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Corretions to “An Automatic Navigation Framework for Magnetic Fish-Like Millirobot in Uncertain Dynamic Environments”

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IEEE robotics and Automation Letters 2025年第4期10卷 3875-3875页

作者： Chenyao Tian Xinjian Fan Jingzhi Jia Zhan Yang Hui Xie State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China School of Mechanical and Electrical Engineering Soochow University Suzhou China

The first author's name was misspelled as “Chengyao Tian” in [1], containing an extraneous “g”. The correct spelling is “Chenyao Tian”.

关键词： Navigation

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Magnetic-Actuated Flexible Instruments with Enhanced Bending Capability through Magnetic Distribution Optimization

Magnetic-Actuated Flexible Instruments with Enhanced Bending...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Yuanrui Huang Runyu Ma Jian Hu Mingcong Chen Jian Chen Hongbin Liu School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China School of General Engineering Beihang University Beijing China Centre of AI and Robotics (CAIR) Hong Kong Institute of Science & Innovation Chinese Academy of Sciences

Magnetically-actuated flexible surgical robot has promising applications for ultra-narrow and tortuous orifices. However, maximizing its bending capability and manipulability remains a significant hurdle for clinical use. In this study, we introduce an objective function that can accurately predict a catheter's bending angle with given numbers of internal permanent magnets (IPMs) under various magnetic fields through iterative calculation. The optimal magnets distribution that yields the maximal controllable bending angle, could be determined by optimizing this objective function. The effectiveness of this method is validated through simulations and experiments. Additionally, we propose a simple control scheme to control the bending angle of the magnetically-actuated catheter based on the piecewise constant curvature model. The experimental results demonstrate that the proposed method significantly improves the motion accuracy of the catheter. The catheter with the optimized magnet distribution achieved superior tracking performance with an Integral Absolute Error (IAE) of 1.08 rad·s and maximal controllable bending angle of 150°.

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Microwave characterization of exotic resonant states in dielectric resonators

Microwave characterization of exotic resonant states in diel...

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Electronic Technology, Communication and Information (ICETCI), IEEE International Conference on

作者： Tong Wu Andrey B. Evlyukhin Vladimir R. Tuz State Key Laboratory on Integrated Optoelectronics College of Electronic Science and Engineering International Center of Future Science Jilin University Changchun China Cluster of Excellence PhoenixD Institute of Quantum Optics Leibniz University Hannover Germany School of Radiophysics Biomedical Electronics and Computer Systems V. N. Karazin Kharkiv National University Kharkiv Ukraine

ISBN: (数字)9798350361643

ISBN: (纸本)9798350361650

In this study, we design a structure consisting of the radial arrangement of several vertically standing dielectric disks (resonators) so that such a ring cluster supports exotic toroidal dipole mode excitation. Subsequently, the characteristics of a system composed of two identical rings with a change in the distance are studied to reveal how to affect the peculiarities of the coupling between two toroidal dipole modes. The manifestation of toroidal dipole coupling is confirmed by checking the extinction cross-section, near-field distributions, and induced toroidal moments obtained from both full-wave numerical simulation and microwave experiments. To experiment, particles are made from commercially available ceramics. During the measurements, standard microwave equipment is used to characterize the toroidal dipole coupling within the frequency band of 1−10 GHz. Since the structure comprises simple dielectric disks without any metallic elements, the proposed designs are hopefully scalable down to the micrometer or nanometer scale considering their practical applications as building blocks in metamaterials operated on the radiation-less exotic toroidal and anapole states.

关键词： Microwave measurement Couplings Microwave integrated circuits Masers Microwave communication Particle measurements Dielectrics

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Improving Assessment in Kidney Transplantation by Multitask General Path Model

SSRN

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SSRN 2023年

作者： Lan, Qing Chen, Xiaoyu Li, Murong Robertson, John Lei, Yong Jin, Ran Grado Department of Industrial and Systems Engineering Virginia Tech BlacksburgVA24061 United States Department of Industrial Engineering University of Louisville LouisvilleKY40292 United States State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou310013 China School of Biomedical Engineering and Sciences Virginia Tech BlacksburgVA24061 United States 1145 Perry Street BlacksburgVA24061 United States

Background and Objective: Kidney transplantation helps end-stage patients regain health and quality-of-life. The decisions for matching donor kidneys and recipients affect success of transplantation. However, current kidney matching decision procedures do not consider viability loss during preservation. The objective here is to forecast heterogeneous kidney viability, based on historical datasets to support kidney matching ***: Six recently procured porcine kidneys were used to conduct viability assessment experiments to validate the proposed multitask general path model. The model forecasts kidney viability by transferring knowledge from learning the commonality of all kidneys and the heterogeneity of each ***: The proposed model provides exactly accurate kidney viability forecasting results compared to the state-of-the-art models because it quantifies the degradation information from trajectory of a viability loss path. It transfers knowledge of common effects from all kidneys and identifies individual effects of each ***: This method can be readily extended to other decision-making scenarios in kidney transplantation to improve overall assessment performance. For example, analytical generalizations gained by modeling have been validated based on needle biopsy data targeting the improvement of tissue extraction accuracy. The proposed model applied in multiple kidney assessment processes in transplantation can potentially reduce the kidney discard rate to benefit more patients. © 2023, The Authors. All rights reserved.

关键词： Forecasting

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Improving assessment in kidney transplantation by multitask general path model

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Computer Methods and Programs in Biomedicine Update 2023年 4卷

作者： Lan, Qing Chen, Xiaoyu Li, Murong Robertson, John Lei, Yong Jin, Ran Grado Department of Industrial and Systems Engineering Virginia Tech Blacksburg 24061 VA United States Department of Industrial and Systems Engineering State University of New York at Buffalo Buffalo 14260 NY United States State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou 310013 China Department of Biomedical Engineering and Sciences Virginia Tech Blacksburg 24061 VA United States

Background: Kidney transplantation is a pivotal intervention for individuals suffering from end-stage renal diseases, offering them the potential for restored health and an enhanced quality of life. However, the successful outcome of these transplantation procedures relies significantly on the careful matching of donor kidneys with compatible recipients. Unfortunately, the current kidney-matching process overlooks viability changes during preservation. The objective of this study is to investigate the potential for forecasting heterogeneous kidney viability using historical datasets to enhance kidney-matching decision-making. Methods: We present a multitask general path model designed for continuous forecasting of kidney viability during preservation. This model quantifies likely viability trajectories of donor kidneys based on pathologist-provided biopsy scores during preservation, explicitly addressing both inter-kidney similarities and individual differences. To validate our model, we conducted viability assessments on six recently procured porcine kidneys and needle biopsy insertion experiments on phantoms, utilizing a leave-one-kidney-out cross-validation approach. Results: Our proposed model consistently exhibited the lowest forecasting error (averaged root mean squared error, RMSEbegin=0.61 at the beginning and RMSEend<0.05 at the end of kidney preservation) when compared to widely-adopted benchmark models, including multitask learning (RMSEbegin=0.65, RMSEend=0.54), general path (RMSEbegin=0.58, RMSEend=0.49), and generalized linear models (RMSEbegin=0.59, RMSEend=0.56) in the kidney viability assessment study. Additionally, across all testing scenarios, the forecasting RMSE of our model rapidly diminished with minimal initial kidney samples during preservation. Similar patterns were observed from the needle biopsy insertion study. Conclusions: In both validation studies, our model outperformed benchmark models and exhibited rapid learning with limited initi

关键词： Data-driven decision-making Kidney assessment in transplantation Kidney viability forecasting Multitask general path model Needle biopsy

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Hair Direction Detection*

Hair Direction Detection*

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WRC Symposium on Advanced robotics and Automation (WRC SARA)

作者： Peng Ba Pengyi Wang Hongde Wu Qian Yang Yongqiang Feng Junchen Wang Yida David Hu Changsheng Li Wenyong Liu Shaolong Kuang Bai-Quan Su Medical Robotics Laboratory School of Intelligent Engineering and Automation Beijing University of Posts and Telecommunications Beijing China Plastic Surgery Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China School of Mechanical Engineering and Automation Beihang University Beijing China Brigham and Women’s Hospital Harvard Medical School Boston MA USA School of Mechatronical Engineering Beijing Institute of Technology Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China Key Laboratory for Biomechanics and Mechanobiology of Chinese Education Ministry Beijing Advanced Innovation Centre for Biomedical Engineering School of Biological Science and Medical Engineering Beihang University Beijing China School of Health Science and Environmental Engineering Shenzhen University of Technology Shenzhen China

ISBN: (数字)9798331506100

ISBN: (纸本)9798331506117

Hair direction is an important external feature of hair, and recognising hair direction is a prerequisite for processing hair. In this paper, a new algorithm is proposed and systematically verified experimentally for the problem of recognising hair direction. The main goal of this paper is to develop an algorithm that can identify hair direction in a complex image environment. A curve segment analysis method based on image skeletonisation is adopted, which is based on skeleton extraction, intersection identification, curve segmentation and direction prediction. In addition, this paper combines the technique of non-maximal value suppression and PCA analysis to improve the accuracy and stability of the estimation. In the experimental design, this paper chooses a representative image dataset to verify the effectiveness of this paper's algorithm. The experimental process includes the steps of image preprocessing, skeletonisation processing, intersection detection and merging, and direction prediction. The experimental results show that the method in this paper can accurately and effectively identify the hair direction. The main contribution of this paper is to propose a new hair direction recognition method and experimentally verify its effectiveness and accuracy in complex backgrounds.

关键词： Hair Image segmentation Accuracy Three-dimensional displays Merging Prediction algorithms Stability analysis

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Efficient Planar Pose Estimation via UWB Measurements

Efficient Planar Pose Estimation via UWB Measurements

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IEEE International Conference on robotics and Automation (ICRA)

作者： Haodong Jiang Wentao Wang Yuan Shen Xinghan Li Xiaoqiang Ren Biqiang Mu Junfeng Wu Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS) School of Data Science the Chinese University of HongKong Shenzhen P. R. China College of Control Science and Engineering and the State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou P. R. China School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing P. R. China School of Mechatronic Engineering and Automation Shanghai University Shanghai P. R. China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing P. R. China

state estimation is an essential part of autonomous systems. Integrating the Ultra-Wideband (UWB) technique has been shown to correct the long-term estimation drift and bypass the complexity of loop closure detection. However, few works on robotics treat UWB as a stand-alone state estimation solution. The primary purpose of this work is to investigate planar pose estimation using only UWB range measurements. We prove the excellent property of a two-step scheme, which says we can refine a consistent estimator to be asymptotically efficient by one step of Gauss-Newton iteration. Grounded on this result, we design the GN-ULS estimator, which reduces the computation time significantly compared to previous methods and presents the possibility of using only UWB for real-time state estimation.

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Co-Axial Slender Tubular robot (CAST): Towards Robotized Operation for Transorbital Neurosurgery with Minimal Invasiveness

Co-Axial Slender Tubular robot (CAST): Towards Robotized Ope...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Shuai Wang Qingxiang Zhao Jian Chen Mingcong Chen Guanglin Cao Jian Hu Runfeng Zhu Danny Tat Ming Chan Ming Feng Hongbin Liu centre for Artificial Intelligence and Robotics (CAIR) Hong Kong Institute of Science and Innovation Chinese Academy of Sciences CAIR and CASIA Department of Biomedical Engineering City University of Hong Kong HKSAR School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences (CASIA) Beijing China Department of Mechanical Engineering The Hong Kong Polytechnic University Department of Surgery The Chinese University of Hong Kong HKSAR Beijing Union Medical College Hospital

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Transorbital Neuro Surgery (TNS) offers a novel treatment towards the lesion inside skull pursuing minimal invasiveness. Most conventional TNS tools are rigid and straight, limiting the dexterity and accessibility in passing a small port. Bendable and steerable surgical tools provides an alternative for this issue. In this work, we proposed a dual-segment slender surgical robot arm for TNS, which is a Co-Axial Slender Tubular robot (CAST), and modelled it using novel approaches. Another contribution is tendon-mortise shaped slits along the axial direction, enhancing the overall stiffness. The bending of CAST is actuated by pushing/pulling distance, and the maximum diameter is only 1.7mm with high dexterity after mounting on a rigid robot arm. Experiments demonstrates that the proposed the slit design doubles the stiffness properties compared to traditional rectangle slit designs. The path-following task shows that the position error was maximally 3mm in open-looped control. Test on a skull model demonstrates that the whole system could successfully perform electrocoagulation procedure inside the depth of skull in a robotized manner effectively.

关键词： Medical robotics Limiting Instruments Robot vision systems Kinematics Manipulators Neurosurgery

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DNA tetrahedron-mediated immune-sandwich assay for rapid and sensitive detection of PSA through a microfluidic electrochemical detection system

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Microsystems & Nanoengineering 2021年第2期7卷 221-230页

作者： Dezhi Feng Jing Su Yi Xu Guifang He Chenguang Wang Xiao Wang Tingrui Pan Xianting Ding Xianqiang Mi Key Laboratory of Functional Materials for Informatics Shanghai Institute of Microsystem and Information TechnologyChinese Academy of Sciences200050ShanghaiChina Shanghai Advanced Research Institute Chinese Academy of Sciences201210ShanghaiChina University of Chinese Academy of Sciences 100049BeijingChina State Key Laboratory of Oncogenes and Related Genes Institute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong University200030ShanghaiChina School of Life Sciences Shanghai University200444ShanghaiChina Shenzhen Institutes of Advanced Technology Chinese Academy of Science518055ShenzhenChina CAS Center for Excellence in Superconducting Electronics (CENSE)200050ShanghaiChina Key Laboratory of Systems Health Science of Zhejiang Province Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesChinese Academy of Sciences310024HangzhouChina

Prostate-specific antigen(PSA)is the most widely used biomarker for the early diagnosis of prostate *** methods for PSA detection are burdened with some limitations and require ***,we developed a novel microfluidic–electrochemical(μFEC)detection system for PSA ***,we constructed an electrochemical biosensor based on screen-printed electrodes(SPEs)with modification of gold nanoflowers(Au NFs)and DNA tetrahedron structural probes(TSPs),which showed great detection ***,we fabricated microfluidic chips by DNA TSP-Au NF-modified SPEs and a PDMS layer with designed dense meandering ***,theμFEC detection system was achieved based on microfluidic chips integrated with the liquid automatic conveying unit and electrochemical detection ***μFEC system we developed acquired great detection performance for PSA detection in PBS *** PSA assays in spiked serum samples of theμFEC system,we obtained a linear dynamic range of 1–100 ng/mL with a limit of detection of 0.2 ng/mL and a total reaction time<25 *** serum samples of prostate cancer patients presented a strong correlation between the“gold-standard”chemiluminescence assays and theμFEC *** terms of operation procedure,cost,and reaction time,our method was superior to the current methods for PSA detection and shows great potential for practical clinical application in the future.

关键词： fluid diagnosis system

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EndoMamba: An Efficient Foundation Model for Endoscopic Videos via Hierarchical Pre-training

arXiv

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arXiv 2025年

作者： Tian, Qingyao Liao, Huai Huang, Xinyan Yang, Bingyu Lei, Dongdong Ourselin, Sebastien Liu, Hongbin State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Dept. of Radiology The First Affiliated Hospital Sun Yat-sen University Guangzhou China Centre for Artificial Intelligence and Robotics Chinese Academy of Sciences Hong Kong School of Engineering and Imaging Sciences King’s College London United Kingdom

Endoscopic video-based tasks, such as visual navigation and surgical phase recognition, play a crucial role in minimally invasive surgeries by providing real-time assistance. While recent video foundation models have shown promise, their applications are hindered by (1) computational inefficiencies and (2) suboptimal performance caused by limited data for pre-training in endoscopy. To address these issues, we present EndoMamba, a foundation model designed for real-time inference while learning generalized spatiotemporal representations. First, to mitigate computational inefficiencies, we propose the EndoMamba backbone, optimized for real-time inference. Inspired by recent advancements in state space models, EndoMamba integrates Bidirectional Mamba blocks for spatial modeling within individual frames and vanilla Mamba blocks for past-to-present reasoning across the temporal domain. This design enables both strong spatiotemporal modeling and efficient inference in online video streams. Second, we propose a self-supervised hierarchical pre-training diagram to enhance EndoMamba’s representation learning using endoscopic videos and incorporating general video domain knowledge. Specifically, our approach combines masked reconstruction with auxiliary supervision, leveraging low-level reconstruction to capture spatial-temporal structures and high-level alignment to transfer broader knowledge from a pretrained general-video domain foundation model. Extensive experiments on four downstream tasks—classification, segmentation, surgical phase recognition, and localization—demonstrate that EndoMamba outperforms existing foundation models and task-specific methods while maintaining real-time inference speed. The source code will be released upon acceptance. Copyright © 2025, The Authors. All rights reserved.

关键词： Endoscopy

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