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3rd IEEE RAS and EMBS International Conference on Biomedical robotics and Biomechatronics

作者： Lister, Kevin Gao, Zhan Desai, Jaydev P. Robotics Automation and Medical Systems (RAMS) Laboratory Maryland Robotics Center University of Maryland College Park MD United States

ISBN: (纸本)9781424477098

Advancements in real-time surgical simulation techniques have provided the ability to utilize more complex nonlinear constitutive models for biological tissues which result in increased haptic and graphic accuracy. When developing such a model, verification is necessary to determine the accuracy of the force response as well as the magnitude of tissue deformation for tool-tissue interactions. In this study, we have constructed an experimental setup that provides the ability to obtain force-displacement information as well as surface deformation of porcine liver for in-vivo probing tasks. In addition, the system is capable of accurately determining the geometry of the liver specimen. These combined attributes provide the context required to simulate the experiment with accurate boundary conditions, whereby the only variable in the analysis is the material properties of the liver specimen. During the simulation, effects of settling due to gravity have been taken into account by a technique which incorporates the proper internal stress conditions in the model without altering the geometry. Initially, a model developed from ex-vivo tension, compression and pure shear experimentation is run through the simulation to determine the efficacy of utilizing an ex-vivo model for simulation of in-vivo probing tasks on porcine liver. Subsequently, a method for improving upon the model was developed such that increased accuracy could be achieved for the force characteristics while maintaining a high correlation with the surface displacement data.

关键词： 3D porcine liver model biological tissues cellular biophysics compressibility compression force-displacement information liver physiological models shear deformation shear experimentation surface deformation tension tissue deformation

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Nanoscale imaging and mechanical analysis of viral infection on cells by atomic force microscopy

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生物化学与生物物理学报（英文版） 2020年第11期52卷 1289-1292页

作者： Bin Liu Dan Dang Yang Yang Peng Yu Mi Li State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China lnstitutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China School of Medical Devices Shenyang Pharmaceutical UniversityShenyang 110016China State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China lnstitutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China lnstitutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China lnstitutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China

Investigating the mechanical cues involved in virus-cell interactions opens novel possibilities for understanding the underlying mech-anisms guiding viral infection,which will have great impacts on virology and human *** threat from viruses to human health is increasingly severe,and new deadly viruses are constantly dis-covered in the world,including severe acute respiratory syndrome-related coronavirus,severe acute respiratory syndrome coronavirus 2,Middle East respiratory syndrome-related coronavirus(MERS-CoV),Zika virus(ZIKV),Ebola virus,avian influenza virus,and so on[1-3],which pose unprecedented burden to human society.

关键词： microscopy atomic force virus diseases diagnostic imaging

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Towards a MRI-Compatible Meso-Scale SMA-Actuated Robot using PWM Control

Towards a MRI-Compatible Meso-Scale SMA-Actuated Robot using...

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3rd IEEE RAS and EMBS International Conference on Biomedical robotics and Biomechatronics

作者： Ho, Mingyen Desai, Jaydev P. Robotics Automation and Medical Systems (RAMS) Laboratory Maryland Robotics Center Institute for Systems Research at University of Maryland College Park 20742 USA

ISBN: (纸本)9781424477098

In this paper, we present our work towards the development of a SMA-actuated meso-scale robot for neurosurgery, which can be operated under MRI guidance. In this robot, we use two antagonistic SMA wires as actuators for each joint, so that each joint can be actuated independently. Due to the size scale of the robot, it is impossible to have individual position sensors at each joint and hence we rely primarily on temperature feedback to control the robot. We thus designed and developed an experimental setup to characterize the SMA wires. The goal of SMA characterization was to develop systematic experiments whereby the dependence of the joint motion on the temperature (and hence the SMA phase transition) can be experimentally determined. We also developed a theoretical model based on Tanaka's model and the geometry of the robot to characterize the joint motion with the change in SMA wire temperature. The results demonstrated that the SMA wire temperature can be used reliably to predict the joint motion of the robot. We then developed a Pulse Width Modulation (PWM) scheme to control the temperature of SMA wires (and hence the joint motion). By using PWM control and switching circuits, we can actuate multiple SMA wires simultaneously and independently using only one power supply. Experimental results from our current prototype of a 2-DOF robot show that we can actuate the SMA wires reliably and hence observe joint motion in a gelatin medium as well as in MRI.

关键词： MRI-compatible mesoscale SMA-actuated robot PWM Control Tanaka model actuators biocontrol biomedical MRI gelatin medium joint motion medical robotics mobile robots neurophysiology neurosurgery phase transition pulse width modulation pulse width modulation shape memory effect shape memory effects surgery switching circuits switching circuits

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Scalable Fabrication of Uniform Fast-Response Humidity Field Sensing Array for Respiration Recognition and Contactless Human-Machine Interaction

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Advanced Functional Materials 2025年

作者： Zhang, Zhicheng Li, Jianye Chen, Huizhi Wang, Hao Luo, Yibing Si, Ranzi Xie, Ruijie Tao, Kai Yang, Bo-Ru Zhang, Daohui Liu, Fei Huo, Fengwei Wu, Jin State Key Laboratory of Optoelectronic Materials and Technologies and the Guangdong Province Key Laboratory of Display Material and Technology School of Electronics and Information Technology Sun Yat-sen University Guangzhou510275 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Xiamen University Xiang'an Campus Xiang'an South Road Fujian Xiamen361102 China Dongguan Key Laboratory of Advanced Drug Delivery and Biosensing Research and Development School of Pharmacy and Dongguan Innovation Institute Guangdong Medical University Dongguan523808 China Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace School of Mechanical Engineering Northwestern Polytechnical University Xi'an710072 China State Key Laboratory of Transducer Technology Shanghai200050 China

In the wake of the COVID-19 pandemic, there is an increased demand for humidity sensors that can accurately detect targets without direct contact, driving advancements in contactless human-machine interaction (HMI) and non-invasive medical diagnostics. However, it is difficult for traditional individual sensors to accurately acquire humidity field information for reliable HMI. Here, an ionogel film-based flexible and fast-response humidity field sensing array is developed via a scalable, efficient, and modified spin-coating-based fabrication strategy for accurate detection of humidity distribution. By optimizing the structure and constitution of the hydrophobic ionogel films, the sensors display ultrafast response and recovery time (0.65/0.85 s), a broad detection range (11-98% RH), long-term stability (120 days), excellent repeatability, flexibility, and environmental tolerances. Thanks to the one-time scalable fabrication, the sensing units in the array exhibit superior uniformity, as the device-to-device deviation is reduced to one-ninth compared to traditional multi-batch fabrication methods. With the aid of machine learning algorithms, this humidity sensing array realizes not only the accurate identification of various subtle breath abnormalities (e.g., oral breathing, apnea, left and right nasal congestions) by conformally attaching to wearable masks, but also the precise contactless HMI applications (e.g., anti-interference gesture recognition and wireless control of intelligent executive terminals). © 2025 Wiley-VCH GmbH.

关键词： Humidity sensors

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Effect of Image Noise on the Classification of Skin Lesions Using Deep Convolutional Neural Networks

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Tsinghua Science and Technology 2020年第3期25卷 425-434页

作者： Xiaoyu Fan Muzhi Dai Chenxi Liu Fan Wu Xiangda Yan Ye Feng Yongqiang Feng Baiquan Su the Medical Robotics Laboratory School of AutomationBeijing University of Posts and TelecommunicationsBeijing 100876China. the Department of Laser Aesthetic Surgery Plastic Surgery HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100144China.

Skin lesions are in a category of disease that is both common in humans and a major cause of *** classification accuracy of skin lesions is a crucial determinant of the success rate of curing lethal *** Convolutional Neural Networks(CNNs)are now the most prevalent computer algorithms for the purpose of disease *** with all algorithms,CNNs are sensitive to noise from imaging devices,which often contaminates the quality of the images that are fed into *** this paper,a deep CNN(Inception-v3)is used to study the effect of image noise on the classification of skin *** noise,impulse noise,and noise made up of a compound of the two are added to an image dataset,namely the Dermofit Image Library from the University of ***,based on t-distributed Stochastic Neighbor Embedding(t-SNE)visualization,Receiver Operating Characteristic(ROC)analysis,and saliency maps,demonstrate the reliability of the Inception-v3 deep CNN in classifying noisy skin lesion images.

关键词： skin lesion deep convolutional neural network image noise

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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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Soft robotics:Morphology and Morphology-inspired Motion Strategy

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IEEE/CAA Journal of Automatica Sinica 2021年第9期8卷 1500-1522页

作者： Fan Xu Hesheng Wang Department of Automation Institute of Medical RoboticsKey Laboratory of System Control and Information Processing of Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong UniversityShanghai 200240China

robotics has aroused huge attention since the *** of the uniqueness that industrial applications exhibit,conventional rigid robots have displayed noticeable limitations,particularly in safe cooperation as well as with environmental ***,scientists have shifted their focus on soft robotics to apply this type of robots more effectively in unstructured *** decades,they have been committed to exploring sub-fields of soft robotics(e.g.,cutting-edge techniques in design and fabrication,accurate modeling,as well as advanced control algorithms).Although scientists have made many different efforts,they share the common goal of enhancing *** presented paper aims to brief the progress of soft robotic research for readers interested in this field,and clarify how an appropriate control algorithm can be produced for soft robots with specific *** paper,instead of enumerating existing modeling or control methods of a certain soft robot prototype,interprets for the relationship between morphology and morphology-dependent motion strategy,attempts to delve into the common issues in a particular class of soft robots,and elucidates a generic solution to enhance their performance.

关键词： Soft continuum manipulator soft gripper soft mobile robot soft robot control method soft robot modeling method soft robotics

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IntraROB-a programmable targeting device for interventional radiology

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International Congress Series 2005年 1281卷 407-411页

作者： Kronreif, Gernot Kettenbach, Joachim Fürst, Martin Kornfeld, Martin Ptacek, Wolfgang Vogele, Michael ARC Seibersdorf Research GmbH Mechatronic Automation Systems Robotics Laboratory Austria Department of Diagnostic Radiology Vienna Medical University Austria Medical Intelligence GmbH Germany

The appropriateness of robotic systems for interventional radiology could be successfully demonstrated by our previous prototype "B-RobI" as well as by other groups. Such robotic targeting devices can serve as the physician's "third hand" providing with a stable and accurate guidance of the medical tool-e.g. a biopsy needle-towards the lesion. For integration of such new technology into clinical practice, robotic systems must be further improved in terms of safety, reliability and easy handling. This paper describes a new design for a robotic targeting device, which is aimed to transfer the proofed concepts from our prototype "B-RobI" into a practical clinical setup. The paper outlines the system modules and a first in vitro study for US-guided biopsies using a needle penetrable phantom. © 2005 CARS and Elsevier B.V.

关键词： Computer-aided surgery Image-guided intervention Interventional radiology Localisation medical robotics

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Effects of temperature and cellular interactions on the mechanics and morphology of human cancer cells investigated by atomic force microscopy

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Science China(Life Sciences) 2015年第9期58卷 889-901页

作者： LI Mi LIU LianQing XI Ning WANG YueChao XIAO XiuBin ZHANG WeiJing State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences University of Chinese Academy of Sciences Department of Electrical and Computer Engineering Michigan State University Department of Lymphoma Affiliated Hospital of Military Medical Academy of Sciences

Cell mechanics plays an important role in cellular physiological activities. Recent studies have shown that cellular mechanical properties are novel biomarkers for indicating the cell states. In this article, temperature-controllable atomic force microscopy(AFM) was applied to quantitatively investigate the effects of temperature and cellular interactions on the mechanics and morphology of human cancer cells. First, AFM indenting experiments were performed on six types of human cells to investigate the changes of cellular Young's modulus at different temperatures and the results showed that the mechanical responses to the changes of temperature were variable for different types of cancer cells. Second, AFM imaging experiments were performed to observe the morphological changes in living cells at different temperatures and the results showed the significant changes of cell morphology caused by the alterations of temperature. Finally, by co-culturing human cancer cells with human immune cells, the mechanical and morphological changes in cancer cells were investigated. The results showed that the co-culture of cancer cells and immune cells could cause the distinct mechanical changes in cancer cells, but no significant morphological differences were observed. The experimental results improved our understanding of the effects of temperature and cellular interactions on the mechanics and morphology of cancer cells.

关键词： atomic force microscopy mechanics cancer cell temperature cellular interactions

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Domain-Invariant Similarity Activation Map Contrastive Learning for Retrieval-Based Long-Term Visual Localization

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IEEE/CAA Journal of Automatica Sinica 2022年第2期9卷 313-328页

作者： Hanjiang Hu Hesheng Wang Zhe Liu Weidong Chen Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China IEEE Department of Automation Institute of Medical RoboticsKey Laboratory of System Control and Information Processing of Ministry of EducationKey Laboratory of Marine Intelligent Equipment and System of Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China Department of Computer Science and Technology University of CambridgeCambridge CB30FDUnited Kingdom

Visual localization is a crucial component in the application of mobile robot and autonomous *** retrieval is an efficient and effective technique in image-based localization *** to the drastic variability of environmental conditions,e.g.,illumination changes,retrievalbased visual localization is severely affected and becomes a challenging *** this work,a general architecture is first formulated probabilistically to extract domain-invariant features through multi-domain image ***,a novel gradientweighted similarity activation mapping loss(Grad-SAM)is incorporated for finer localization with high *** also propose a new adaptive triplet loss to boost the contrastive learning of the embedding in a self-supervised *** final coarse-to-fine image retrieval pipeline is implemented as the sequential combination of models with and without Grad-SAM *** experiments have been conducted to validate the effectiveness of the proposed approach on the CMU-Seasons *** strong generalization ability of our approach is verified with the RobotCar dataset using models pre-trained on urban parts of the CMU-Seasons *** performance is on par with or even outperforms the state-of-the-art image-based localization baselines in medium or high precision,especially under challenging environments with illumination variance,vegetation,and night-time ***,real-site experiments have been conducted to validate the efficiency and effectiveness of the coarse-to-fine strategy for localization.

关键词： Deep representation learning place recognition visual localization

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