Publications by authors named "Shahriar Sefati"

8 Publications

  • Page 1 of 1

Stochastic Force-based Insertion Depth and Tip Position Estimations of Flexible FBG-Equipped Instruments in Robotic Retinal Surgery.

IEEE ASME Trans Mechatron 2021 Jun 8;26(3):1512-1523. Epub 2020 Sep 8.

Laboratory for Computational Sensing and Robotics (LCSR) at the Johns Hopkins University, Baltimore, MD, 21218, USA.

Vitreoretinal surgery is among the most delicate surgical tasks during which surgeon hand tremor may severely attenuate surgeon performance. Robotic assistance has been demonstrated to be beneficial in diminishing hand tremor. Among the requirements for reliable assistance from the robot is to provide precise measurements of system states e.g. sclera forces, tool tip position and tool insertion depth. Providing this and other sensing information using existing technology would contribute towards development and implementation of autonomous robot-assisted tasks in retinal surgery such as laser ablation, guided suture placement/assisted needle vessel cannulation, among other applications. In the present work, we use a state-estimating Kalman filtering (KF) to improve the tool tip position and insertion depth estimates, which used to be purely obtained by robot forward kinematics (FWK) and direct sensor measurements, respectively. To improve tool tip localization, in addition to robot FWK, we also use sclera force measurements along with beam theory to account for tool deflection. For insertion depth, the robot FWK is combined with sensor measurements for the cases where sensor measurements are not reliable enough. The improved tool tip position and insertion depth measurements are validated using a stereo camera system through preliminary experiments and a case study. The results indicate that the tool tip position and insertion depth measurements are significantly improved by 77% and 94% after applying KF, respectively.
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http://dx.doi.org/10.1109/tmech.2020.3022830DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8294652PMC
June 2021

Fluoroscopic Navigation for a Surgical Robotic System including a Continuum Manipulator.

IEEE Trans Biomed Eng 2021 Jul 16;PP. Epub 2021 Jul 16.

We present an image-based navigation solution for a surgical robotic system with a Continuum Manipulator (CM). Our navigation system uses only fluoroscopic images from a mobile C-arm to estimate the CM shape and pose with respect to the bone anatomy. The CM pose and shape estimation is achieved using image intensity-based 2D/3D registration. A learning-based framework is used to automatically detect the CM in X-ray images, identifying landmark features that are used to initialize and regularize image registration. We also propose a modified hand-eye calibration method that numerically optimizes the hand-eye matrix during image registration. The proposed navigation system for CM positioning was tested in simulation and cadaveric studies. In simulation, the proposed registration achieved a mean error of 1.10 0.72 mm between the CM tip and a target entry point on the femur. In cadaveric experiments, the mean CM tip position error was 2.86 0.80 mm after registration and repositioning of the CM. The results suggest that our proposed fluoroscopic navigation is sufficient to guide the CM for orthopedic applications.
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http://dx.doi.org/10.1109/TBME.2021.3097631DOI Listing
July 2021

A Surgical Robotic System for Treatment of Pelvic Osteolysis Using an FBG-Equipped Continuum Manipulator and Flexible Instruments.

IEEE ASME Trans Mechatron 2021 Feb 31;26(1):369-380. Epub 2020 Aug 31.

Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, USA, 21218; Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA; Department of Orthopedic Surgery, The Johns Hopkins Medical School, Baltimore, MD, USA, 21205.

This paper presents the development and experimental evaluation of a redundant robotic system for the less-invasive treatment of osteolysis (bone degradation) behind the acetabular implant during total hip replacement revision surgery. The system comprises a rigid-link positioning robot and a Continuum Dexterous Manipulator (CDM) equipped with highly flexible debriding tools and a Fiber Bragg Grating (FBG)-based sensor. The robot and the continuum manipulator are controlled concurrently via an optimization-based framework using the Tip Position Estimation (TPE) from the FBG sensor as feedback. Performance of the system is evaluated on a setup that consists of an acetabular cup and saw-bone phantom simulating the bone behind the cup. Experiments consist of performing the surgical procedure on the simulated phantom setup. CDM TPE using FBGs, target location placement, cutting performance, and the concurrent control algorithm capability in achieving the desired tasks are evaluated. Mean and standard deviation of the CDM TPE from the FBG sensor and the robotic system are 0.50 mm, and 0.18 mm, respectively. Using the developed surgical system, accurate positioning and successful cutting of desired straight-line and curvilinear paths on saw-bone phantoms behind the cup with different densities are demonstrated. Compared to the conventional rigid tools, the workspace reach behind the acetabular cup is 2.47 times greater when using the developed robotic system.
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http://dx.doi.org/10.1109/tmech.2020.3020504DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8132934PMC
February 2021

An Active Steering Hand-held Robotic System for Minimally Invasive Orthopaedic Surgery Using a Continuum Manipulator.

IEEE Robot Autom Lett 2021 Apr 16;6(2):1622-1629. Epub 2021 Feb 16.

Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, USA.

This paper presents the development and experimental evaluation of an active steering hand-held robotic system for milling and curved drilling in minimally invasive orthopaedic interventions. The system comprises a cable-driven continuum dexterous manipulator (CDM), an actuation unit with a handpiece, and a flexible, rotary cutting tool. Compared to conventional rigid drills, the proposed system enhances dexterity and reach in confined spaces in surgery, while providing direct control to the surgeon with sufficient stability while cutting/milling hard tissue. Of note, for cases that require precise motion, the system is able to be mounted on a positioning robot for additional controllability. A proportional-derivative (PD) controller for regulating drive cable tension is proposed for the stable steering of the CDM during cutting operations. The robotic system is characterized and tested with various tool rotational speeds and cable tensions, demonstrating successful cutting of three-dimensional and curvilinear tool paths in simulated cancellous bone and bone phantom. Material removal rates (MRRs) of up to 571 mm/s are achieved for stable cutting, demonstrating great improvement over previous related works.
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http://dx.doi.org/10.1109/lra.2021.3059634DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8052093PMC
April 2021

Data-Driven Shape Sensing of a Surgical Continuum Manipulator Using an Uncalibrated Fiber Bragg Grating Sensor.

IEEE Sens J 2021 Feb 1;21(3):3066-3076. Epub 2021 Oct 1.

Department of Orthopedic Surgery, The Johns Hopkins Medical School, Baltimore, MD, USA, 21205.

This article proposes a data-driven learning-based approach for shape sensing and Distal-end Position Estimation (DPE) of a surgical Continuum Manipulator (CM) in constrained environments using Fiber Bragg Grating (FBG) sensors. The proposed approach uses only the sensory data from an unmodeled uncalibrated sensor embedded in the CM to estimate the shape and DPE. It serves as an alternate to the conventional mechanics-based sensor-model-dependent approach which relies on several sensor and CM geometrical assumptions. Unlike the conventional approach where the shape is reconstructed from proximal to distal end of the device, we propose a reversed approach where the distal-end position is estimated first and given this information, shape is then reconstructed from distal to proximal end. The proposed methodology yields more accurate DPE by avoiding accumulation of integration errors in conventional approaches. We study three data-driven models, namely a linear regression model, a Deep Neural Network (DNN), and a Temporal Neural Network (TNN) and compare DPE and shape reconstruction results. Additionally, we test both approaches (data-driven and model-dependent) against internal and external disturbances to the CM and its environment such as incorporation of flexible medical instruments into the CM and contacts with obstacles in taskspace. Using the data-driven (DNN) and model-dependent approaches, the following max absolute errors are observed for DPE: 0.78 mm and 2.45 mm in free bending motion, 0.11 mm and 3.20 mm with flexible instruments, and 1.22 mm and 3.19 mm with taskspace obstacles, indicating superior performance of the proposed data-driven approach compared to the conventional approaches.
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http://dx.doi.org/10.1109/jsen.2020.3028208DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7978403PMC
February 2021

High-Resolution Optical Fiber Shape Sensing of Continuum Robots: A Comparative Study.

IEEE Int Conf Robot Autom 2020 May-Aug;2020. Epub 2020 Sep 15.

Department of Engineering Physics, Polytechnique Montral, 2900 Edouard-Montpetit, Montreal, Canada.

Flexible medical instruments, such as Continuum Dexterous Manipulators (CDM), constitute an important class of tools for minimally invasive surgery. Accurate CDM shape reconstruction during surgery is of great importance, yet a challenging task. Fiber Bragg grating (FBG) sensors have demonstrated great potential in shape sensing and consequently tip position estimation of CDMs. However, due to the limited number of sensing locations, these sensors can only accurately recover basic shapes, and become unreliable in the presence of obstacles or many inflection points such as s-bends. Optical Frequency Domain Reflectometry (OFDR), on the other hand, can achieve much higher spatial resolution, and can therefore accurately reconstruct more complex shapes. Additionally, Random Optical Gratings by Ultraviolet laser Exposure (ROGUEs) can be written in the fibers to increase signal to noise ratio of the sensors. In this comparison study, the tip position error is used as a metric to compare both FBG and OFDR shape reconstructions for a 35 mm long CDM developed for orthopedic surgeries, using a pair of stereo cameras as ground truth. Three sets of experiments were conducted to measure the accuracy of each technique in various surgical scenarios. The tip position error for the OFDR (and FBG) technique was found to be 0.32 (0.83) mm in free-bending environment, 0.41 (0.80) mm when interacting with obstacles, and 0.45 (2.27) mm in s-bending. Moreover, the maximum tip position error remains sub-millimeter for the OFDR reconstruction, while it reaches 3.40 mm for FBG reconstruction. These results propose a cost-effective, robust and more accurate alternative to FBG sensors for reconstructing complex CDM shapes.
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http://dx.doi.org/10.1109/icra40945.2020.9197454DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8375516PMC
September 2020

On the Use of a Continuum Manipulator and a Bendable Medical Screw for Minimally Invasive Interventions in Orthopedic Surgery.

IEEE Trans Med Robot Bionics 2019 Feb 28;1(1):14-21. Epub 2019 Jan 28.

Laboratory for Computational Sensing and Robotics, The Johns Hopkins University, Baltimore, MD 21218 USA, and also with the Applied Physics Laboratory, The Johns Hopkins University, Laurel, MD 20723 USA.

Accurate placement and stable fixation are the main goals of internal fixation of bone fractures using the traditional medical screws. These goals are necessary to expedite and avoid improper fracture healing due to misalignment of the bone fragments. However, the rigidity of the screw, geometry of the fractured anatomy (e.g., femur and pelvis), and osteoporosis may cause an array of complications. To address these challenges, we propose the use of a continuum manipulator and a bendable medical screw (BMS) to drill curved tunnels and fixate the bone fragments. This novel approach provides the clinicians with a degree of freedom in selecting the drilling entry point as well as the navigation of drill in complex anatomical and osteoporotic bones. This technique can also facilitate the treatment of osteonecrosis and augmentation of the hip to prevent osteoporotic fractures. In this paper: 1) we evaluated the performance of the curved drilling technique on human cadaveric specimens by making several curved tunnels with different curvatures and 2) we also demonstrated the feasibility of internal fixation using the BMS versus a rigid straight screw by performing finite element simulation of fracture fixation in an osteoporotic femur.
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http://dx.doi.org/10.1109/tmrb.2019.2895780DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7518451PMC
February 2019

Real-Time Sclera Force Feedback for Enabling Safe Robot-Assisted Vitreoretinal Surgery.

Annu Int Conf IEEE Eng Med Biol Soc 2018 Jul;2018:3650-3655

One of the major yet little recognized challenges in robotic vitreoretinal surgery is the matter of tool forces applied to the sclera. Tissue safety, coordinated tool use and interactions between tool tip and shaft forces are little studied. The introduction of robotic assist has further diminished the surgeon's ability to perceive scleral forces. Microsurgical tools capable of measuring such small forces integrated with robotmanipulators may therefore improve functionality and safety by providing sclera force feedback to the surgeon. In this paper, using a force-sensing tool, we have conducted robotassisted eye manipulation experiments to evaluate the utility of providing scleral force feedback. The work assesses 1) passive audio feedback and 2) active haptic feedback and evaluates the impact of these feedbacks on scleral forces in excess of aboundary. The results show that in presence of passive or active feedback, the duration of experiment increases, while the duration for which scleral forces exceed a safe threshold decreases.
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http://dx.doi.org/10.1109/EMBC.2018.8513255DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6241282PMC
July 2018
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