Yuna Choi;Daehun Lee;Geun Young Hong;Dong-Hyuk Lee;Sajjad Manzoor;Youngjin Choi
{"title":"Tensegrity Sensor-Integrated Hip Exoskeleton for Human Motion Recognition During Walking","authors":"Yuna Choi;Daehun Lee;Geun Young Hong;Dong-Hyuk Lee;Sajjad Manzoor;Youngjin Choi","doi":"10.1109/TMRB.2025.3646760","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3646760","url":null,"abstract":"This paper proposes a hip exoskeleton inspired by the concept of biotensegrity. An actuator directly connected to a rigid structure is applied to provide a high assistive torque for flexion and extension in the sagittal plane. In the frontal and transverse planes, where lower torque is sufficient, passive joints based on tensegrity structures are introduced to mimic the flexibility and load distribution of the human musculoskeletal system. In particular, a novel passive joint mechanism is structurally extended into a universal joint that functions as a joint angle sensor, enabling the quantitative measurement of the wearer’s hip complex motions during walking. To validate this mechanism, five linear parameters are extracted using line geometry to analyze its universal joint behavior mathematically. Specifically, the change in resistance of the rubber band inside the sensor is used to calculate the joint kinematics, that is, it is used to estimate the rotation axis and angle based on a line geometry. Finally, comparative experiments with actual joint angles are conducted, confirming that the three-degrees-of-freedom motion of the wearer’s hip complex can be effectively recognized using the tensegrity sensor-integrated hip exoskeleton.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"8 1","pages":"515-525"},"PeriodicalIF":4.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148486776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Junling Fu;Zijian Cai;Runing Xiao;Giancarlo Ferrigno;Alberto Redaelli;Elena De Momi
{"title":"Learning-Based Hybrid Needle Tip Tracking and Visualization Framework for Robotic Ultrasound-Guided Interventions","authors":"Junling Fu;Zijian Cai;Runing Xiao;Giancarlo Ferrigno;Alberto Redaelli;Elena De Momi","doi":"10.1109/TMRB.2026.3654277","DOIUrl":"https://doi.org/10.1109/TMRB.2026.3654277","url":null,"abstract":"Ultrasound (US)-guided needle-based interventions have been extensively employed in clinical practice for biopsies, regional anesthesia, and tumor ablation, considering the advantages of real-time imaging, portability, and non-ionizing radiation. Precise localization and tracking of the needle tip are critical for ensuring the successful needle placement while minimizing the risk of injury to surrounding anatomical structures. However, achieving real-time and reliable needle tip tracking remains challenging due to the inherent properties of US images, such as low spatial resolution, speckle noise, and imaging artifacts that obscure the needle tip. This study proposes a hybrid learning-based framework for accurately and robustly localizing the needle tip within the US image plane during robot-assisted interventional procedures. The framework comprises a dual-branch template matching-based detection module, a Convolutional Neural Network (CNN)-based detection module, and a “dynamic template selection and updating” mechanism to enhance overall tracking performance. Additionally, to recover the needle tip invisibility caused by unanticipated movements, an active exploration strategy based on a Gaussian Process (GP) model and Bayesian Optimization (BO) is proposed for efficient and accurate robotic US probe pose adjustment. The effectiveness of the proposed method for needle tip tracking performance has been evaluated through a series of experiments conducted on ex vivo porcine liver samples under varying insertion angles and velocities. Experimental results demonstrate that the proposed framework achieves a maximum median localization error of 1.17 mm and an Interquartile Range (IQR) of 1.28 mm across all test conditions. Furthermore, in scenarios requiring needle tip visibility recovery, the proposed BO-based strategy achieved a median localization error of 1.52 mm and an IQR of 0.95 mm.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"8 1","pages":"252-263"},"PeriodicalIF":4.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11352972","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148487088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sofia Breschi;Domenico Riggio;Ingrid Tombini;Junling Fu;Maria Francesca Spadea;Elena De Momi
{"title":"Visuo-Haptic Feedback and Extended Reality in Microinvasive Cardiac Surgery: A Next-Generation Simulator for Mitral Valve Repair","authors":"Sofia Breschi;Domenico Riggio;Ingrid Tombini;Junling Fu;Maria Francesca Spadea;Elena De Momi","doi":"10.1109/TMRB.2025.3643940","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3643940","url":null,"abstract":"Mitral regurgitation is a structural heart disease characterized by dysfunction of the mitral valve. It can be treated through minimally invasive transcatheter edge-to-edge repair procedures, such as those involving the MitraClip<inline-formula> <tex-math>${}^{^{text {TM}}} $ </tex-math></inline-formula> system. Despite its clinical efficacy, the procedure poses technical challenges, requiring interventional cardiologists to undergo multiple procedures to achieve instrumentation proficiency. Previous studies have demonstrated the efficacy of extended reality simulators in improving surgical skill training. The purpose of this study is to evaluate the effectiveness of visuo-haptic feedback within an extended reality simulator to accelerate and enhance the learning process for the MitraClip<inline-formula> <tex-math>${}^{^{text {TM}}} $ </tex-math></inline-formula> procedure, potentially offering a valuable tool in surgical training. In this study, based on the prototype of our previous simulator, we further implemented a novel cardiac dynamic environment, a visual feedback interface, an innovative haptic armband, and a new model of the catheter to enhance the simulator’s fidelity and educational usability. Experiment results demonstrated that users benefiting from visuo-haptic feedback exhibited significantly reduced completion times, reduced deviation from predefined trajectories, and presented safer navigation results. Moreover, users preferred the visuo-haptic feedback experience, highlighting its perceived value in enhancing training. These findings underscore the potential of adding visuo-haptic feedback to extended reality simulators in surgical training for complex procedures, improving proficiency and patient surgery outcomes.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"8 1","pages":"277-287"},"PeriodicalIF":4.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11299599","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148487612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Trajectory Planning and Correction for Transnasal Surgical Robots via RCM Constraint Modeling and Fiber Optic Sensing Feedback","authors":"Zhixiong Zhou;Qingsong Ai;Ping Liang;Zemin Liu;Quan Liu;Tianliang Li;Weiwei Xia;Wei Meng","doi":"10.1109/TMRB.2025.3646762","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3646762","url":null,"abstract":"Transnasal surgical robots must operate within the confined anatomical space of the nasal cavity, which requires high precision in trajectory planning and real-time correction. This study presents a comprehensive trajectory planning and real-time correction framework for transnasal surgical robots, integrating Remote Center of Motion (RCM) constraints and real-time fiber optic sensing feedback. A personalized 3D point cloud and grid map of the nasal cavity are constructed based on computed tomography (CT) imaging. The improved RRT* algorithm is used to generate collision-free paths that adhere to RCM constraints. To address sensor measurement errors, an Adaptive Unscented Kalman Filter (AUKF) is employed to accurately estimate the end-effector’s position and correct minor deviations in real-time through position control. When significant trajectory deviation or contact with nasal tissue is detected, a local trajectory replanning strategy with multiple constraints is introduced, dynamically adjusting the path based on sensor feedback. Experimental results show that the proposed framework effectively generates anatomically compatible motion paths and provides real-time trajectory error correction in complex nasal environments, offering a reliable and precise solution for robot-assisted transnasal surgery.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"8 1","pages":"198-207"},"PeriodicalIF":4.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148490429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"OmniSense: A Visuotactile Sensor for Force, Texture, and Temperature","authors":"Thad Jacob T. Tiong;Aaron Raymond See","doi":"10.1109/TMRB.2025.3646751","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3646751","url":null,"abstract":"OmniSense is a novel visuotactile sensor integrating texture imaging, force classification, temperature detection, 3D reconstruction, size estimation, lump detection, and object recognition within a single elastomer-based system. Unlike traditional sensors like GelSight, OmniTact, or HaptiTemp, which require multiple elastomers or compromise functionality, OmniSense combines multimodal sensing capabilities without sacrificing precision. Its design enables high-resolution imaging, force and temperature sensing, and photometric stereo-based 3D reconstruction, offering versatility for medical and industrial applications. With size estimation achieving sub-millimeter accuracy and capable of lump detection identifying anomalies beneath a synthetic skin, OmniSense addresses critical challenges in spatial analysis and medical diagnostics. Furthermore, it delivers superior object recognition, achieving a mean average precision of 95%. These advancements establish OmniSense as a novel approach on visuotactile sensor design for tasks requiring real-time, multimodal feedback.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"8 1","pages":"504-514"},"PeriodicalIF":4.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148489708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Novel Real-Time Modeling and Perception Method for Surgical Robots Based on Multisensory Data in a Dynamic Unstructured Environment","authors":"Guoli Song;Tian Gao;Xingang Zhao;Lu Hua;Ting Zhang;Yiwen Zhao","doi":"10.1109/TMRB.2025.3643987","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3643987","url":null,"abstract":"Despite advancements in robotic surgery, recent developments in surgical robots have rarely focused on ensuring the safety of surgeons and other devices within the surgical environment. This paper introduces a novel real-time modeling and perception method tailored for surgical Dynamic Unstructured Environments, leveraging multisensory data. We propose the use of a uniform Cartesian grid (UCG) over the traditional radial non-uniform grid (RNUG) to establish a more accurate offline model of the surgical environment. Furthermore, our approach incorporates multisensory data fusion and UCGs for rapid online updates of environmental models. This dual strategy of offline modeling and online updating addresses both modeling accuracy and efficiency, making UCG modeling more suitable for multisensory fusion compared to RNUG. The proposed methodology enhances the overall safety and operational reliability of surgical robots.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"8 1","pages":"334-346"},"PeriodicalIF":4.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148489760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Avinash S. Pramod;Santhakumar Mohan;Asokan Thondiyath
{"title":"Human-Centric Shoulder Exoskeleton: A Novel Assistive Device With a Self-Aligning Mechanism to Reduce Interaction Forces","authors":"Avinash S. Pramod;Santhakumar Mohan;Asokan Thondiyath","doi":"10.1109/TMRB.2025.3646719","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3646719","url":null,"abstract":"Upper limb wearable exoskeletons are devices used for assistive and augmentative applications in work environments. The shoulder mechanism of the upper limb exoskeleton is vital in fulfilling its objective by exhibiting its capability to move with the human shoulder in unity without any joint axis misalignment. Any misalignment can cause strain on the human shoulder complex due to unwanted interaction forces between the user and the exoskeleton. Most existing portable assistive or augmentation exoskeletons fail to exhibit the capability to self-align when there is a joint axis misalignment due to design-related issues. This paper presents the design, analysis, and experimental evaluation of a novel human-centric shoulder exoskeleton with a self-aligning shoulder mechanism for an average adult male. The novelty of the design is that it considers the human shoulder’s humeral head (HH) translation and incorporates a novel mechanism to reduce misalignment. The system’s design details, workspace analysis, and prototype testing and analysis are explained. The proposed exoskeleton is evaluated and validated using simulation and experimentation on a standardised test bench. The results are compared with the existing conventional exoskeleton and human-assisted motion, and it was found that the proposed exoskeleton is capable of reducing the interaction forces due to misalignment by 99%. Further, a simple assistive control architecture is proposed and implemented for the exoskeleton for efficient operation.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"8 1","pages":"347-356"},"PeriodicalIF":4.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148491084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ella Walsh;Nillan Nimal;Adnan Munawar;James Drake;Tim Van Mieghem;Thomas Looi
{"title":"Development of a Virtual da Vinci Xi Training Simulator for Robotic In-Utero Open Spina Bifida Repair","authors":"Ella Walsh;Nillan Nimal;Adnan Munawar;James Drake;Tim Van Mieghem;Thomas Looi","doi":"10.1109/TMRB.2025.3644001","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3644001","url":null,"abstract":"Open spina bifida (OSB), also known as myelomeningocele, is a neural tube defect where the spine of a developing fetus is exposed. Repair of the defect before birth improves outcomes for both mother and child. A novel minimally invasive robotic in-utero approach is proposed, requiring new tools to enable surgeon planning and training. This work presents a dynamic virtual simulator of the da Vinci Xi Robotic Surgical System with an interactive fetal environment that allows surgeons to practice simulated OSB repair. The simulator is built in the Asynchronous Multi-Body Framework (AMBF) and integrated with the da Vinci Research Kit (dVRK). The directional and rotational control mappings were consistent with the respective controls tested on a real operative da Vinci Xi robot <inline-formula> <tex-math>$(R^{2} geq 0.979)$ </tex-math></inline-formula>. Kinematics were further validated with path tracing tasks which yielded similar trajectory deviation errors between the simulator and the real Xi robot. Surgeons completed a suturing task using the simulator and evaluated the performance, agreeing that simulator robot controls are realistic, fetal model and suturing are somewhat realistic, and that the simulator is useful as a training tool. This simulator has potential applications in research, surgical training and preoperative planning for robotic approaches to fetal surgical procedures.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"8 1","pages":"296-303"},"PeriodicalIF":4.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148491080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Design and Control of Continuum Manipulators With Pose Reconstruction Based on Feedforward Compensation","authors":"Yongzhuo Gao;Dexin Cheng;Hui Dong;Zhijiang Du;Wei Wang;Yanyu Su;Wei Dong","doi":"10.1109/TMRB.2026.3654262","DOIUrl":"https://doi.org/10.1109/TMRB.2026.3654262","url":null,"abstract":"Existing continuum manipulators excel at operations because of their omnidirectional bending capabilities. However, their operational performance is constrained by the lack of torsional function along their backbone curves. This paper addresses this issue by proposing a pose reconstruction control strategy that has been successfully applied to tendon-driven continuum manipulators with specific structural designs. This strategy achieves high-precision pose control through bend-torsion decoupling. Additionally, we introduce a model-based backlash function to address the non-linear relationship between the end effector and the actuators and to improve positional and directional accuracy during pose reconstruction. By incorporating indirect rotational compensation and separating control variables, the proposed method enables the manipulator to perform torsional functions along its backbone curves while ensuring applicability to different structural configurations. Simulation and experimental results confirm the efficacy of the proposed method: indirect rotational compensation reduces positional and directional errors by 30.76% and 87.29%, respectively. These findings demonstrate that the proposed approach provides a robust solution for pose reconstruction and high-precision manipulation with continuum manipulators in minimally invasive surgery.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"8 1","pages":"264-276"},"PeriodicalIF":4.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148490104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"IEEE Transactions on Medical Robotics and Bionics Publication Information","authors":"","doi":"10.1109/TMRB.2025.3648629","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3648629","url":null,"abstract":"","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"8 1","pages":"C2-C2"},"PeriodicalIF":4.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11429044","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148487613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}