Seyedmohammadreza Sajadi

• Sajadi, Seyedmohammadreza; Tariverdi, Abbas; Brun, Henrik; Elle, Ole Jakob & Mathiassen, Kim (2026). Robotic transesophageal echocardiography: system design and deep learning-based kinematic modeling. Frontiers in Robotics and AI. 12. doi: 10.3389/frobt.2025.1705142. Full text in Research Archive
• Sajadi, Seyed Mohammad Reza; Mathiassen, Kim; Brun, Henrik & Elle, Ole Jakob (2022). Design, Kinematic Modeling, and Validation of a Robotic-Assisted Transesophageal Echocardiography System, 2022 IEEE/SICE International Symposium on System Integration (SII 2022) : January 9-12, 2022 (Virtual Conference) Narvik, Norway. IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781665445405. doi: 10.1109/SII52469.2022.9708810. Full text in Research Archive
• Sajadi, Seyed Mohammad Reza; Karbasi, Seyed Mojtaba; Brun, Henrik; Tørresen, Jim; Elle, Ole Jakob & Mathiassen, Kim (2022). Towards Autonomous Robotic Biopsy—Design, Modeling and Control of a Robot for Needle Insertion of a Commercial Full Core Biopsy Instrument. Frontiers in Robotics and AI. 9. doi: 10.3389/frobt.2022.896267. Full text in Research Archive Show summary

  This paper presents the design, control, and experimental evaluation of a novel fully automated robotic-assisted system for the positioning and insertion of a commercial full core biopsy instrument under guidance by ultrasound imaging. The robotic system consisted of a novel 4° of freedom (DOF) add-on robot for the positioning and insertion of the biopsy instrument that is attached to a UR5-based teleoperation system with 6 DOF. The robotic system incorporates the advantages of both freehand and probe-guided biopsy techniques. The proposed robotic system can be used as a slave robot in a teleoperation configuration or as an autonomous or semi-autonomous robot in the future. While the UR5 manipulator was controlled using a teleoperation scheme with force controller, a reinforcement learning based controller using the Deep Deterministic Policy Gradient (DDPG) algorithm was developed for the add-on robotic system. The dexterous workspace analysis of the add-on robotic system demonstrated that the system has a suitable workspace within the US image. Two sets of comprehensive experiments including four experiments were performed to evaluate the robotic system’s performance in terms of the biopsy instrument positioning, and the insertion of the needle inside the ultrasound plane. The experimental results showed the ability of the robotic system for in-plane needle insertion. The overall mean error of all four experiments in the tracking of the needle angle was 0.446°, and the resolution of the needle insertion was 0.002 mm.

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• Sajadi, Seyed Mohammad Reza; Mathiassen, Kim; Brun, Henrik & Elle, Ole Jakob (2022). Design, Kinematic Modeling, and Validation of a Robotic-Assisted Transesophageal Echocardiography System. Full text in Research Archive Show summary

  Transesophageal Echocardiography is a safe and minimally invasive tool to provide high-quality anatomic and hemodynamic information of the heart and its structures. However, the risk of exposure to a significant level of radiation during combined fluoroscopy and TEE-guided examinations and musculoskeletal disorders due to holding the probe for prolonged periods of time are two main shortcomings of using TEE manually. This paper presents the design, kinematic modeling, and validation of a novel 6 DOF robotic-assisted transesophageal echocardiography system to overcome the above mentioned shortcomings. The robotic system has been designed based on a commercially available TEE probe with 5 actuated Degrees of freedom on the TEE handle and an extra DOF to control the imaging plane. The constant curvature model is employed for the forward and inverse kinematic modeling of the robotic system. The kinematic model and the performance of the robotic system are validated with an experimental setup using a 6DOF OptiTrack real-time tracking system.

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