Robotic Capsule Endoscope

IEEE Transactions on Robotics (2021): A Real-Time State Dependent Region Estimator for Autonomous Endoscope Navigation

Anonymous — Sat, 23 Jan 2021 22:02:32 +0000

IEEE Transactions on Robotics (2021): A Real-Time State Dependent Region Estimator for Autonomous Endoscope Navigation Anonymous (not verified) Sat, 01/23/2021 - 15:02

[video:https://youtu.be/2oollBj46h0]

Abstract: With significant progress being made toward improving endoscope technology such as capsule endoscopy and robotic endoscopy, the development of advanced strategies for manipulating, controlling, and more generally, easing the accessibility of these devices for physicians is an important next step. This article presents an autonomous navigation strategy for use in endoscopy, utilizing a state-dependent region estimation approach to allow for multimodal control design. This region estimator is evaluated for its accuracy in predicting yaw angle of the camera relative to the lumen center, and for estimating the location of the camera based on overall haustra morphology within the colon. To assess the utility of this region estimator, multimodal control is used to allow for autonomous navigation of the Endoculus, a robotic capsule endoscope, within a benchtop, to-scale, simulated colon. The estimation approach is presented and tested, demonstrating successful tracking of fixed velocity rotations at speeds up to 40 deg/s and allowing for curve anticipation approximately 10 cm before entering a curved section of the simulator. Finally, the multimodal control strategy utilizing this estimator is tested within the simulator over a variety of anatomic configurations. This strategy proves successful for navigation in both straight sections of this simulator and in tightly curved sections as small as 8 cm radius of curvature, with average velocities reaching 2.61 cm/s in straight sections and 0.99 cm/s in curved sections.

Prendergast, J.M., Formosa, G.A., Fulton, M.J., Heckman, C., Rentschler, M.E., “A Real-Time State Dependent Region Estimator for Autonomous Endoscope Navigation,” IEEE Transactions on Robotics.

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IEEE Transactions on Biomedical Engineering (2021): Enabling Autonomous Colonoscopy Intervention Using a Robotic Endoscope Platform

Anonymous — Sat, 23 Jan 2021 22:00:16 +0000

IEEE Transactions on Biomedical Engineering (2021): Enabling Autonomous Colonoscopy Intervention Using a Robotic Endoscope Platform Anonymous (not verified) Sat, 01/23/2021 - 15:00

[video:https://youtu.be/BC11BSpFhM4]

Abstract: Objective: Robotic endoscopes have the potential to dramatically improve endoscopy procedures, however current attempts remain limited due to mobility and sensing challenges and have yet to offer the full capabilities of traditional tools. Endoscopic intervention (e.g., biopsy) for robotic systems remains an understudied problem and must be addressed prior to clinical adoption. This paper presents an autonomous intervention technique onboard a Robotic Endoscope Platform (REP) using endoscopy forceps, an auto-feeding mechanism, and positional feedback. Methods: A workspace model is established for estimating tool position while a Structure from Motion (SfM) approach is used for target-polyp position estimation with the onboard camera and positional sensor. Utilizing this data, a visual system for controlling the REP position and forceps extension is developed and tested within multiple anatomical environments. Results: The workspace model demonstrates accuracy of 5.5% while the target-polyp estimates are within 5 mm of absolute error. This successful experiment requires only 15 seconds once the polyp has been located, with a success rate of 43% using a 1 cm polyp, 67% for a 2 cm polyp, and 81% for a 3 cm polyp. Conclusion: Workspace modeling and visual sensing techniques allow for autonomous endoscopic intervention and demonstrate the potential for similar strategies to be used onboard mobile robotic endoscopic devices. Significance: To the authors’ knowledge this is the first attempt at automating the task of colonoscopy intervention onboard a mobile robot. While the REP is not sized for actual procedures, these techniques are translatable to devices suitable for in vivo application.

Zhang, Q., Prendergast, J.M., Formosa, G.A., Fulton, M.J., Rentschler, M.E., “Enabling Autonomous Colonoscopy Intervention Using a Robotic Endoscope Platform,” IEEE Transactions on Biomedical Engineering.

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ASME Journal of Dynamic Systems, Measurement and Control (2021): Nonlinear Dynamic Modeling of a Robotic Endoscopy Platform on Synthetic Tissue Substrates

Anonymous — Sat, 23 Jan 2021 21:57:54 +0000

ASME Journal of Dynamic Systems, Measurement and Control (2021): Nonlinear Dynamic Modeling of a Robotic Endoscopy Platform on Synthetic Tissue Substrates Anonymous (not verified) Sat, 01/23/2021 - 14:57

Abstract: A scaled robotic endoscopy platform (REP) was previously developed to efficiently test new control schemes in a simulated colon environment. This article presents the derivation and tuning of a nonlinear model of the REP operating on various substrates. The modeling technique and novel empirical friction profiling demonstrated here are useful for a wide variety of devices interacting with unconventional substrates. The model is first derived from the REP drivetrain inertial characteristics, and then the interaction with synthetic tissue is quantified by an automated traction measurement system for multiple substrates. The resulting model is then used with ground-truth VICON and sensor data to optimize uncertain parameters by minimizing pose error over a variety of tests and substrates. The results show an average error reduction of 67% over all tests and substrates, with a worst-case 10% open-loop final position error. The success of these results proves a robust dynamic model of the REP and its tissue interactions without the need to model complex and computationally expensive viscoelastic material properties or discrete/nonlinear events such as stalling. The resulting model will be used to develop model-based feedback control for estimation, disturbance rejection, and autonomy for the REP in an actuated colon simulator.

Formosa, G.A., Prendergast, J.M., Humbert, J.S., Rentschler, M.E., “Nonlinear Dynamic Modeling of a Robotic Endoscopy Platform on Synthetic Tissue Substrates,” ASME Journal of Dynamic Systems, Measurement and Control. 143(1): 011005 (11 pages), 2021.

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IEEE International Conference on Intelligent Robots and Systems (IROS) (2020): Comparing Visual Odometry Systems in Actively Deforming Simulated Colon Environments

Anonymous — Sun, 23 Aug 2020 20:01:04 +0000

IEEE International Conference on Intelligent Robots and Systems (IROS) (2020): Comparing Visual Odometry Systems in Actively Deforming Simulated Colon Environments Anonymous (not verified) Sun, 08/23/2020 - 14:01

[video: https://youtu.be/HdSz3H6I6Mg]

Abstract: This paper presents a new open-source dataset with ground truth position in a simulated colon environment to promote development of real-time feedback systems for physicians performing colonoscopies. Four systems (DSO, LSD-SLAM, SfMLearner, ORB-SLAM2) are tested on this dataset and their failures are analyzed. A data collection platform was fabricated and used to take the dataset in a colonoscopy training simulator that was affixed to a flat surface. The noise in the ground truth positional data induced from the metal in the data collection platform was then characterized and corrected. The Absolute Trajectory RMSE Error (ATE) and Relative Error (RE) metrics were performed on each of the sequences in the dataset for each of the Simultaneous Localization And Mapping (SLAM) systems. While these systems all had good performance in idealized conditions, more realistic conditions in the harder sequences caused them to produce poor results or fail completely. These failures will be a hindrance to physicians in a real-world scenario, so future systems made for this environment must be more robust to the difficulties found in the colon, even at the expense of trajectory accuracy. The authors believe that this is the first open-source dataset with groundtruth data displaying a simulated in vivo environment with active deformation, and that this is the first step toward achieving useful SLAM within the colon.

Fulton, M.J., Prendergast, J.M., DiTommaso, E.R., Rentschler, M.E., “Comparing Visual Odometry Systems in Actively Deforming Simulated Colon Environments,” IEEE International Conference on Intelligent Robots and Systems (IROS), Las Vegas, NV, October, 2020.

(Dataset, Video, IROS Presentation)

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IEEE International Conference on Robotics and Automation (ICRA) (2020): Novel Optimization-Based Design and Surgical Evaluation of a Treaded Robotic Capsule Colonoscope

Anonymous — Sun, 23 Aug 2020 19:57:38 +0000

IEEE International Conference on Robotics and Automation (ICRA) (2020): Novel Optimization-Based Design and Surgical Evaluation of a Treaded Robotic Capsule Colonoscope Anonymous (not verified) Sun, 08/23/2020 - 13:57

[video: https://youtu.be/w_Bfxgj0fF4]

Abstract: Robotic capsule endoscopes (RCEs) are being widely investigated to improve the state of various endoscopy procedures. This paper presents the novel design of a multi-DOF sensor-enabled RCE for colonoscopies (Endoculus) and evaluates porcine in vivo and ex vivo performance. The novelty of the design includes a custom “double-worm” drive that removes axial gear forces while reducing radial moments, and the full parameterization of gear geometries allows for size minimization via an optimization routine over design constraints. Two independently controlled motors drive micro-pillared treads above and below the device allowing for 2-DOF skid-steering, even in a collapsed lumen. The Endoculus contains all functionality of a traditional endoscope: a camera, adjustable LEDs, channels for insufflation and irrigation, and a tool port for endoscopy instruments (e.g., forceps, snares, etc.). Additionally, the Endoculus carries an inertial measurement unit, magnetometer, motor encoders, and motor current sensors to aid in future autonomy strategies. Porcine surgical evaluation demonstrated locomotion up to 40 mm/s on the colon mucosa, 2-DOF steering, the ability to traverse haustral folds, and functionality of endoscopy tools. This platform will enable future validation of feedback control, localization, and mapping algorithms in the unconventional in vivo environment.

Formosa, G.A., Prendergast, J.M., Edmundowicz, S.A., Rentschler, M.E., “Novel Optimization-Based Design and Surgical Evaluation of a Treaded Robotic Capsule Colonoscope,” IEEE International Conference on Robotics and Automation (ICRA), Paris, France, June, 2020.

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IEEE Transactions on Robotics (2020): Novel Optimization-Based Design and Surgical Evaluation of a Treaded Robotic Capsule Colonoscope

Anonymous — Wed, 13 Nov 2019 23:48:03 +0000

IEEE Transactions on Robotics (2020): Novel Optimization-Based Design and Surgical Evaluation of a Treaded Robotic Capsule Colonoscope Anonymous (not verified) Wed, 11/13/2019 - 16:48

[video:https://youtu.be/lTTPNUUq2MA]

Formosa, G.A., Prendergast, J.M., Edmundowicz, S.A., Rentschler, M.E., “Novel Optimization-Based Design and Surgical Evaluation of a Treaded Robotic Capsule Colonoscope,” IEEE Transactions on Robotics. 36(2): 545-552, 2020.

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IEEE International Conference on Intelligent Robots and Systems (2018): Autonomous Localization, Navigation and Haustral Fold Detection for Robotic Endoscopy

Anonymous — Wed, 06 Mar 2019 17:03:11 +0000

IEEE International Conference on Intelligent Robots and Systems (2018): Autonomous Localization, Navigation and Haustral Fold Detection for Robotic Endoscopy Anonymous (not verified) Wed, 03/06/2019 - 10:03

[video: https://youtu.be/x5z16YTQn4M]

Abstract: Capsule endoscopes have gained popularity over the last decade as minimally invasive devices for diagnosing gastrointestinal abnormalities such as colorectal cancer. While this technology offers a less invasive and more convenient alternative to traditional scopes, these capsules are only able to provide observational capabilities due to their passive nature. With the addition of a reliable mobility system and a real-time navigation system, capsule endoscopes could transform from observational devices into active surgical tools, offering biopsy and therapeutic capabilities and even autonomous navigation in a single minimally invasive device. In this work, a vision system is developed to allow for autonomous lumen center tracking and haustral fold identification and tracking during colonoscopy. This system is tested for its ability to accurately identify and track multiple haustral folds across many frames in both simulated and in vivo video, and the lumen center tracking is tested onboard a robotic endoscope platform (REP) within an active simulator to demonstrate autonomous navigation. In addition, real-time localization is demonstrated using open source ORB-SLAM2. The vision system successfully identified 95.6% of Haustral folds in simulator frames and 70.6% in in vivo frames and false positives occurred in less than 1% of frames. The center tracking algorithm showed in vivo center estimates within a mean error of 6.6% of physician estimates and allowed for the REP to traverse 2 m of the active simulator in 6 minutes without intervention.

Prendergast, J.M., Formosa, G.A., Heckman, C.R., Rentschler, M.E., “Autonomous Localization, Navigation and Haustral Fold Detection for Robotic Endoscopy,” IEEE International Conference on Intelligent Robots and Systems, Madrid, Spain, October, 2018.

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IEEE Robotics and Automation Letters (2018): A Modular Endoscopy Simulation Apparatus (MESA) for Robotic Medical Device Sensing and Control Validation

Anonymous — Sat, 06 Oct 2018 17:58:44 +0000

IEEE Robotics and Automation Letters (2018): A Modular Endoscopy Simulation Apparatus (MESA) for Robotic Medical Device Sensing and Control Validation Anonymous (not verified) Sat, 10/06/2018 - 11:58

[video:https://youtu.be/Z0WDcwtgIQM]

Abstract: Much of ongoing robotic endoscope research is focused on locomotion, with only limited exploration into feedback control and autonomy in the unconventional and dynamic in vivo environment. This letter presents a modular endoscopy simulation apparatus (MESA) to quickly, affordably, and repeatedly test novel robotic endoscope control schemes in a synthetic colon at an accessible scale. The MESA allows for replication of many common physiologic barriers for current medical robotics, such as disturbances, patient positional changes, angulation of the colon, and a dynamic visual environment. The MESA will allow research teams to quickly and repeatedly validate new control strategies to minimize the effect of these physiological barriers before testing in costly in vivo procedures. The MESA platform and synthetic colon described in this letter have shown successful replication of colon geometry, visual appearance, peristaltic wave speeds and pressures, and disturbances from patient movement. The mold for the synthetic colon was built in sections to allow for geometry changes for future molds and has shown marked similarity to in vivo images from colonoscopies. The actuators chosen for the various controllable stages have proven ample power to produce maximum-case disturbances expected during procedures, and the stages are modular in structure to allow for a variety of testing scenarios. Inflatable rubber tubes and electronic solenoid valves are used to produce contractile forces, and have shown excess capability to reproduce physiological motility. The simulator presented here will aid in future feedback control, localization, and autonomy development for robotic endoscopes.

Formosa, G.A., Prendergast, J.M., Peng, J., Kirkpatrick, D., Rentschler, M.E., “A Modular Endoscopy Simulation Apparatus (MESA) for Robotic Medical Device Sensing and Control Validation,” IEEE Robotics and Automation Letters. 3(4): 4054-4061, 2018.

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Expert Review of Medical Devices (2015): Magnetically-driven Medical Devices: A Review

Anonymous — Sun, 10 Jun 2018 02:36:01 +0000

Expert Review of Medical Devices (2015): Magnetically-driven Medical Devices: A Review Anonymous (not verified) Sat, 06/09/2018 - 20:36

Abstract: A widely accepted definition of a medical device is an instrument or apparatus that is used to diagnose, prevent or treat disease. Medical devices take a broad range of forms and utilize various methods to operate, such as physical, mechanical or thermal. Of particular interest in this paper are the medical devices that utilize magnetic field sources to operate. The exploitation of magnetic fields to operate or drive medical devices has become increasingly popular due to interesting characteristics of magnetic fields that are not offered by other phenomena, such as mechanical contact, hydrodynamics and thermodynamics. Today, there is a wide range of magnetically driven medical devices purposed for different anatomical regions of the body. A review of these devices is presented and organized into two groups: permanent magnetically driven devices and electromagnetically driven devices. Within each category, the discussion will be further segregated into anatomical regions (e.g., gastrointestinal, ocular, abdominal, thoracic, etc.).

Sliker, L.J., Ciuti, G., Rentschler, M.E., Menciassi, A., "Magnetically-driven Medical Devices: A Review," Expert Review of Medical Devices. 12(6): 737-752, 2015..

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Expert Review of Medical Devices (2016): Towards Autonomous Motion Control in Minimally Invasive Robotic Surgery

Anonymous — Sun, 10 Jun 2018 02:34:06 +0000

Expert Review of Medical Devices (2016): Towards Autonomous Motion Control in Minimally Invasive Robotic Surgery Anonymous (not verified) Sat, 06/09/2018 - 20:34

Abstract: Introduction: While autonomous surgical robotic systems exist primarily at the research level, recently these systems have made a strong push into clinical settings. The autonomous or semi-autonomous control of surgical robotic platforms may offer significant improvements to a diverse field of surgical procedures, allowing for high precision, intelligent manipulation of these systems and opening the door to advanced minimally invasive surgical procedures not currently possible. Areas covered: This review highlights those experimental systems currently under development with a focus on in vivo modeling and control strategies designed specifically for the complex and dynamic surgical environment. Expert review: Novel methods for state estimation, system modeling and disturbance rejection, as applied to these devices, continues to improve the performance of these important surgical tools. Procedures such as Natural Orifice Transluminal Endoscopic Surgery and Laparo-Endoscopic Single Site surgery, as well as more conventional procedures such as Colonoscopy, serve to benefit tremendously from the development of these automated robotic systems, enabling surgeons to minimize tissue damage and shorten procedure times while avoiding the consequences of laparotomy.

Prendergast, J.M., Rentschler, M.E., "Towards Autonomous Motion Control in Minimally Invasive Robotic Surgery," Expert Review of Medical Devices. 13(8): 741-748, 2016.

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