Fiber bragg gratings for medical applications and future challenges: A review

In the last decades, fiber Bragg gratings (FBGs) have become increasingly attractive to medical applications due to their unique properties such as small size, biocompatibility, immunity to electromagnetic interferences, high sensitivity and multiplexing capability. FBGs have been employed in the development of surgical tools, assistive devices, wearables, and biosensors, showing great potentialities for medical uses. This paper reviews the FBG-based measuring systems, their principle of work, and their applications in medicine and healthcare. Particular attention is given to sensing solutions for biomechanics, minimally invasive surgery, physiological monitoring, and medical biosensing. Strengths, weaknesses, open challenges, and future trends are also discussed to highlight how FBGs can meet the demands of next-generation medical devices and healthcare system

Fiber Bragg Gratings for Medical Applications and Future Challenges: A Review

[EN] In the last decades, fiber Bragg gratings (FBGs) have become increasingly attractive to medical applications due to their unique properties such as small size, biocompatibility, immunity to electromagnetic interferences, high sensitivity and multiplexing capability. FBGs have been employed in the development of surgical tools, assistive devices, wearables, and biosensors, showing great potentialities for medical uses. This paper reviews the FBG-based measuring systems, their principle of work, and their applications in medicine and healthcare. Particular attention is given to sensing solutions for biomechanics, minimally invasive surgery, physiological monitoring, and medical biosensing. Strengths, weaknesses, open challenges, and future trends are also discussed to highlight how FBGs can meet the demands of next-generation medical devices and healthcare system.This work was supported in part by INAIL (the Italian National Institute for Insurance against Accident at Work), through the BRIC (Bando ricerche in collaborazione) 2018 SENSE-RISC (Sviluppo di abiti intelligENti Sensorizzati per prevenzione e mitigazione di Rischi per la SiCurezza dei lavoratori) Project under Grant ID10/2018, in part by the UCBM (Universita Campus Bio-Medico di Roma) under the University Strategic HOPE (HOspital to the PatiEnt) Project, in part by the EU Framework Program H2020-FETPROACT-2018-01 NeuHeart Project under Grant GA 824071, by FCT/MEC (Fundacao para a Ciencia e Tecnologia) under the Projects UIDB/50008/2020 - UIDP/50008/2020, and by REACT (Development of optical fiber solutions for Rehabilitation and e-Health applications) FCT-IT-LA scientific action.Lo Presti, D.; Massaroni, C.; Leitao, CSJ.; Domingues, MDF.; Sypabekova, M.; Barrera, D.; Floris, I.... (2020). Fiber Bragg Gratings for Medical Applications and Future Challenges: A Review. IEEE Access. 8:156863-156888. https://doi.org/10.1109/ACCESS.2020.3019138S156863156888

Functional mimicry of Ruffini receptors with fibre Bragg gratings and deep neural networks enables a bio-inspired large-area tactile-sensitive skin

Collaborative robots are expected to physically interact with humans in daily living and the workplace, including industrial and healthcare settings. A key related enabling technology is tactile sensing, which currently requires addressing the outstanding scientific challenge to simultaneously detect contact location and intensity by means of soft conformable artificial skins adapting over large areas to the complex curved geometries of robot embodiments. In this work, the development of a large-area sensitive soft skin with a curved geometry is presented, allowing for robot total-body coverage through modular patches. The biomimetic skin consists of a soft polymeric matrix, resembling a human forearm, embedded with photonic fibre Bragg grating transducers, which partially mimics Ruffini mechanoreceptor functionality with diffuse, overlapping receptive fields. A convolutional neural network deep learning algorithm and a multigrid neuron integration process were implemented to decode the fibre Bragg grating sensor outputs for inference of contact force magnitude and localization through the skin surface. Results of 35 mN (interquartile range 56 mN) and 3.2 mm (interquartile range 2.3 mm) median errors were achieved for force and localization predictions, respectively. Demonstrations with an anthropomorphic arm pave the way towards artificial intelligence based integrated skins enabling safe human–robot cooperation via machine intelligence

Recent developments in fibre optic shape sensing

This paper presents a comprehensive critical review of technologies used in the development of fibre optic shape sensors (FOSSs). Their operation is based on multi-dimensional bend measurements using a series of fibre optic sensors. Optical fibre sensors have experienced tremendous growth from simple bend sensors in 1980s to full three-dimensional FOSSs using multicore fibres in recent years. Following a short review of conventional contact-based shape sensor technologies, the evolution trend and sensing principles of FOSSs are presented. This paper identifies the major optical fibre technologies used for shape sensing and provides an account of the challenges and emerging applications of FOSSs in various industries such as medical robotics, industrial robotics, aerospace and mining industry

Organ Shape Sensing using Pneumatically Attachable Flexible Rails in Robotic-Assisted Laparoscopic Surgery

In robotic-assisted partial nephrectomy, surgeons remove a part of a kidney often due to the presence of a mass. A drop-in ultrasound probe paired to a surgical robot is deployed to execute multiple swipes over the kidney surface to localise the mass and define the margins of resection. This sub-task is challenging and must be performed by a highly skilled surgeon. Automating this sub-task may reduce cognitive load for the surgeon and improve patient outcomes. The overall goal of this work is to autonomously move the ultrasound probe on the surface of the kidney taking advantage of the use of the Pneumatically Attachable Flexible (PAF) rail system, a soft robotic device used for organ scanning and repositioning. First, we integrate a shape-sensing optical fibre into the PAF rail system to evaluate the curvature of target organs in robotic-assisted laparoscopic surgery. Then, we investigate the impact of the stiffness of the material of the PAF rail on the curvature sensing accuracy, considering that soft targets are present in the surgical field. Finally, we use shape sensing to plan the trajectory of the da Vinci surgical robot paired with a drop-in ultrasound probe and autonomously generate an Ultrasound scan of a kidney phantom.Comment: 9 pages, 11 figure

Development of a fiber-based shape sensor for navigating flexible medical tools

Robot-assisted minimally invasive surgical procedure (RAMIS) is a subfield of minimally invasive surgeries with enhanced manual dexterity, manipulability, and intraoperative image guidance. In typical robotic surgeries, it is common to use rigid instruments with functional articulating tips. However, in some operations where no adequate and direct access to target anatomies is available, continuum robots can be more practical, as they provide curvilinear and flexible access. However, their inherent deformable design makes it difficult to accurately estimate their 3D shape during the operation in real-time. Despite extensive model-based research that relies on kinematics and mechanics, accurate shape sensing of continuum robots remains challenging. The state-of-the-art tracking technologies, including optical trackers, EM tracking systems, and intraoperative imaging modalities, are also unsuitable for this task, as they all have shortcomings. Optical fiber shape sensing solutions offer various advantages compared to other tracking modalities and can provide high-resolution shape measurements in real-time. However, commercially available fiber shape sensors are expensive and have limited accuracy. In this thesis, we propose two cost-effective fiber shape sensing solutions based on multiple single-mode fibers with FBG (fiber Bragg grating) arrays and eccentric FBGs. First, we present the fabrication and calibration process of two shape sensing prototypes based on multiple single-mode fibers with semi-rigid and super-elastic substrates. Then, we investigate the sensing mechanism of edge-FBGs, which are eccentric Bragg gratings inscribed off-axis in the fiber's core. Finally, we present a deep learning algorithm to model edge-FBG sensors that can directly predict the sensor's shape from its signal and does not require any calibration or shape reconstruction steps. In general, depending on the target application, each of the presented fiber shape sensing solutions can be used as a suitable tracking device. The developed fiber sensor with the semi-rigid substrate has a working channel in the middle and can accurately measure small deflections with an average tip error of 2.7 mm. The super-elastic sensor is suitable for measuring medium to large deflections, where a centimeter range tip error is still acceptable. The tip error in such super-elastic sensors is higher compared to semi-rigid sensors (9.9-16.2 mm in medium and large deflections, respectively), as there is a trade-off between accuracy and flexibility in substrate-based fiber sensors. Edge-FBG sensor, as the best performing sensing mechanism among the investigated fiber shape sensors, can achieve a tip accuracy of around 2 mm in complex shapes, where the fiber is heavily deflected. The developed edge-FBG shape sensing solution can compete with the state-of-the-art distributed fiber shape sensors that cost 30 times more

Fiber Bragg Gratings as e-Health Enablers: An Overview for Gait Analysis Applications

Nowadays, the fast advances in sensing technologies and ubiquitous wireless networking are reflected in medical practice. It provides new healthcare advantages under the scope of e-Health applications, enhancing life quality of citizens. The increase of life expectancy of current population comes with its challenges and growing health risks, which include locomotive problems. Such impairments and its rehabilitation require a close monitoring and continuous evaluation, which add financial burdens on an already overloaded healthcare system. Analysis of body movements and gait pattern can help in the rehabilitation of such problems. These monitoring systems should be noninvasive and comfortable, in order to not jeopardize the mobility and the day-to-day activities of citizens. The use of fiber Bragg gratings (FBGs) as e-Health enablers has presented itself as a new topic to be investigated, exploiting the FBGs’ advantages over its electronic counterparts. Although gait analysis has been widely assessed, the use of FBGs in biomechanics and rehabilitation is recent, with a wide field of applications. This chapter provides a review of the application of FBGs for gait analysis monitoring, namely its use in topics such as the monitoring of plantar pressure, angle, and torsion and its integration in rehabilitation exoskeletons and for prosthetic control

Utilizing Compliance To Address Modern Challenges in Robotics

Mechanical compliance will be an essential component for agile robots as they begin to leave the laboratory settings and join our world. The most crucial finding of this dissertation is showing how lessons learned from soft robotics can be adapted into traditional robotics to introduce compliance. Therefore, it presents practical knowledge on how to build soft bodied sensor and actuation modules: first example being soft-bodied curvature sensors. These sensors contain both standard electronic components soldered on flexible PCBs and hyperelastic materials that cover the electronics. They are built by curing multi-material composites inside hyper elastic materials. Then it shows, via precise sensing by using magnets and Hall-effect sensors, how closed-loop control of soft actuation modules can be achieved via proprioceptive feedback. Once curvature sensing idea is verified, the dissertation describes how the same sensing methodology, along with the same multi-material manufacturing technique can be utilized to construct soft bodied tri-axial force sensors. It shows experimentally that these sensors can be used by traditional robotic grippers to increase grasping quality. At this point, I observe that compliance is an important property that robots may utilize for different types of motions. One example being Raibert\u27s 2D hopper mechanism. It uses its leg-spring to store energy while on the ground and release this energy before jumping. I observe that via soft material design, it would be possible to embed compliance directly into the linkage design itself. So I go over the design details of an extremely lightweight compliant five-bar mechanism design that can store energy when compressed via soft ligaments embedded in its joints. I experimentally show that the compliant leg design offers increased efficiency compared to a rigid counterpart. I also utilize the previously mentioned soft bodied force sensors for rapid contact detection (~5-10 Hz) in the hopper test platform. In the end, this thesis connects soft robotics with the traditional body of robotic knowledge in two aspects: a) I show that manufacturing techniques we use for soft bodied sensor/actuator designs can be utilized for creating soft ligaments that add strength and compliance to robot joints; and b) I demonstrate that soft bodied force sensing techniques can be used reliably for robotic contact detection

Intra-Operative Needle Tracking Using Optical Shape Sensing Technology

RÉSUMÉ Contexte : Les métastases hépatiques colorectales sont la principale cause de décès liée au cancer du foie dans le monde. Au cours de la dernière décennie, il a été démontré que l’ablation par radiofréquence (RFA, pour radiofrequency ablation) est une méthode de traitement percutané très efficace contre ce type de métastases. Cela dit, un positionnement précis de l’embout de l’aiguille utilisé en RFA est essentiel afin de se départir adéquatement de la totalité des cellules cancéreuses. Une technologie prometteuse pour obtenir la forme et la position de l’aiguille en temps réel est basée sur l’utilisation de réseaux de Bragg (FBG, pour fiber Bragg grating) à titre de senseur de contrainte. En effet, ce type de senseurs a une vitesse d’acquisition allant jusqu’à 20 kHz, ce qui est suffisamment rapide pour permettre des applications de guidage en temps réel. Méthode : Les travaux présentés au sein de ce mémoire décrivent le développement d’une technologie, compatible aux systèmes d’imageries par résonance magnétique (IRM), permettant d’effectuer le suivi de la forme de l’aiguille utilisée en RFA. Premièrement, trois fibres contenant une série de réseaux de Bragg ont été collées dans une géométrie spécifique et intégrées à l’intérieur d’une aiguille 20G-150 mm. Ensuite, un algorithme de reconstruction de forme tridimensionnelle a été développé, basé sur les mesures de translation spectrales des FBGs acquises en temps réel durant le guidage de l’aiguille. La position du bout de l’aiguille ainsi que la forme tridimensionnelle complète de celle-ci ont été représentées et comparées à la position de la zone ciblée à la suite d’une simple méthode de calibration. Finalement, nous avons validé notre système de navigation en effectuant une série d’expériences in vitro. La précision du système de reconstruction tridimensionnelle de la forme et de l’orientation de l’aiguille a été évaluée en utilisant deux caméras positionnées perpendiculairement de manière à connaitre la position de l’aiguille dans le système d’axes du laboratoire. L’évaluation de la précision au bout de l’aiguille a quant à elle été faite en utilisant des fantômes précisément conçus à cet effet. Finalement, des interventions guidées en IRM ont été testées et comparées au système de navigation électromagnétique NDI Aurora (EMTS, pour Electromagnétic tracking system) par le biais du FRE (fiducial registration error) et du TRE (target registration error). Résultats: Lors de nos premières expériences in vitro, la précision obtenue quant à la position du bout de l’aiguille était de 0,96 mm pour une déflexion allant jusqu’à ±10,68 mm. À titre comparatif, le système d’Aurora a une précision de 0.84 mm dans des circonstances similaires. Les résultats obtenus lors de nos seconds tests ont démontré que l’erreur entre la position réelle du bout de l’aiguille et la position fournie par notre système de reconstruction de forme est de 1,04 mm, alors qu’elle est de 0,82 mm pour le EMTS d’Aurora. Pour ce qui est de notre dispositif, cette erreur est proportionnelle à l’amplitude de déflexion de l’aiguille, contrairement à l’EMTS pour qui l’erreur demeure relativement constante. La dernière expérience a été effectuée à l’aide d’un fantôme en gélatine, pour laquelle nous avons obtenu un TRE de 1,19 mm pour notre système basé sur les FBG et de 1.06 mm pour le système de navigation par senseurs électromagnétiques (EMTS). Les résultats démontrent que l’évaluation du FRE est similaire pour les deux approches. De plus, l’information fournie par les caméras permet d’estimer la précision de notre dispositif en tout point le long de l’aiguille. Conclusion : En analysant et en interprétant les résultats obtenus lors de nos expériences in vitro, nous pouvons conclure que la précision de notre système de navigation basé sur les FBG est bien adaptée pour l’évaluation de la position du bout et la forme de l’aiguille lors d’interventions RFA des tumeurs du foie. La précision de notre système de navigation est fortement comparable avec celle du système basé sur des senseurs électromagnétiques commercialisé par Aurora. L’erreur obtenue par notre système est attribuable à un mauvais alignement des réseaux de Bragg par rapport au plan associé à la région sensorielle et aussi à la différence entre le diamètre des fibres et celui de la paroi interne de l’aiguille.----------ABSTRACT Background: Colorectal liver metastasis is the leading cause of liver cancer death in the world. In the past decade, radiofrequency ablation (RFA) has proven to be an effective percutaneous treatment modality for the treatment of metastatic hepatic cancer. Accurate needle tip placement is essential for RFA of liver tumors. A promising technology to obtain the real-time information of the shape of the needle is by using fiber Bragg grating (FBG) sensors at high frequencies (up to 20 kHz). Methods: In this thesis work, we developed an MR-compatible needle tracking technology designed for RFA procedures in liver cancer. At first, three fibers each containing a series of FBGs were glued together and integrated inside a 20G-150 mm needle. Then a three-dimensional needle shape reconstruction algorithm was developed, based on the FBG measurements collected in real-time during needle guidance. The tip position and shape of the reconstructed 3D needle model were represented with respect to the target defined in the image space by performing a fiducial-based registration. Finally, we validated our FBG-based needle navigation by doing a series of in-vitro experiments. The shape of the 3D reconstructed needle was compared to measurements obtained from camera images. In addition, the needle tip accuracy was assessed on the ground-truth phantoms. Finally, MRI guided intervention was tested and compared to an NDI Aurora EM tracking system (EMTS) in terms of fiducial registration error (FRE) and target registration error (TRE). Results: In our first in-vitro experiment, the tip tracking accuracy of our FBG tracking system was of 0.96 mm for the maximum tip deflection of up to ±10.68 mm, while the tip tracking accuracy of the Aurora system for the similar test was 0.84 mm. Results obtained from the second in-vitro experiment demonstrated tip tracking accuracy of 1.04 mm and 0.82 mm for our FBG tracking system and Aurora EMTS, respectively for the maximum tip deflection of up to ±16.83 mm. The tip tracking error in the developed FBG-based system reduced linearly with decreasing tip deflection, while the error was similar but randomly varying for the EMTS. The last experiment was done with a gel phantom, yielding a TRE of 1.19 mm and 1.06 mm for the FBG and EM tracking, respectively. Results showed that across all experiments, the computed FRE of both tracking systems was similar. Moreover, actual shape information obtained from the camera images ensured the shape accuracy of our FBG-based needle shape model. Conclusion: By analyzing and interpreting the results obtained from the in-vitro experiments, we conclude that the accuracy of our FBG-based tracking system is suitable for needle tip detection in RFA of liver tumors. The accuracy of our tracking system is nearly comparable to that of the Aurora EMTS. The error given by our tracking system is attributed to the misalignment of the FBG sensors in a single axial plane and also to the gap between the needle's inner wall and the fibers inside