IEEE transactions on medical robotics and bionics最新文献

IEEE Transactions on Medical Robotics and Bionics Information for Authors IEEE医学机器人与仿生学信息汇刊

IF 3.8

IEEE transactions on medical robotics and bionics Pub Date : 2026-03-10 DOI: 10.1109/TMRB.2025.3648633

引用次数: 0

IEEE Transactions on Medical Robotics and Bionics Society Information 医学机器人与仿生学学会汇刊

IF 3.8

IEEE transactions on medical robotics and bionics Pub Date : 2026-03-10 DOI: 10.1109/TMRB.2025.3648631

引用次数: 0

Minimally Invasive Neurosurgical Robot for MRI-Guided Intratumoral Therapeutic Delivery. 用于mri引导下肿瘤内治疗输送的微创神经外科机器人。

IF 3.8

IEEE transactions on medical robotics and bionics Pub Date : 2026-02-01 Epub Date: 2026-01-14 DOI: 10.1109/tmrb.2026.3654255

Saeed Rezaeian, Hengjie Chen, Chandan Sidhu, Brenda Bartnik-Olson, Behnam Badie, Jun Sheng

{"title":"Minimally Invasive Neurosurgical Robot for MRI-Guided Intratumoral Therapeutic Delivery.","authors":"Saeed Rezaeian, Hengjie Chen, Chandan Sidhu, Brenda Bartnik-Olson, Behnam Badie, Jun Sheng","doi":"10.1109/tmrb.2026.3654255","DOIUrl":"10.1109/tmrb.2026.3654255","url":null,"abstract":"This paper presents the design, modeling, and feasibility study of a magnetic resonance (MR)-conditional steerable neurosurgical robot for minimally invasive intratumoral delivery of therapeutic agents. Immunotherapy is an emerging brain tumor treatment technique but faces challenges due to low trafficking with systemic infusions, particularly in the case of large tumors. To address this limitation, we have developed a novel robotic system capable of delivering therapeutic agents throughout the entire volume of the brain tumor. The robot consists of a straight, rigid outer tube and a flexible inner tube that can navigate along curved paths and articulate in 3D space. A custom-designed injection mechanism consisting of syringes and hydraulic transmission is integrated into the robotic system. A non-magnetic actuation system enables robot navigation to various locations within the tumor. Therefore, by delivering therapeutic agents to individual target locations, the overall trafficking and efficiency can be potentially improved. Characterization-based control experiments yielded a curvature control error of 2.6 ± 1.8% and a relative tip tracking error of 4.2 ± 3.9%, demonstrating the high accuracy of our control strategy. A phantom study demonstrated a significant improvement of the tumor coverage ratio made by the robotic needle compared to the straight needle (73% vs. 29%). An MRI-guided manipulation study showed an acceptable decrease in the signal-to-noise ratio (up to 1.41%) when the robot is manipulated in the water phantom. All these studies synergistically validated the feasibility of our new approach of robotically steerable, MRI-guided therapeutic delivery.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"8 1","pages":"219-231"},"PeriodicalIF":3.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13026081/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147576811","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}

引用次数: 0

A Deep Learning Framework With Domain Generalization and Few-Shot Learning for Locomotion Mode Classification Across Users, Sessions, and Prostheses. 基于领域泛化和少镜头学习的跨用户、会话和假肢运动模式分类深度学习框架。

IF 3.8

IEEE transactions on medical robotics and bionics Pub Date : 2026-02-01 Epub Date: 2025-09-04 DOI: 10.1109/tmrb.2025.3606364

Eugenio Anselmino, Ann M Simon, Levi J Hargrove

{"title":"A Deep Learning Framework With Domain Generalization and Few-Shot Learning for Locomotion Mode Classification Across Users, Sessions, and Prostheses.","authors":"Eugenio Anselmino, Ann M Simon, Levi J Hargrove","doi":"10.1109/tmrb.2025.3606364","DOIUrl":"10.1109/tmrb.2025.3606364","url":null,"abstract":"Transfemoral amputees don and doff their prostheses at least daily, making inter-session classification performance important for clinical implementation of locomotion mode classification algorithms. Here, we present a deep-learning framework based on domain-adversarial training and few-shot learning fine-tuning to classify locomotion modes in unseen sessions or subjects' data across different prosthesis models. We validated the approach with a leave-one-session-out analysis repeated five times and made comparisons to a prosthesis-specific classifier. The dataset was created by merging data from two different prosthesis models (Vanderbilt University, VU, Gen 2 and Gen 3 powered knee-ankle prostheses), for a total of 31 sessions acquired across multiple days from 11 subjects. Subjects performed five locomotion tasks: level walking, incline and decline walking, and stair ascent and descent. Since transitions between different locomotion modes happen at different gait events, the analyses have been repeated for both heel-strike (HS) and toe-off (TO) events. At HS events, the proposed approach achieves a median f1-score of 99.12% and 92.41% on VU Gen 2 and Gen 3 prostheses respectively. At TO events, the proposed approach reaches a median f1-score of 96.83% with VU Gen 2 and 94.36% with VU Gen 3. The proposed framework is a promising solution for locomotion classification on data of previously unseen sessions or subjects, allowing classification on multiple prosthesis models.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"8 1","pages":"77-83"},"PeriodicalIF":3.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13037883/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147596557","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}

引用次数: 0

Novel Compact Tactile Stimulator with Sensing: Designed for Individuals with a Brain Injury and MRI. 新型紧凑型触觉刺激器与传感：设计为个人与脑损伤和MRI。

IF 3.8

IEEE transactions on medical robotics and bionics Pub Date : 2026-02-01 Epub Date: 2025-12-22 DOI: 10.1109/tmrb.2025.3646748

Nahid Kalantaryardebily, Anna C Feldbush, Ardalan Kahak, Suyi Li, Netta Gurari

{"title":"Novel Compact Tactile Stimulator with Sensing: Designed for Individuals with a Brain Injury and MRI.","authors":"Nahid Kalantaryardebily, Anna C Feldbush, Ardalan Kahak, Suyi Li, Netta Gurari","doi":"10.1109/tmrb.2025.3646748","DOIUrl":"10.1109/tmrb.2025.3646748","url":null,"abstract":"Existing tactile assessments indicate that greater than half of individuals living with a brain injury experience tactile impairments, which impede their recovery. Yet, these tactile assessments lack sensitivity, reliability, and ergonomic compatibility for the millions of individuals who experience a clenched hand posture following their brain injury. We present a novel compact, automated tactile stimulator with real-time force estimation, which we designed for use in brain injury and magnetic resonance imaging (MRI). The system interfaces with the finger through a compact-sized stimulator (9 mm height - 18 mm outer diameter) that uses pneumatic actuation to inflate a silicone membrane. The membrane indents a Kirigami cutout, maintaining a constant 6 mm contact area on the finger and enabling precise force application down to 0.01 N with increments as low as 0.01 N. Integrated fiber optic displacement and pressure sensors provide real-time measurement of the indentation of the skin and estimation of forces applied. A physical model and a neural network each estimated the applied forces, with the latter achieving higher accuracy. This novel tactile stimulator system addresses critical limitations of existing devices, enabling accurate, low-force tactile stimulation and measurement, while maintaining a compact size to investigate the neural processes governing tactile perception, including following a brain injury.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"8 1","pages":"492-503"},"PeriodicalIF":3.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13012328/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147517094","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}

引用次数: 0

Interdisciplinary Dialogues on Surgical Data Science: Revising Its Benefits for Surgical Stakeholders and Patients. 外科数据科学的跨学科对话：修订其对外科利益相关者和患者的益处。

IF 3.8

IEEE transactions on medical robotics and bionics Pub Date : 2026-02-01 Epub Date: 2025-12-15 DOI: 10.1109/tmrb.2025.3643994

Marco Bombieri, Arnaud Huaulmé, Kevin Cleary, Stamatia Giannarou, Gernot Kronreif, Franziska Mathis-Ullrich, Evangelos Mazomenos, Krystel Nyangoh Timoh, Micha Pfeiffer, Marco A Zenati, Paolo Fiorini, Pierre Jannin

{"title":"Interdisciplinary Dialogues on Surgical Data Science: Revising Its Benefits for Surgical Stakeholders and Patients.","authors":"Marco Bombieri, Arnaud Huaulmé, Kevin Cleary, Stamatia Giannarou, Gernot Kronreif, Franziska Mathis-Ullrich, Evangelos Mazomenos, Krystel Nyangoh Timoh, Micha Pfeiffer, Marco A Zenati, Paolo Fiorini, Pierre Jannin","doi":"10.1109/tmrb.2025.3643994","DOIUrl":"https://doi.org/10.1109/tmrb.2025.3643994","url":null,"abstract":"Recent advancements in data science and robotic surgery have introduced significant opportunities and challenges in the field of healthcare. To assess their implications, a multidisciplinary panel of experts in medicine and computer science convened to evaluate the potential benefits, risks, and ethical considerations associated with these technologies. The discussion addressed critical topics, including the role of Artificial Intelligence (AI) in enhancing surgical decision-making, the integration of robotics to improve procedural precision, and the broader socioeconomic and psychological impacts on patients and their families. Particular attention was given to the perspectives of key surgical stakeholders, including healthcare professionals and institutions, as well as the implications for equity and accessibility in surgical care. This paper presents a synthesis of the key outcomes from the deliberations. By identifying research gaps and proposing strategic directions, the findings aim to serve as a foundational resource for future investigations and innovations in data-driven and robotic-assisted surgery.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"8 1","pages":"288-295"},"PeriodicalIF":3.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13099167/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147791156","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}

引用次数: 0

Autonomous Slip-Prevention Grip Force Control and Its Potential in Shared Control of Robotic Prosthetic Hands. 自主防滑握力控制及其在机器人假手共享控制中的潜力。

IF 3.8

IEEE transactions on medical robotics and bionics Pub Date : 2026-02-01 Epub Date: 2025-12-15 DOI: 10.1109/tmrb.2025.3644009

Joseph Berman, Varun Nalam, Jie Yin, He Huang

{"title":"Autonomous Slip-Prevention Grip Force Control and Its Potential in Shared Control of Robotic Prosthetic Hands.","authors":"Joseph Berman, Varun Nalam, Jie Yin, He Huang","doi":"10.1109/tmrb.2025.3644009","DOIUrl":"https://doi.org/10.1109/tmrb.2025.3644009","url":null,"abstract":"This study aimed to develop and validate a novel autonomous slip-prevention grip force controller for a robotic prosthetic hand. The controller utilized an optical flow sensor to detect object slippage events, which triggered increases in the desired gripping force within a closed-loop force control system. We first validated the slip-prevention functionality on a bench test platform. Subsequently, the controller was integrated into a simple shared control framework to demonstrate its feasibility in enhancing the grasping function for prosthesis users. In this shared control framework, myoelectric position control (i.e., user control) was employed when the hand was not engaged in a grasp, while the intelligent autonomous grip force control was activated during contact with an object. The feasibility of the shared control was tested with human participants performing tasks involving the grasping, transferring, and releasing of various objects while using and wearing the prosthetic hand. Additionally, we compared the shared control to a myoelectric-only controller (without the autonomous grip force control) in the object manipulation task combined with a secondary cognitive task. The results demonstrated that the proposed automatic grip force controller effectively prevented slips and improved grasping stability under various perturbations. Compared to myoelectric-only control, the shared control reduced the user's cognitive effort required for object manipulation and lead to increased task success. While our designed slip-prevention grip force controller shows significant potential to assist the prosthesis users in improving grasping functionality, further exploration of other shared control paradigms is necessary to maximize user performance and acceptance in the future.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"8 1","pages":"430-441"},"PeriodicalIF":3.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13099084/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147791231","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}

引用次数: 0

Concentric Tube Robot-Assisted Intracerebral Hemorrhage Evacuation: Validation in an Ovine Model. 同心管机器人辅助脑出血引流：在绵羊模型中的验证。

IF 3.8

IEEE transactions on medical robotics and bionics Pub Date : 2026-02-01 Epub Date: 2026-01-14 DOI: 10.1109/tmrb.2026.3654269

Anthony L Gunderman, Joe Sommer, Saikat Sengupta, Dimitri Sigounas, Kevin Cleary, Yue Chen

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Data-Based Modeling of Twisted Coiled Actuators 基于数据的扭曲线圈执行器建模

IF 3.8

IEEE transactions on medical robotics and bionics Pub Date : 2026-01-14 DOI: 10.1109/TMRB.2026.3654133

Parisa Daemi;Alex Lizotte;Michael D. Naish;Aaron D. Price;Ana Luisa Trejos

{"title":"Data-Based Modeling of Twisted Coiled Actuators","authors":"Parisa Daemi;Alex Lizotte;Michael D. Naish;Aaron D. Price;Ana Luisa Trejos","doi":"10.1109/TMRB.2026.3654133","DOIUrl":"https://doi.org/10.1109/TMRB.2026.3654133","url":null,"abstract":"Twisted Coiled Actuators (TCAs) have emerged as a promising option for developing artificial muscles with high power-to-weight ratios and inexpensive fabrication. However, their nonlinear time-variant dynamics, hysteresis, and unmodeled parameters pose challenges in their control, which limits their use in designing wearable exoskeleton devices. To overcome these challenges, this study developed and validated a data-based model, the Nonlinear AutoRegressive eXogenous (NARX) neural network, for predicting the nonlinear dynamic behaviors of TCAs cooled by forced air. The model considers the characterization of both heating and cooling systems on the actuation of TCAs. The NARX model was trained and validated using an experimental setup that adopts a novel cooling apparatus for implementation in soft wearable devices. The precision of the NARX model resulted in <inline-formula> <tex-math>${R}^{2}$ </tex-math></inline-formula> values of 0.99 and 0.81 for training and testing, respectively. The results demonstrate the potential of the developed model for improving the control systems of wearable soft robotic devices using TCAs.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"8 1","pages":"526-537"},"PeriodicalIF":3.8,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147440672","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}

引用次数: 0

Soft Robotic Bio-Inspired Breast Pump 软体机器人仿生吸乳器

IF 3.8

IEEE transactions on medical robotics and bionics Pub Date : 2025-12-24 DOI: 10.1109/TMRB.2025.3644012

Kirsten Lussenburg;Giovanni Colucci;Giuseppe Quaglia;Cosimo Della Santina;Aimée Sakes

{"title":"Soft Robotic Bio-Inspired Breast Pump","authors":"Kirsten Lussenburg;Giovanni Colucci;Giuseppe Quaglia;Cosimo Della Santina;Aimée Sakes","doi":"10.1109/TMRB.2025.3644012","DOIUrl":"https://doi.org/10.1109/TMRB.2025.3644012","url":null,"abstract":"Breastfeeding is essential for infant nutrition, but the increasing number of women returning to work before weaning highlights the need for efficient and comfortable milk expression methods. Traditional breast pumps rely solely on vacuum suction, which can cause discomfort, tissue damage, and longer extraction times compared to natural nursing. This study aims to develop a breast pump that better mimics the biomechanics of infant breastfeeding to improve comfort and efficiency. We investigated two actuator designs—membrane and soft pleated—integrated into the breast shield to replicate infant sucking. The pleated actuator proved most effective, offering a wide range of expansion and contraction. Unlike traditional pumps, vacuum is applied through radial expansion, allowing the nipple to widen rather than elongate, closely simulating infant tongue movements. The breast shield was fabricated using additive manufacturing with soft, elastic materials, enabling complex geometries and varied stiffness. The prototype was tested against a commercial pump using an artificial breast phantom. Results suggest this design can enhance milk output, reduce pumping time, and improve user comfort. By merging soft robotics with biological insights, our approach offers a promising alternative to conventional breast pumps.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"8 1","pages":"538-550"},"PeriodicalIF":3.8,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11313872","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147440583","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}

引用次数: 0