To address the existing challenges in various surgical procedures, in the ARTS lab, our long-term research vision and interest is on prognostic design and development of biomechanically-aware flexible and dexterous instruments, Intelligent implants, and autonomous surgical robots for various less/minimally invasive diagnosis and treatment surgical procedures.

Utilizing these novel medical devices and surgical robots/instruments together with patient-specific biomechanical frameworks, intelligent control algorithms, and medical imaging modalities, ARTS lab in collaboration with clinicians will work toward engineering the surgery (Surgineering) and partnering dexterous intelligent robots with surgeons. Our ultimate goal is to augment the clinicians’ skills to further improve quality of the surgery and patient safety.

Currently, we have three active research directions funded by the National Institute of Health and industry.

  • A Novel Semi-autonomous Surgeon-in-the-loop in situ Robotic Bioprinting System for Functional and Cosmetic Restoration of Musculoskeltal System

Funding Agency: NIH Director’s New Innovator Award, NIH NIAMS

Collaborators: Dr. Ali KhademHosseini, Dr. Johnson V. John, and Dr. Mehmet R. Dokmeci, the Terasaki Institute for Biomedical Innovation

Team Members: Hansoul Kim, Shuojue Yang, Jeff Bonyun

Abstract: In this project, our long-goal is to develop an unprecedented semi-autonomous surgeon-in-the-loop surgical robotic system and complementary computer-assisted algorithms to enable an intuitive in situ robotic bioprinting of human tissues and organs. More specifically, using this extrusion-based bioprinting system, a surgeon can (i) first utilize a high-resolution three-dimensional (3D) point cloud camera to plan an arbitrary spatial printing geometry on the target anatomical surface, (ii) co-operate with a robotic system to manipulate a custom-designed bioprinting instrument to precisely follow the planned printing geometry, and (iii) perform an intuitive and precise deposition of engineered bioinks to make tissue constructs on the target anatomical surface, while (iv) directly control and monitor the printing process to ensure the safety and success of the procedure. The focus of this proposal is simultaneous functional and cosmetic restoration of large volumetric muscle loss (VML) injuries by utilizing a novel engineered bioink- developed by our collaborators at the Terasaki Institute of Biomedical Innovation, a complementary robotic bioprinting system, and intuitive computer-assisted algorithms.

  • Design and Development of a Surgical Robotic Platform based on Flexible Robots and Implants for Minimally-Invasive Orthopedic and Neurosurgerical Interventions

Funding Agency: NIH Trailblazer Award, NIH NIBIB

Collaborators: Dr. Mohsen Khadem,  University of Edinburgh- Dr. Jordan Amadio, University of Texas Dell Medical School

Team Members: Yang Liu, Susheela Sharma, Yash Kulkarni, Yuewan Sun, Jeff Bonyun, Sarah Go, Tarunraj Govindarajan

Abstract: In this project, our long-range goal is to develop a novel semi-autonomous, minimally-invasive, image-guided neurosurgical robotic workstation that consists of a robotic positioning mechanism, a continuum manipulator, flexible instruments, and flexible implants (i.e., flexible pedicle screws (FPSs)) to enable the next generation of minimally- and less-invasive spinal interventions. By providing access to regions within vertebral body, which currently are not accessible utilizing conventional rigid surgical instruments, this neurosurgical robotic workstation will enable surgical treatment of various bone defects in spine such as compression on the spinal cord and/or nerve roots, metastatic bone disease, and vertebral compression fractures due to severe osteoporosis. For this project, we mainly will focus on the mechanical design, development, basic control, and assessment of the subsystems of this novel robotic system with the goal of minimally invasive spinal fusion of osteoporotic vertebrae.

Published Papers:

  • Sharma, Susheela, Ji H. Park, Jordan P. Amadio, Mohsen Khadem, and Farshid Alambeigi. “A novel concentric tube steerable drilling robot for minimally invasive treatment of spinal tumors using cavity and u-shape drilling techniques.” 2023 IEEE international conference on robotics and automation (ICRA), 2023.
  • Sharma, Susheela, Tarunraj G. Mohanraj, Jordan P. Amadio, Mohsen Khadem, and Farshid Alambeigi. “A Concentric Tube Steerable Drilling Robot for Minimally Invasive Spinal Fixation of Osteoporotic Vertebrae.” IEEE Transactions on Biomedical Engineering (2023).
  • Sharma, Susheela, Yuewan Sun, Sarah Go, Jordan P. Amadio, Mohsen Khadem, Amir Hossein Eskandari, and Farshid Alambeigi. “Towards Biomechanics-Aware Design of a Steerable Drilling Robot for Spinal Fixation Procedures with Flexible Pedicle Screws.” In 2023 International Symposium on Medical Robotics (ISMR), pp. 1-6. IEEE, 2023.
  • Nguyen, Nathan, Morgan Parker, Ozdemir Can Kara, and Farshid Alambeigi. “Toward Distributed Fiber Optic Shape Sensing of Continuum Manipulators: A Cost-effective and Simple Manufacturing of Sensor Assembly.” In 2022 IEEE Sensors, pp. 1-4. IEEE, 2022.
  • Mohanraj, Tarunraj G., Jaeyun Song, Mohammad R. Rajebi, Lei Zhou, and Farshid Alambeigi. “A Kirigami-Based Magnetically Steerable Robotic Catheter for Treatment of Peripheral Artery Disease.” In 2022 9th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob), pp. 1-6. IEEE, 2022.
  • Liu, Yang, Tarunraj G. Mohanraj, Mohammad R. Rajebi, Lei Zhou, and Farshid Alambeigi. “Multiphysical analytical modeling and design of a magnetically steerable robotic catheter for treatment of peripheral artery disease.” IEEE/ASME Transactions on Mechatronics 27, no. 4 (2022): 1873-1881.
  • Liu, Yang, and Farshid Alambeigi. “Impact of Generic Tendon Routing on Tension Loss of Tendon-Driven Continuum Manipulators With Planar Deformation.” IEEE Robotics and Automation Letters 7, no. 2 (2022): 3624-3631.
  • Thamo, Balint, Farshid Alambeigi, Kev Dhaliwal, and Mohsen Khadem. “A hybrid dual jacobian approach for autonomous control of concentric tube robots in unknown constrained environments.” In 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 2809-2815. IEEE, 2021.
  • Liu, Yang, Uksang Yoo, Seungbeom Ha, S. Farokh Atashzar, and Farshid Alambeigi. “Influence of antagonistic tensions on distributed friction forces of multisegment tendon-driven continuum manipulators with irregular geometry.” IEEE/ASME Transactions on Mechatronics 27, no. 5 (2021): 2418-2428.
  • Liu, Yang, and Farshid Alambeigi. “Effect of external and internal loads on tension loss of tendon-driven continuum manipulators.” IEEE Robotics and Automation Letters 6, no. 2 (2021): 1606-1613.
  • Yoo, Uksang, Yang Liu, Ashish D. Deshpande, and Farshid Alamabeigi. “Analytical Design of a Pneumatic Elastomer Robot With Deterministically Adjusted Stiffness.” IEEE robotics and automation letters 6, no. 4 (2021): 7773-7780.
  • Liu, Yang, Seong Hyo Ahn, Uksang Yoo, Alexander R. Cohen, and Farshid Alambeigi. “Toward analytical modeling and evaluation of curvature-dependent distributed friction force in tendon-driven continuum manipulators.” In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 8823-8828. IEEE, 2020.
  • Design and Development of an Autonomous Surgical Framework with Intelligent Tactile Skin for Sensitive and Reliable Early Diagnosis, Topographic Mapping, and Stiffness Classification Of Colorectal Cancer Polyps

Funding Agency: NIH NCI- MITRE Incorporation

Collaborators: Dr. S. Farokh Atashzar, New York University- Dr. Naruhiko Ikoma, Yuki Hirata, University of Texas, MD Anderson Cancer Center

Team Members: Hansoul Kim, Ozdemir C. Kara, Siddhartha Kapuria, Nethra Venkatayogi, Jiaqi Xue, Jeff Bonyun, Tarunraj Govindarajan

Abstract: In this project, Our long-term goal is to develop a novel soft robotic endoscope with intelligent tactile sensors and complementary machine learning (ML) and computer vision (CV) algorithms to enhance early-stage detection, accurate tumor localization, and treatment stratification of various gastrointestinal (GI) cancers. This robotic framework provides clinicians with (i) asafe and intuitively-steerable soft robotic endoscope to perform precise diagnosis, biopsy, and surgical procedures; (ii) in vivo high-fidelity visual, textural, and stiffness information of the diagnosed anatomy; and (iii) in vivo radiation-free quantified topographic mapping and morphological characterization of GI polyps using CV algorithms.

Published Papers:

  • Hirata, Yuki, Ali Azhdarinia, Farshid Alambeigi, and Naruhiko Ikoma. “ASO Author Reflections: Management of R1 Margins in the Era of Multidisciplinary Treatment of Gastric Cancer.” Annals of surgical oncology (2023): 1-2.
  • Hirata, Yuki, Farshid Alambeigi, and Naruhiko Ikoma. “ASO Author Reflections: Evolution of Surgical Techniques Through Robotic Surgery Technology.” Annals of surgical oncology 30, no. 5 (2023): 2960-2961.
  • Kapuria, Siddhartha, Tarunraj G. Mohanraj, Nethra Venkatayogi, Ozdemir Can Kara, Yuki Hirata, Patrick Minot, Ariel Kapusta, Naruhiko Ikoma, and Farshid Alambeigi. “Towards Reliable Colorectal Cancer Polyps Classification via Vision Based Tactile Sensing and Confidence-Calibrated Neural Networks.” In 2023 International Symposium on Medical Robotics (ISMR), pp. 1-7. IEEE, 2023.
  • Kara, Ozdemir Can, Nethra Venkatayogi, Naruhiko Ikoma, and Farshid Alambeigi. “A reliable and sensitive framework for simultaneous type and stage detection of colorectal cancer polyps.” Annals of Biomedical Engineering (2023): 1-14.
  • Venkatayogi, Nethra, Qin Hu, Ozdemir Can Kara, Tarunraj G. Mohanraj, S. Farokh Atashzar, and Farshid Alambeigi. “Pit-Pattern Classification of Colorectal Cancer Polyps Using a Hyper Sensitive Vision-Based Tactile Sensor and Dilated Residual Networks.” arXiv preprint arXiv:2211.06814 (2022).
  • Venkatayogi, Nethra, Ozdemir Can Kara, Jeff Bonyun, Naruhiko Ikoma, and Farshid Alambeigi. “Classification of colorectal cancer polyps via transfer learning and vision-based tactile sensing.” In 2022 IEEE Sensors, pp. 1-4. IEEE, 2022.
  • Kara, Ozdemir Can, Naruhiko Ikoma, and Farshid Alambeigi. “HySenSe: A hyper-sensitive and high-fidelity vision-based tactile sensor.” In 2022 IEEE Sensors, pp. 1-4. IEEE, 2022.