52 research outputs found

    Single-Fiber Optical Frequency Domain Reflectometry Shape Sensing of Continuum Manipulators with Planar Bending

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    To address the challenges associated with shape sensing of continuum manipulators (CMs) using Fiber Bragg Grating (FBG) optical fibers, we feature a unique shape sensing assembly utilizing solely a single Optical Frequency Domain Reflectometry (OFDR) fiber attached to a flat nitinol wire (NiTi). Integrating this easy-to-manufacture unique sensor with a long and soft CM with 170 mm length, we performed different experiments to evaluate its shape reconstruction ability. Results demonstrate phenomenal shape reconstruction accuracy for both C-shape (< 2 mm tip error, < 1.2 mm shape error) and J-shape (< 3.4 mm tip error, < 2.3 mm shape error) experiments

    HySenSe: A Hyper-Sensitive and High-Fidelity Vision-Based Tactile Sensor

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    In this paper, to address the sensitivity and durability trade-off of Vision-based Tactile Sensor (VTSs), we introduce a hyper-sensitive and high-fidelity VTS called HySenSe. We demonstrate that by solely changing one step during the fabrication of the gel layer of the GelSight sensor (as the most well-known VTS), we can substantially improve its sensitivity and durability. Our experimental results clearly demonstrate the outperformance of the HySenSe compared with a similar GelSight sensor in detecting textural details of various objects under identical experimental conditions and low interaction forces (<= 1.5 N).Comment: Accepted to IEEE Sensors 2022 Conferenc

    Towards Biomechanical Evaluation of a Transformative Additively Manufactured Flexible Pedicle Screw for Robotic Spinal Fixation

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    Vital for spinal fracture treatment, pedicle screw fixation is the gold standard for spinal fixation procedures. Nevertheless, due to the screw pullout and loosening issues, this surgery often fails to be effective for patients suffering from osteoporosis (i.e., having low bone mineral density). These failures can be attributed to the rigidity of existing drilling instruments and pedicle screws forcing clinicians to place these implants into the osteoporotic regions of the vertebral body. To address this critical issue, we have developed a steerable drilling robotic system and evaluated its performance in drilling various J- and U-shape trajectories. Complementary to this robotic system, in this paper, we propose design, additive manufacturing, and biomechanical evaluation of a transformative flexible pedicle screw (FPS) that can be placed in pre-drilled straight and curved trajectories. To evaluate the performance of the proposed flexible implant, we designed and fabricated two different types of FPSs using the direct metal laser sintering (DMLS) process. Utilizing our unique experimental setup and ASTM standards, we then performed various pullout experiments on these FPSs to evaluate and analyze their biomechanical performance implanted in straight trajectories.Comment: 6 pages, 7 figures, Accepted for publication at the 2024 International Symposium on Medical Robotic

    Classification of Colorectal Cancer Polyps via Transfer Learning and Vision-Based Tactile Sensing

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    In this study, to address the current high earlydetection miss rate of colorectal cancer (CRC) polyps, we explore the potentials of utilizing transfer learning and machine learning (ML) classifiers to precisely and sensitively classify the type of CRC polyps. Instead of using the common colonoscopic images, we applied three different ML algorithms on the 3D textural image outputs of a unique vision-based surface tactile sensor (VS-TS). To collect realistic textural images of CRC polyps for training the utilized ML classifiers and evaluating their performance, we first designed and additively manufactured 48 types of realistic polyp phantoms with different hardness, type, and textures. Next, the performance of the used three ML algorithms in classifying the type of fabricated polyps was quantitatively evaluated using various statistical metrics.Comment: Accepted to IEEE Sensors 2022 Conferenc
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