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International Symposium on medical robotics (ISMR)

作者： Florian Heemeyer Anirudh Choudhary Jaydev P. Desai Medical Robotics and Automation Laboratory Georgia Institute of Technology Atlanta GA 30332 USA

ISBN: (数字)9781728154886

ISBN: (纸本)9781728154893

Image intensifiers, also known as C-arms, are important and low-cost tools for surgeons to guide minimally-invasive procedures. However, image intensifiers suffer from several distortions that can impede their ability to provide accurate guidance. These distortions can be misleading during an automated minimally-invasive surgery where the accurate shape-estimation of the robot is essential. Since the distortion strongly depends on the orientation of the C-arm during image acquisition, we propose an approach for distortion correction in combination with a calibration procedure to precisely estimate its orientation. To estimate an accurate distortion correction function, we take images of a calibration grid in 258 different C-arm orientations and apply polynomial regression on these images. The C-arm is calibrated using an external camera along with optical flow and point-correspondence-based matching to allow sufficient pose estimation. Our C-arm tracking algorithm estimates the pose of the C-arm with a mean absolute deviation of 0.2° and 0.3° for 5° and 10° relative motion. The proposed C-arm calibration procedure allows the positioning of the C-arm within an error range of 0.5°. The resulting distortion correction leads to a mean pixel displacement of 0.30 pixel.

关键词： Distortion Calibration Cameras Optical distortion Tracking Optical imaging Adaptive optics

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Quantitative Characterization of Cell Physiological State Based on Dynamical Cell Mechanics for Drug Efficacy Indication

SSRN

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SSRN 2022年

作者： Ma, Shuang Wu, Junfeng Liu, Zhihua He, Rong Wang, Yuechao Liu, Lianqing Wang, Tianlu Wang, Wenxue State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Department of Thoracic Surgery Cancer Hospital of China Medical University Liaoning Cancer Hospital and Institute Shenyang110042 China Department of Radiotherapy Cancer Hospital of China Medical University Liaoning Cancer Hospital and Institute Shenyang110042 China

Cell mechanics is essential to cell development and function and its dynamics evolution reflects the physiological state of cells. Here, we investigate the dynamical mechanical properties, viscoelasticity and Young’s modulus, of single cells (MCF-7 and HEK293) under various drug (PTX and DOX) conditions, and present two mathematical approaches to quantitatively characterizing the cell physiological state. It is demonstrated that the cellular mechanical properties upon the drug action increase over time and tend to saturate, and can be mathematically characterized by a linear time-invariant dynamical model. It is shown that the transition matrices of dynamical cell systems significantly improve the classification accuracies of the cells under different drug actions. Furthermore, it is revealed that there exists a positive linear correlation between the cytoskeleton density and the cellular mechanical properties, and, regardless of drug action conditions, the physiological state of a cell in terms of its cytoskeleton density can be predicted from its mechanical properties by a linear regression model. It is also indicated that the viscoelasticity properties are a better biomarker than the Young’s modulus to characterize the cell state. This study builds a relationship between the cellular mechanical properties and the cellular physiological state, adding information for evaluating drug *** Information: This work was supported by the National Natural Science Foundation of China (Grant Nos. U1908215, 61925307, 62003338);Liaoning Revitalization Talents Program (Grant No. XLYC2002014);Natural Science Foundation of Liaoning Province of China (Grant No. 2020-ZLLH-47), and Joint fund of Science & Technology Department of Liaoning Province and State Key laboratory of robotics， China (Grant No. 2019-KF-01-01).Declaration of Interests: The authors declare no conflict of interest. © 2022, The Authors. All rights reserved.

关键词： Cells

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Low-Friction Soft Robots for Targeted Bacterial Infection Treatment in Gastrointestinal Tract

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Cyborg and Bionic Systems 2024年第1期5卷 162-176页

作者： Ben Wang Yunrui Chen Zhicheng Ye Haidong Yu Kai Fung Chan Tiantian Xu Zhiguang Guo Weimin Liu Li Zhang College of Chemistry and Environmental Engineering Shenzhen UniversityShenzhen 518060China Guangxi Key Laboratory of Processing for Non-Ferrous Metals and Featured Materials School of ResourceEnvironments and MaterialsGuangxi UniversityNanning 530004China Chow Yuk Ho Technology Centre for Innovative Medicine The Chinese University of Hong KongShatinNew TerritoriesHong Kong SARChina Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Key Laboratory of Biomedical Imaging Science and System Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Hubei Collaborative Innovation Centre for Advanced Organic Chemical Materials and Ministry of Education Key Laboratory for the Green Preparation and Application of Functional Materials Hubei UniversityWuhan 430062China State Key Laboratory of Solid Lubrication Lanzhou Institute of Chemical PhysicsChinese Academy of ScienceLanzhou 730000China Department of Mechanical and Automation Engineering The Chinese University of Hong KongShatinNew TerritoriesHong Kong SARChina Multi-Scale Medical Robotics Center Hong Kong Science ParkShatinNew TerritoriesHong Kong SARChina

Untethered and self-transformable miniature robots are capable of performing reconfigurable deformation and on-demand locomotion,which aid the traversal toward various lumens,and bring revolutionary changes for targeted delivery in gastrointestinal(GI)***,the viscous non-Newtonian liquid environment and plicae gastricae obstacles severely hamper high-precision actuation and payload ***,we developed a low-friction soft robot by assembly of densely arranged cone structures and grafting of hydrophobic *** magnetic orientation encoded robot can move in multiple modes,with a substantially reduced drag,terrain adaptability,and improved motion velocity across the non-Newtonian ***,the robot stiffness can be reversibly controlled with magnetically induced hardening,enabling on-site scratching and destruction of antibiotic-ineradicable polymeric matrix in biofilms with a low-frequency magnetic ***,the magnetocaloric effect can be utilized to eradicate the bacteria by magnetocaloric effect under high-frequency alternating *** verify the potential applications inside the body,the clinical imaging-guided actuation platforms were developed for vision-based control and delivery of the *** developed low-friction robots and clinical imaging-guided actuation platforms show their high potential to perform bacterial infection therapy in various lumens inside the body.

关键词： gastrointestinal tract reconfigurable deformation targeted bacterial infection treatment low friction soft robots plicae gastricae obstacles assembly densely arranged cone structures targeted delivery grafting hy

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ARST: Auto-Regressive Surgical Transformer for Phase Recognition from Laparoscopic Videos

arXiv

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arXiv 2022年

作者： Zou, Xiaoyang Liu, Wenyong Wang, Junchen Tao, Rong Zheng, Guoyan Institute of Medical Robotics School of Biomedical Engineering Shanghai Jiao Tong University Shanghai200240 China Key Laboratory for Biomechanics and Mechanobiology of Ministry of Eduction Beijing Advanced Innovation Center for Biomedical Engineering School of Biological Science and Medical Engineering Beihang University Beijing100083 China School of Mechanical Engineering and Automation Beihang University Beijing100091 China

Phase recognition plays an essential role for surgical workflow analysis in computer assisted intervention. Transformer, originally proposed for sequential data modeling in natural language processing, has been successfully applied to surgical phase recognition. Existing works based on transformer mainly focus on modeling attention dependency, without introducing auto-regression. In this work, an Auto-Regressive Surgical Transformer, referred as ARST, is first proposed for on-line surgical phase recognition from laparoscopic videos, modeling the inter-phase correlation implicitly by conditional probability distribution. To reduce inference bias and to enhance phase consistency, we further develop a consistency constraint inference strategy based on auto-regression. We conduct comprehensive validations on a well-known public dataset Cholec80. Experimental results show that our method outperforms the state-of-the-art methods both quantitatively and qualitatively, and achieves an inference rate of 66 frames per second (fps). Copyright © 2022, The Authors. All rights reserved.

关键词： Probability distributions

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An OCSVM Based Assessment Method for Robotic Rehabilitation

An OCSVM Based Assessment Method for Robotic Rehabilitation

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Chinese automation Congress (CAC)

作者： Xu Zhong Fan-Gang Meng Bi Zhang Jie Yao Xiao-Liang Fan Xin-Gang Zhao State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China School of Intelligent Medicine China Medical University Shenyang China Industrial and Commercial Bank of China Jinan China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781665426480

The automatic assessment of rehabilitation level is an important part of the automatic rehabilitation training system. In order to carry out an accurate rehabilitation grade assessment for patients with ankle dyskinesia, this paper proposes a grade-variable rehabilitation assessment strategy. Firstly, the plantar pressure insoles are used to collect normal people's plantar pressure data samples as training set of the model and a decision boundary is obtained through the One-Class Support Vector Machine (OCSVM) model for the detection of abnormal data. Then, the patient's plantar pressure data is used as a test set to output the abnormal degree of the current ankle dyskinesia. The abnormal degree is introduced into the control process of the ankle rehabilitation robot, corresponding to realize the rehabilitation strategy of variable grades. Experiments verify that the model established in this paper is a concise, staged and graded periodical rehabilitation assessment method.

关键词： Training Support vector machines automation Process control Transforms Patient rehabilitation Rehabilitation robotics

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Optimizing Combinatory Drugs using Markov Chain-Based Models

Research Square

引用

Research Square 2021年

作者： Ma, Shuang Dang, Dan Wang, Wenxue Wang, Yuechao Liu, Lianqing State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Faculty of Medical Devices Shenyang Pharmaceutical University Shenyang China

Background: Combinatory drug therapy for complex diseases, such as HSV infection and cancers, has a more significant efficacy than single-drug treatment. However, one key challenge is how to effectively and efficiently determine the optimal concentrations of combinatory drugs because the number of drug combinations increases exponentially with the types of drugs. Results: In this study, a searching method based on Markov chain is presented to optimize the combinatory drug concentrations. Its performance is compared with four stochastic optimization algorithms as benchmark methods by simulation and biological experiements. Both simulation results and experimental data demonstrate that the Markov Chain-based approach is more reliable and efficient than the benchmark algorithms. Conclusion: This article provides a versatile method for combinatory drug screening, which is of great significance for clinical drug combination therapy. © 2021, CC BY.

关键词： Disease control

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MG-SLAM: Structure Gaussian Splatting SLAM with Manhattan World Hypothesis

arXiv

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arXiv 2024年

作者： Liu, Shuhong Deng, Tianchen Zhou, Heng Li, Liuzhuozheng Wang, Hongyu Wang, Danwei Li, Mingrui Department of Information Science and Technology Department of Complexity Science and Engineering The University of Tokyo Tokyo113-8654 Japan Institute of Medical Robotics Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Department of Mechanical Engineering Columbia University New York10027 United States School of Electrical and Electronic Engineering Nanyang Technological University Singapore Department of Computer Science Dalian University of Technology Dalian116024 China

Gaussian Splatting SLAMs have made significant advancements in improving the efficiency and fidelity of real-time reconstructions. However, these systems often encounter incomplete reconstructions in complex indoor environments, characterized by substantial holes due to unobserved geometry caused by obstacles or limited view angles. To address this challenge, we present Manhattan Gaussian SLAM, an RGB-D system that leverages the Manhattan World hypothesis to enhance geometric accuracy and completeness. By seamlessly integrating fused line segments derived from structured scenes, our method ensures robust tracking in textureless indoor areas. Moreover, The extracted lines and planar surface assumption allow strategic interpolation of new Gaussians in regions of missing geometry, enabling efficient scene completion. Extensive experiments conducted on both synthetic and real-world scenes demonstrate that these advancements enable our method to achieve state-of-the-art performance, marking a substantial improvement in the capabilities of Gaussian SLAM systems. © 2024, CC BY.

关键词： Gaussian distribution

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Exploiting the Intrinsic Neighborhood Semantic Structure for Domain Adaptation in EEG-based Emotion Recognition

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IEEE Transactions on Affective Computing 2025年

作者： Yang, Yi Wang, Ze Song, Yu Jia, Ziyu Wang, Boyu Jung, Tzyy-Ping Wan, Feng Macau University of Science and Technology Macao Centre for Mathematical Sciences Respiratory Disease AI Laboratory on Epidemic Intelligence and Medical Big Data Instrument Applications Faculty of Innovation Engineering 999078 China Tianjin University of Technology School of Electrical Engineering and Automation Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin300384 China Chinese Academy of Sciences Beijing Key Laboratory of Brainnetome and Brain-Computer Interface and Brainnetome Center Institute of Automation Beijing100045 China Western University Department of Computer Science Brain Mind Institute LondonONN6A 3K7 Canada University of California at San Diego Swartz Center for Computational Neuroscience Institute for Neural Computation La Jolla CA92093 United States University of Macau Department of Electrical and Computer Engineering Faculty of Science and Technology China University of Macau Centre for Cognitive and Brain Sciences Centre for Artificial Intelligence and Robotics Institute of Collaborative Innovation 999078 China

Due to the inherent non-stationarity and individual differences present in electroencephalogram (EEG) signals, developing a generalizable model that performs well on new subjects is challenging in EEG-based emotion recognition. Most existing domain adaptation (DA) methods typically mitigate these discrepancies by aligning the marginal distributions of domain feature representations. However, when there is a significant difference in the class-conditional distribution between domain features and labels, the domain-invariant features learned by aligning marginal distributions may have limited discriminative ability for unlabeled target instances or even prove counterproductive. To address this issue, we propose a Neighborhood Semantic Aware Learning-based Dynamic Graph Attention Convolution (NSAL-DGAT) approach that learns target semantic information by considering the inter-domain semantic topological structure, thereby improving classifier adaptation for target instances. Specifically, the proposed NSAL framework is designed to capitalize on the insight that after domain feature alignment, some target samples and their neighboring source samples exhibit similar semantics. By leveraging the neighborhood topological structure, we extract and incorporate semantic target features to train a more transferable classifier. Besides, we implement an entropy weighting mechanism to emphasize representative target semantic information, encouraging target instances to prioritize high-confidence individuals within the source neighborhood. We have conducted extensive experiments on the public SEED dataset and our collected the Hearing-Impaired EEG Dataset (HIED). The experimental results underscore the efficacy of our proposed NSAL-DGAT approach, showcasing state-of-the-art accuracy in subject-dependent as well as subject-independent scenarios. The source code is available at https://***/YYingDL/NSAL-DGAT. © 2010-2012 IEEE.

关键词： Speech analysis

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Evaluation of Disinfection Methods for Autonomous Mobile Robots Used in Hospital Logistics in Emergency Departments

引用

The Journal of hospital infection 2025年 162卷 17-25页

作者： Przemysław Kardas Filip Bielec Małgorzata Brauncajs Paweł Lewek Dariusz Timler Ewelina Łojewska Marcello Chiurazzi Neri Niccolò Dei Gastone Ciuti Raquel Juliá Ros Víctor Solaz Estevan Alessia Maccaro Leandro Pecchia Beatriz Merino Alejandro Medrano Thomas Penzel Giuseppe Fico Department of Family Medicine Medical University of Lodz Lodz 90419 Poland. Department of Microbiology and Laboratory Medical Immunology Medical University of Lodz Lodz 90419 Poland. Department of Emergency and Disaster Medicine Medical University of Lodz Lodz 90419 Poland. Office for Research Strategies and Development Medical University of Lodz Lodz 90419 Poland. BioRobotics Institute & Department of Excellence in Robotics and AI Scuola Superiore Sant'Anna Pisa 56127 Italy. Robotnik Automation S.L. Paterna Valencia 46980 Spain. Department of Social Sciences University of Naples Federico II Applied Biomedical Signal Processing Intelligent eHealth Laboratory School of Engineering University of Warwick Coventry CV4 7AL UK. Applied Biomedical Signal Processing Intelligent eHealth Laboratory School of Engineering University of Warwick Coventry CV4 7AL UK Department of Engineering University Campus Bio-Medico of Rome Via Alvaro del Portillo 21 Rome 00128 Italy. Life Supporting Technologies Departamento de Tecnología Fotónica y Bioingeniería Universidad Politècnica de Madrid Madrid Spain. Interdisciplinary Center of Sleep Medicine Charité University Medicine Berlin Berlin Germany.

BACKGROUND:Autonomous Mobile Robots (AMRs) have been increasingly used in hospital logistics, particularly in high-risk areas, such as Emergency Departments (EDs), to streamline operations, reduce staff fatigue, and minimize infection risks. However, their effective disinfection remains a critical concern, especially when it comes to solutions aimed at preventing spread of multi-drug-resistant organisms. OBJECTIVE:This study evaluated the microbiological cleanliness and effectiveness of various disinfection methods for AMRs in real-life hospital logistics settings, with a particular focus on their application in EDs. METHODS:The HOSBOT, an AMR designed for hospital logistics, was deployed in a tertiary hospital for two weeks and validated for transport of biological samples. Microbiological contamination was assessed at multiple robot sites before and after disinfection, using two methods, i.e. manual wiping with a standard disinfectant and non-contact fumigation with low temperature vaporized hydrogen peroxide. Contamination levels were evaluated using quantitative and qualitative microbiological techniques, and a threshold of <2.5 colony-forming units/cm for critical environments, recommended by the Centers for Disease Control and Prevention (CDC), was considered as proof of success. RESULTS:Bacterial contamination exceeded thresholds at all sites. Both disinfection methods significantly decreased contamination. Manual wiping reduced bacterial counts below thresholds and eradicated fungal growth, while fumigation was effective for bacterial but not fungal contamination. Fumigation also failed to meet CDC cleanliness standards in hard-to-reach areas. CONCLUSIONS:Both manual wiping and fumigation effectively reduced bacterial contamination, however, wiping showed better results in fungal eradication. Improvements to fumigation methods are necessary, such as application of higher disinfectant concentrations or alternative chemicals. The aforementioned findings not on

关键词： Autonomous Mobile Robots Bacterial contamination Decontamination Disinfection Emergency Department Fungal contamination Hospital logistics Intensive care unit Microbiological cleanliness robotics

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Occupational heat strain in outdoor workers: A comprehensive review and meta-analysis

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Temperature 2022年第1期9卷 67-102页

作者： Ioannou, Leonidas G. Foster, Josh Morris, Nathan B. Piil, Jacob F. Havenith, George Mekjavic, Igor B. Kenny, Glen P. Nybo, Lars Flouris, Andreas D. FAME Laboratory Department of Physical Education and Sport Science University of Thessaly Trikala Greece Institute for Exercise and Environmental Medicine Texas Health Presbyterian Hospital Dallas and University of Texas Southwestern Medical Center Dallas TX United States Department of Human Physiology & Nutrition University of Colorado Springs CO United States Department of Nutrition Exercise and Sports August Krogh Building University of Copenhagen Copenhagen Denmark Environmental Ergonomics Research Centre Loughborough Design School Loughborough University Loughborough United Kingdom Department of Automation Biocybernetics and Robotics Jozef Stefan Institute Ljubljana Slovenia Human and Environmental Physiology Research Unit School of Human Kinetics University of Ottawa Ottawa ON Canada

The present comprehensive review (i) summarizes the current knowledge on the impacts of occupational heat stress on outdoor workers, (ii) provides a historical background on this issue, (iii) presents a meta-analysis of published data, (iv) explores inter-individual and intra-individual factors, (v) discusses the available heat mitigation strategies, (vi) estimates physical work capacity, labour productivity, and metabolic rate for the year 2030, and (vii) provides an overview of existing policy and legal frameworks on occupational heat exposure. Meta-analytic findings from 38 field studies that involved monitoring 2,409 outdoor workers across 41 jobs in 21 countries suggest that occupational heat stress increases the core (r = 0.44) and skin (r = 0.44) temperatures, as well as the heart rate (r = 0.38) and urine specific gravity (r = 0.13) of outdoor workers (all p < 0.05). Moreover, it diminishes the capacity of outdoor workers for manual labour (r = −0.82;p < 0.001) and is responsible for more than two thirds of the reduction in their metabolic rate. Importantly, our analysis shows that physical work capacity is projected to be highly affected by the ongoing anthropogenic global warming. Nevertheless, the metabolic rate and, therefore, labour productivity are projected to remain at levels higher than the workers’ physical work capacity, indicating that people will continue to work more intensely than they should to meet their financial obligations for food and shelter. In this respect, complementary measures targeting self-pacing, hydration, work-rest regimes, ventilated garments, and mechanization can be adopted to protect outdoor workers. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

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