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Brain-X 2025年第1期3卷

作者： Bai, Long Chen, Shugeng Wang, Peng Chen, He Yan, Jiaqing Zhu, Xiaojian Song, Enming Tian, Bobo Su, Jiacan Li, Xiaoli Organoid Research Center Institute of Translational Medicine Shanghai University Shanghai China Department of Orthopedics Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai China National Center for Translational Medicine (Shanghai) SHU Branch Shanghai University Shanghai China Wenzhou Institute of Shanghai University Zhejiang Wenzhou China Department of Rehabilitation Medicine Huashan Hospital Fudan University Shanghai China Department of Language Literature and Communication Faculty of Humanities Vrije Universiteit Amsterdam Amsterdam Netherlands School of Automation Science and Engineering South China University of Technology Guangdong Guangzhou China Pazhou Laboratory Guangdong Guangzhou China School of Electrical and Control Engineering North China University of Technology Beijing China CAS Key Laboratory of Magnetic Materials and Devices and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Zhejiang Ningbo China Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and Perception Institute of Optoelectronics Fudan University Shanghai China Key Laboratory of Polar Materials and Devices Department of Electronics Ministry of Education East China Normal University Shanghai China

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EEG-Based Brain-Computer Interfaces Are Vulnerable to Backdoor Attacks

Research Square

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Research Square 2021年

作者： Meng, Lubin Huang, Jian Zeng, Zhigang Jiang, Xue Yu, Shan Jung, Tzyy-Ping Lin, Chin-Teng Chavarriaga, Ricardo Wu, Dongrui Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Brainnetome Center and National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China La Jolla CA United States Center for Advanced Neurological Engineering Institute of Engineering in Medicine UCSD La Jolla CA United States Centre of Artificial Intelligence Faculty of Engineering and Information Technology University of Technology Sydney Australia ZHAW DataLab Zürich University of Applied Sciences Winterthur8401 Switzerland

Research and development of electroencephalogram (EEG) based brain-computer interfaces (BCIs) have advanced rapidly, partly due to the wide adoption of sophisticated machine learning approaches for decoding the EEG signals. However, recent studies have shown that machine learning algorithms are vulnerable to adversarial attacks, e.g., the attacker can add tiny adversarial perturbations to a test sample to fool the model, or poison the training data to insert a secret backdoor. Previous research has shown that adversarial attacks are also possible for EEG-based BCIs. However, only adversarial perturbations have been considered, and the approaches are theoretically sound but very difficult to implement in practice. This article proposes to use narrow period pulse for poisoning attack of EEG-based BCIs, which is more feasible in practice and has never been considered before. One can create dangerous backdoors in the machine learning model by injecting poisoning samples into the training set. Test samples with the backdoor key will then be classified into the target class specified by the attacker. What most distinguishes our approach from previous ones is that the backdoor key does not need to be synchronized with the EEG trials, making it very easy to implement. The effectiveness and robustness of the backdoor attack approach is demonstrated, highlighting a critical security concern for EEG-based BCIs. © 2021, CC BY.

关键词： Electroencephalography

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An Early Stage Researcher's Primer on Systems Medicine Terminology

Network and Systems Medicine

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Network and Systems Medicine 2021年第1期4卷 2-50页

作者： Zanin, Massimiliano Aitya, Nadim A.A. Basilio, José Baumbach, Jan Benis, Arriel Behera, Chandan K. Bucholc, Magda Castiglione, Filippo Chouvarda, Ioanna Comte, Blandine Dao, Tien-Tuan Ding, Xuemei Pujos-Guillot, Estelle Filipovic, Nenad Finn, David P. Glass, David H. Harel, Nissim Iesmantas, Tomas Ivanoska, Ilinka Joshi, Alok Boudjeltia, Karim Zouaoui Kaoui, Badr Kaur, Daman Maguire, Liam P. McClean, Paula L. McCombe, Niamh De Miranda, João Luís Moisescu, Mihnea Alexandru Pappalardo, Francesco Polster, Annikka Prasad, Girijesh Rozman, Damjana Sacala, Ioan Sanchez-Bornot, Jose M. Schmid, Johannes A. Sharp, Trevor Solé-Casals, Jordi Spiwok, Vojtěch Spyrou, George M. Stalidzans, Egils Stres, Blaa Sustersic, Tijana Symeonidis, Ioannis Tieri, Paolo Todd, Stephen Van Steen, Kristel Veneva, Milena Wang, Da-Hui Wang, Haiying Wang, Hui Watterson, Steven Wong-Lin, Kongfatt Yang, Su Zou, Xin Schmidt, Harald H.H.W. Centro de Tecnología Biomédica Universidad Politécnica de Madrid Madrid Spain Intelligent Systems Research Centre School of Computing Engineering and Intelligent Systems Ulster University Ulster United Kingdom Center for Physiology and Pharmacology Institute of Vascular Biology and Thrombosis Research Medical University of Vienna Vienna Austria TUM School of Life Sciences Weihenstephan Technical University of Munich Freising Germany Holon Israel CNR National Research Council IAC Institute for Applied Computing Rome Italy Lab of Computing Medical Informatics and Biomedical Imaging Technologies School of Medicine Aristotle University of Thessaloniki Thessaloniki Greece Université Clermont Auvergne INRAE UNH Plateforme d'Exploration du Métabolisme MetaboHUB Clermont Clermont-Ferrand France Université de Technologie de Compiègne Compiègne France Labex MS2T Control of Technological Systems-of-Systems CNRS and Université de Technologie de Compiègne Compiègne France Faculty of Engineering University of Kragujevac Kragujevac Serbia Kragujevac Serbia Steinbeis Advanced Risk Technologies Institute Doo Kragujevac Kragujevac Serbia Pharmacology and Therapeutics School of Medicine Galway Neuroscience Centre National University of Ireland Galway Ireland School of Computing Ulster University Ulster United Kingdom Holon Israel Department of Mathematics and Natural Sciences Kaunas University of Technology Kaunas Lithuania Faculty of Computer Science and Engineering Ss. Cyril and Methodius University Skopje Macedonia Medicine Faculty Université Libre de Bruxelles CHU de Charleroi Charleroi Belgium Northern Ireland Centre for Stratified Medicine Biomedical Sciences Research Institute Ulster University Ulster United Kingdom Escola Superior de Tecnologia e Gestão Instituto Politécnico de Portalegre Portalegre Portugal Instituto Superior Técnico Universidade de Lisboa Lisboa Portugal Faculty of Automatic Control and Computers University Politehnica of B

Background: Systems Medicine is a novel approach to medicine, that is, an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral different fields, including medicine, biology, statistics, modeling and simulation, and data science. Such heterogeneity leads to semantic issues, which may slow down implementation and fruitful interaction between these highly diverse fields. Methods: In this review, we collect and explain more than100 terms related to Systems Medicine. These include both modeling and data science terms and basic systems medicine terms, along with some synthetic definitions, examples of applications, and lists of relevant references. Results: This glossary aims at being a first aid kit for the Systems Medicine researcher facing an unfamiliar term, where he/she can get a first understanding of them, and, more importantly, examples and references for digging into the topic. © Massimiliano Zanin et al., 2021;Published by Mary Ann Liebert, Inc. 2021.

关键词： Semantics

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What Is Required to Prevent a Second Major Outbreak of SARS-CoV-2 upon Lifting Quarantine in Wuhan City,China

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The Innovation 2020年第1期1卷 152-157页

作者： Lei Zhang Mingwang Shen Xiaomeng Ma Shu Su Wenfeng Gong Jing Wang Yusha Tao Zhuoru Zou Rui Zhao Joseph T.F.Lau Wei Li Feng Liu Kai Ye Youfa Wang Guihua Zhuang Christopher K.Fairley China-Australia Joint Research Center for Infectious Diseases School of Public HealthXi’an Jiaotong University Health Science CenterXi’anShaanxi 710061PR China Melbourne Sexual Health Centre Alfred HealthMelbourneAustralia Central Clinical School Faculty of MedicineNursing and Health SciencesMonash UniversityMelbourneVICAustralia Department of Epidemiology and Biostatistics College of Public HealthZhengzhou UniversityZhengzhou 450001 HenanChina Institute of Health Policy Management and Evaluation University of TorontoTorontoONCanada School of Public Health and Preventive Medicine Faculty of MedicineMonash UniversityMelbourneAustralia Centre for Research Behaviors Centre for Health Behaviours ResearchSchool of Public Health and Primary CareThe Chinese University of Hong KongHong KongHong Kong Bill and Melinda Gates Foundation SeattleWAUSA Department of Epidemiology and Health Statistics School of Public HealthSoutheast UniversityNanjing210009 JiangsuChina Shaanxi Provincial Center for Disease Control and Prevention Xi’an710054 ShaanxiChina MOE Key Lab for Intelligent Networks&Networks Security Faculty of Electronics and Information EngineeringXi’an Jiaotong UniversityXi’an 710049 China School of Automation Science and Engineering Faculty of Electronics and Information EngineeringXi’an Jiaotong UniversityXi’an 710049 China Genome Institute the First Affiliated Hospital of Xi’an Jiaotong UniversityXi’an 710061 China The School of Life Science and Technology Xi’an Jiaotong UniversityXi’an 710049 China Global Health Institute Department of Epidemiology and BiostatisticsSchool of Public HealthXi’an Jiaotong University Health Science CenterXi’anShaanxi 710061China

BACKGROUND The Chinese government implemented a metropolitan-wide quarantine of Wuhan city on 23rd January 2020 to curb the epidemic of the coronavirus *** of this quarantine is *** modelled the effects of two key hea... 详细信息

关键词： Wuhan break Major

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Progressive Inertial Poser: Progressive Real-Time Kinematic Chain Estimation for 3D Full-Body Pose from Three IMU Sensors

arXiv

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arXiv 2025年

作者： Zhu, Zunjie Zhao, Yan Hu, Yihan Wang, Guoxiang Qiu, Hai Zheng, Bolun Yan, Chenggang Xu, Feng School of Communication Engineering Hangzhou Dianzi University Hangzhou323000 China Key Laboratory of Micro-nano Sensing and IoT of Wenzhou Wenzhou Institute of Hangzhou Dianzi University Wenzhou325038 China School of Control Science and Engineering Tiangong University Tianjin300387 China College of Business Lishui University Lishui310018 China Costar Intelligent Optoelectronics Technology Co. Ltd China School of Automation Hangzhou Dianzi University Hangzhou323000 China Faculty of Applied Sciences Macao Polytechnic University 999078 China School of software and BNRist Tsinghua University Beijing100084 China

The motion capture system that supports full-body virtual representation is of key significance for virtual reality. Compared to vision-based systems, full-body pose estimation from sparse tracking signals is not limited by environmental conditions or recording range. However, previous works either face the challenge of wearing additional sensors on the pelvis and lower-body or rely on external visual sensors to obtain global positions of key joints. To improve the practicality of the technology for virtual reality applications, we estimate full-body poses using only inertial data obtained from three Inertial Measurement Unit (IMU) sensors worn on the head and wrists, thereby reducing the complexity of the hardware system. In this work, we propose a method called Progressive Inertial Poser (ProgIP) for human pose estimation, which combines neural network estimation with a human dynamics model, considers the hierarchical structure of the kinematic chain, and employs a multi-stage progressive network estimation with increased depth to reconstruct full-body motion in real time. The encoder combines Transformer Encoder and bidirectional LSTM (TE-biLSTM) to flexibly capture the temporal dependencies of the inertial sequence, while the decoder based on multi-layer perceptrons (MLPs) transforms high-dimensional features and accurately projects them onto Skinned Multi-Person Linear (SMPL) model parameters. Quantitative and qualitative experimental results on multiple public datasets show that our method outperforms state-of-the-art methods with the same inputs, and is comparable to recent works using six IMU sensors. Copyright © 2025, The Authors. All rights reserved.

关键词： Virtual reality

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Progressive Inertial Poser: Progressive Real-Time Kinematic Chain Estimation for 3D Full-Body Pose from Three IMU Sensors

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Zhu, Zunjie Zhao, Yan Hu, Yihan Wang, Guoxiang Qiu, Hai Zheng, Bolun Yan, Chenggang Xu, Feng Hangzhou Dianzi University School of Communication Engineering Hangzhou 323000 China Wenzhou Institute of Hangzhou Dianzi University Key Laboratory of Micro-nano Sensing and IoT of Wenzhou Wenzhou 325038 China Tiangong University School of Control Science and Engineering Tianjin 300387 China Lishui University College of Business Lishui 310018 China Costar Intelligent Optoelectronics Technology Co. Ltd China Hangzhou Dianzi University School of Automation Hangzhou 323000 China Macao Polytechnic University Faculty of Applied Sciences 999078 Macao Tsinghua University School of software and BNRist Beijing 100084 China

关键词： full-body virtual representation IMU sensors kinematic chain motion capture neural network progressive estimation virtual reality

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Finite-size scaling of geometric renormalization flows in complex networks

arXiv

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arXiv 2020年

作者： Chen, Dan Su, Housheng Wang, Xiaofan Pan, Gui-Jun Chen, Guanrong School of Artificial Intelligence and Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan430074 China Department of Automation Shanghai University Shanghai200072 China Faculty of Physics and Electronic Science Hubei University Wuhan430062 China Department of Electrical Engineering City University of Hong Kong Hong Kong Hong Kong

Recently, the concept of geometric renormalization group provides a good approach for studying the structural symmetry and functional invariance of complex networks. Along this line, we systematically investigate the finite-size scaling of structural and dynamical observables in geometric renormalization flows of synthetic and real evolutionary networks. Our results show that these observables can be well characterized by a certain scaling function. Specifically, we show that the critical exponent implied by the scaling function is independent of these observables but only depends on the small-world properties of the network, namely, all networks located in the small-world phase have a uniform scaling exponent, while those located in the non-small-world phase and in their critical regions have another uniform scaling. More importantly, we perform extensive experiments on real evolutionary networks with small-world characteristics, and our results show that these observables also have uniform scaling in their geometric renormalization flows. Therefore, in a sense this exponent can be used as an effective measure for classifying universal small-world and non-small-world network models. © 2020, CC BY-SA.

关键词： Geometry

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Development of the Insect-inspired Biomimetic Underwater Microrobot for a Father-son Robot System

Development of the Insect-inspired Biomimetic Underwater Mic...

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IEEE International Conference on Mechatronics and Automation

作者： Wenbo Sui Shuxiang Guo Liang Zheng Ruochen An Awa Tendeng Graduate School of Engineering Kagawa University Takamatsu Kagawa Japan Faculty of Engineering and Design Kagawa University Hayashi-cho Kagawa Japan Key Laboratory of Convergence Medical Engineering System and Healthcare Technology the Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology Beijing China Tianjin Key Laboratory for Control Theory and Application in Complicated Systems and Intelligent Robot Laboratory Tianjin University of Technology Tianjin China

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

In this paper, the lifting platform structure of the father robot and the development of the insect-inspired biomimetic underwater microrobot are presented. The objective is to decrease the load of microrobot and realize more functions. In previous researchers, the platform of the father robot is fixed, which is not conducive to adopt and release the son robot. The structure of the lifting platform can effectively solve the problem in theory. The insect-inspired microrobot used wood which has high hydrophilism. It causes the body of microrobot increased weight and short-term works. The fillable structure with waterproof character which is made by a 3D printer. The new structure also can be changed weight for achieving different functions underwater efficiently. Then, two kinds of communication between the light source and microrobot like chasing rotation and fixed distance chasing are described in order to prove the feasibility of the software. In all these cases, experimental results show the performance of the microrobot.

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A Method for Obtaining Contact Force between Catheter Tip and Vascular Wall in Master-slave Robotic System

A Method for Obtaining Contact Force between Catheter Tip an...

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IEEE International Conference on Mechatronics and Automation

作者： Xiaoliang Jin Shuxiang Guo Jian Guo Peng Shi Dapeng Song Faculty of Engineering and Design Kagawa University 2217-20 Hayashi-cho Takamatsu Kagawa Japan Key Laboratory of Convergence Medical Engineering System and Healthcare Technology the Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology Beijing China Tianjin Key Laboratory for Control Theory and Application in Complicated Systems and Intelligent Robot Laboratory Tianjin University of Technology Tianjin China

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

In the research of vascular interventional surgery robotic system, the force information acquisition of surgical tools (guidewires and catheters) has a significant affect on the safety of surgery, especially the contact force between the catheter tip and vascular wall. Therefore. In order to obtain this contact force, we noticed the pressure sensitive rubber because of its piezoresistive effect and easy processing into any shape. a force sensor based on the pressure sensitive rubber was developed in this paper. Once a force is applied on the force sensor attached to the catheter tip, the contact force can be approximated by the piezoresistive effect of the pressure sensitive rubber. The feasibility of the developed force sensor was verified by the experiments in “Vitro”. And the results showed that the force sensor was developed in this paper can accurately detect the contact force between the catheter tip and vascular wall at different positions in the vascular model, the extraction of contact force information of catheter tip is of great significance to the safety of surgery, and the application potential of pressure sensitive rubber.

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Super-resolution longitudinally polarized light needle achieved by tightly focusing radially polarized beams

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Optoelectronics Letters 2018年第1期14卷 1-5页

作者：史长坤聂仲泉田彦婷刘超赵永创贾宝华 Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province College of Physics and Optoelectronics Taiyuan University of Technology Centre for Micro-Photonics Faculty of Science Engineering and Technology Swinburne University of Technology

Based on the vector diffraction theory, a super-resolution longitudinally polarized optical needle with ultra-long depth of focus(DOF) is generated by tightly focusing a radially polarized beam that is modulated by a self-designed ternary hybrid(phase/amplitude) filter(THF). Both the phase and the amplitude patterns of THF are judiciously optimized by the versatile particle swarm optimization(PSO) searching algorithm. For the focusing configuration with a combination of a high numerical aperture(NA) and the optimized sine-shaped THFs, an optical needle with the full width at half maximum(FWHM) of 0.414λ and the DOF of 7.58λ is accessed, which corresponds to an aspect ratio of 18.3. The demonstrated longitudinally polarized super-resolution light needle with high aspect ratio opens up broad applications in high-density optical data storage, nano-photolithography, super-resolution imaging and high-efficiency particle trapping.

关键词： Super-resolution longitudinally polarized light needle achieved by tightly focusing radially polarized beams THF PSO

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