions is the lack of precise feedback on their shape and tip position inside the patient's body. Shape sensors based on fiber Bragg gratings (FBGs) can provide accurate shape information depending on their design. One of the most common configurations in FBG-based shape sensors is to attach three single-mode optical fibers with arrays of FBGs in a triangular fashion around a substrate. Usually, the selected substrates dominate the bending stiffness of the sensor probe, as they have a larger diameter and show less flexibility compared to the optical fibers. Although sensors with this configuration can accurately estimate the shape, they cannot be implemented in flexible endoscopes where large deflections are expected.This paper investigates the shape sensor's performance when using a superelastic substrate with a small diameter instead of a substrate with dominating bending stiffness. A generalized model is also designed for characterizing this type of flexible FBG-based shape sensor. Moreover, we evaluated the sensor in single and multi-bend deformations using two shape reconstruction methods.

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Distributed fiber optics strain sensors: from long to short distance

Blanc¹,

Schenato²,

Molardi³

et al. 2022

Comptes Rendus. Géoscience

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Developed for more than forty years, optical fibers have features that make them particularly attractive for making sensors. One of the strengths of these sensors is that they can measure different physical parameters in a distributed manner over a wide range of lengths (from a few cm up to tens of kilometers) with a spatial resolution ranging from millimeters to meters. In this article, we are particularly interested in distributed fiber sensors, mainly based on light scattering processes, for measuring strain variations. This review concerns both applications requiring long lengths of fiber in a geological context, as well as those using length less than one meter for the medical sector. While distributed fiber optics sensors have already shown their great potential for long-range applications, short-range applications are a niche sector emerging in the last few years.Résumé. Développées depuis plus de quarante ans, les fibres optiques présentent des caractéristiques qui les rendent particulièrement attractives pour la réalisation de capteurs. L'un des points forts de ces capteurs est qu'ils peuvent mesurer différents paramètres physiques de manière distribuée sur une large gamme de longueurs (de quelques cm à des dizaines de kilomètres) avec une résolution spatiale allant du millimètre au mètre. Dans cet article, nous nous intéressons particulièrement aux capteurs

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Femtosecond laser processing of evanescence field coupled waveguides in single mode glass fibers for optical 3D shape sensing and navigation

Cited by 4 publications

References 11 publications

Shape sensing of optical fiber Bragg gratings based on deep learning

Shape sensing of optical fiber Bragg gratings based on deep learning

Fabrication and Characterization of a Flexible FBG-Based Shape Sensor Using Single-Mode Fibers

Distributed fiber optics strain sensors: from long to short distance

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