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Al-Ahmad O, Ourak M, Vlekken J, Lindner E, Vander Poorten E. Three-dimensional catheter tip force sensing using multi-core fiber Bragg gratings. Front Robot AI 2023; 10:1154494. [PMID: 36968129 PMCID: PMC10031093 DOI: 10.3389/frobt.2023.1154494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 02/21/2023] [Indexed: 03/11/2023] Open
Abstract
Awareness of catheter tip interaction forces is a crucial aspect during cardiac ablation procedures. The most important contact forces are the ones that originate between the catheter tip and the beating cardiac tissue. Clinical studies have shown that effective ablation occurs when contact forces are in the proximity of 0.2 N. Lower contact forces lead to ineffective ablation, while higher contact forces may result in complications such as cardiac perforation. Accurate and high resolution force sensing is therefore indispensable in such critical situations. Accordingly, this work presents the development of a unique and novel catheter tip force sensor utilizing a multi-core fiber with inscribed fiber Bragg gratings. A customizable helical compression spring is designed to serve as the flexural component relaying external forces to the multi-core fiber. The limited number of components, simple construction, and compact nature of the sensor makes it an appealing solution towards clinical translation. An elaborated approach is proposed for the design and dimensioning of the necessary sensor components. The approach also presents a unique method to decouple longitudinal and lateral force measurements. A force sensor prototype and a dedicated calibration setup are developed to experimentally validate the theoretical performance. Results show that the proposed force sensor exhibits 7.4 mN longitudinal resolution, 0.8 mN lateral resolution, 0.72 mN mean longitudinal error, 0.96 mN mean lateral error, a high repeatability, and excellent decoupling between longitudinal and lateral forces.
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Affiliation(s)
- Omar Al-Ahmad
- Robot-Assisted Surgery (RAS) group, Department of Mechanical Engineering, KU Leuven University, Leuven, Belgium
- FBGS International NV, Geel, Belgium
- *Correspondence: Omar Al-Ahmad ,
| | - Mouloud Ourak
- Robot-Assisted Surgery (RAS) group, Department of Mechanical Engineering, KU Leuven University, Leuven, Belgium
| | | | | | - Emmanuel Vander Poorten
- Robot-Assisted Surgery (RAS) group, Department of Mechanical Engineering, KU Leuven University, Leuven, Belgium
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2
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Curvature-based force estimation for an elastic tube. ROBOTICA 2023. [DOI: 10.1017/s0263574723000115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/15/2023]
Abstract
Abstract
Contact force is one of the most significant feedback for robots to achieve accurate control and safe interaction with environment. For continuum robots, it is possible to estimate the contact force based on the feedback of robot shapes, which can address the difficulty of mounting dedicated force sensors on the continuum robot body with strict dimension constraints. In this paper, we use local curvatures to estimate the magnitude and location of single or multiple contact forces based on Cosserat rod theory. We validate the proposed method in a thin elastic tube and calculate the curvatures via Fiber Bragg Grating (FBG) sensors or image feedback. For the curvature feedback obtained from multicore FBG sensors, the overall force magnitude estimation error is
$0.062 \pm 0.068$
N and the overall location estimation error is
$3.51 \pm 2.60$
mm. For the curvature feedback obtained from image, the overall force magnitude estimation error is
$0.049 \pm 0.048$
N and the overall location estimation error is
$2.75 \pm 1.71$
mm. The results demonstrate that the curvature-based force estimation method is able to accurately estimate the contact force.
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3
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Lezcano DA, Iordachita II, Kim JS. Lie-Group Theoretic Approach to Shape-Sensing Using FBG-Sensorized Needles Including Double-Layer Tissue and S-Shape Insertions. IEEE SENSORS JOURNAL 2022; 22:22232-22243. [PMID: 37216067 PMCID: PMC10193911 DOI: 10.1109/jsen.2022.3212209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Flexible bevel-tipped needles are often used for needle insertion in minimally-invasive surgical techniques due to their ability to be steered in cluttered environments. Shapesensing enables physicians to determine the location of needles intra-operatively without requiring radiation of the patient, enabling accurate needle placement. In this paper, we validate a theoretical method for flexible needle shape-sensing that allows for complex curvatures, extending upon a previous sensor-based model. This model combines curvature measurements from fiber Bragg grating (FBG) sensors and the mechanics of an inextensible elastic rod to determine and predict the 3D needle shape during insertion. We evaluate the model's shape sensing capabilities in C- and S-shape insertions in single-layer isotropic tissue, and C-shape insertions in two-layer isotropic tissue. Experiments on a four-active area, FBG-sensorized needle were performed in varying tissue stiffnesses and insertion scenarios under stereo vision to provide the 3D ground truth needle shape. The results validate a viable 3D needle shape-sensing model accounting for complex curvatures in flexible needles with mean needle shape sensing root-mean-square errors of 0.160 ± 0.055 mm over 650 needle insertions.
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Affiliation(s)
- Dimitri A Lezcano
- Mechanical Engineering Department, Johns Hopkins University, MD 21201 USA
| | | | - Jin Seob Kim
- Mechanical Engineering Department, Johns Hopkins University, MD 21201 USA
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Zhou C, Lin Z, Huang S, Li B, Gao A. Progress in Probe-Based Sensing Techniques for In Vivo Diagnosis. BIOSENSORS 2022; 12:943. [PMID: 36354452 PMCID: PMC9688418 DOI: 10.3390/bios12110943] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 10/13/2022] [Accepted: 10/24/2022] [Indexed: 06/16/2023]
Abstract
Advancements in robotic surgery help to improve the endoluminal diagnosis and treatment with minimally invasive or non-invasive intervention in a precise and safe manner. Miniaturized probe-based sensors can be used to obtain information about endoluminal anatomy, and they can be integrated with medical robots to augment the convenience of robotic operations. The tremendous benefit of having this physiological information during the intervention has led to the development of a variety of in vivo sensing technologies over the past decades. In this paper, we review the probe-based sensing techniques for the in vivo physical and biochemical sensing in China in recent years, especially on in vivo force sensing, temperature sensing, optical coherence tomography/photoacoustic/ultrasound imaging, chemical sensing, and biomarker sensing.
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Affiliation(s)
- Cheng Zhou
- Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai 200240, China
- Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Zecai Lin
- Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai 200240, China
- Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Shaoping Huang
- Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai 200240, China
- Department of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Bing Li
- Institute for Materials Discovery, University College London, London WC1E 7JE, UK
| | - Anzhu Gao
- Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai 200240, China
- Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China
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5
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Aloi V, Dang KT, Barth EJ, Rucker C. Estimating Forces Along Continuum Robots. IEEE Robot Autom Lett 2022. [DOI: 10.1109/lra.2022.3188905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Vincent Aloi
- Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, TN, USA
| | - Khoa T. Dang
- Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, TN, USA
| | - Eric J. Barth
- Department of Mechanical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Caleb Rucker
- Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, TN, USA
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Ha XT, Wu D, Lai CF, Ourak M, Borghesan G, Menciassi A, Poorten EV. Contact Localization of Continuum and Flexible Robot Using Data-Driven Approach. IEEE Robot Autom Lett 2022. [DOI: 10.1109/lra.2022.3176723] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Affiliation(s)
- Xuan Thao Ha
- Department of Mechanical Engineering, KU Leuven, Leuven, Belgium
| | - Di Wu
- Department of Mechanical Engineering, KU Leuven, Leuven, Belgium
| | | | - Mouloud Ourak
- Department of Mechanical Engineering, KU Leuven, Leuven, Belgium
| | - Gianni Borghesan
- Department of Mechanical Engineering, KU Leuven, Leuven, Belgium
| | - Arianna Menciassi
- The BioRobotics Institute, Scuola Superiore Sant–Anna, Pontedera, Italy
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7
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3D Curvature-Based Tip Load Estimation for Continuum Robots. IEEE Robot Autom Lett 2022. [DOI: 10.1109/lra.2022.3194680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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8
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Rao P, Peyron Q, Burgner-Kahrs J. Shape Representation and Modeling of Tendon-Driven Continuum Robots Using Euler Arc Splines. IEEE Robot Autom Lett 2022. [DOI: 10.1109/lra.2022.3185377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Priyanka Rao
- Continuum Robotics Laboratory, Department of Mathematical & Computational Sciences, University of Toronto, Toronto, ON, Canada
| | - Quentin Peyron
- Continuum Robotics Laboratory, Department of Mathematical & Computational Sciences, University of Toronto, Toronto, ON, Canada
| | - Jessica Burgner-Kahrs
- Continuum Robotics Laboratory, Department of Mathematical & Computational Sciences, University of Toronto, Toronto, ON, Canada
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