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Going below and beyond the surface: Microneedle structure, materials, drugs, fabrication, and applications for wound healing and tissue regeneration

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Bioactive Materials 2023年第9期27卷 303-326页

作者： Shang Lyu Zhifei Dong Xiaoxiao Xu Ho-Pan Bei Ho-Yin Yuen Chung-Wai James Cheung Man-Sang Wong Yong He Xin Zhao Department of Biomedical Engineering The Hong Kong Polytechnic UniversityHung HomHong Kong SARPR China Faculty of Science University of WaterlooWaterlooOntarioCanada State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical EngineeringZhejiang UniversityHangzhouPR China

Microneedle, as a novel drug delivery system, has attracted widespread attention due to its non-invasiveness, painless and simple administration, controllable drug delivery, and diverse cargo loading capacity. Although microneedles are initially designed to penetrate stratum corneum of skin for transdermal drug delivery, they, recently, have been used to promote wound healing and regeneration of diverse tissues and organs and the results are promising. Despite there are reviews about microneedles, few of them focus on wound healing and tissue regeneration. Here, we review the recent advances of microneedles in this field. We first give an overview of microneedle system in terms of its potential cargos (e.g., small molecules, macromolecules, nucleic acids, nanoparticles, extracellular vesicle, cells), structural designs (e.g., multidrug structures, adhesive structures), material selection, and drug release mechanisms. Then we briefly summarize different microneedle fabrication methods, including their advantages and limitations. We finally summarize the recent progress of microneedle-assisted wound healing and tissue regeneration (e.g., skin, cardiac, bone, tendon, ocular, vascular, oral, hair, spinal cord, and uterine tissues). We expect that our article would serve as a guideline for readers to design their microneedle systems according to different applications, including material selection, drug selection, and structure design, for achieving better healing and regeneration efficacy.

关键词： Microneedles Microfabrication Wound healing Tissue regeneration Drug delivery

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A deep learning-based model for automated STN localization using local field potentials in Parkinson’s disease

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Soft Computing 2025年第4期29卷 2343-2362页

作者： Hosny, Mohamed Naeem, Mohamed A. Zhu, Minwei Gao, Wenpeng Elshenhab, Ahmed M. Fu, Yili Department of Electrical Engineering Benha Faculty of Engineering Benha University Benha Egypt State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin150080 China Department of Mechatronics and Robotics Engineering Faculty of Engineering South Valley University Qena Egypt First Affiliated Hospital Harbin Medical University Harbin150001 China School of Life Science and Technology Harbin Institute of Technology Harbin150080 China Department of Mathematics Faculty of Science Mansoura University Mansoura35516 Egypt

Accurate identification of the subthalamic nucleus (STN) borders is time-consuming, relying heavily on the neurosurgeon expertise in manually interpreting the electrophysiological signals. Local field potentials (LFPs) have garnered imperative attention due to their strong correlation with the STN. However, existing detection models often face challenges with high computational complexity, hyperparameter optimization and lack of explainability, making them unreliable for clinicians. Therefore, this study introduces an explanatory framework using convolutional neural networks (CNN) for detecting the STN region from LFPs. Continuous wavelet transform is employed to convert LFPs signals into scalogram images, which are then processed by sixteen CNN models. We evaluated our framework by examining the impact of various limiting factors on the classification performance, including model size, learning rate (LR), optimizers and data scaling. Deep features are extracted from the top-performing CNN architectures to capture rich representations of the scalograms. These features are then fused and classified using k-nearest neighbour algorithm. Gradient-weighted class activation mapping is used to explain the decisions made by the proposed model. Our approach achieved an accuracy of 99.61%, outperforming individual CNN models for STN localization. The experimental results revealed that CNN models, embedded with additional hyperparameters and layers, generally outperformed smaller models. Besides, low LR significantly enhanced the performance compared to high LR. Moreover, features extracted from untuned networks produced lower performance than tuned networks. The proposed system could revolutionize deep brain stimulation surgery by increasing efficiency and reducing reliance on clinician expertise for STN detection. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Wavelet transforms

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A policy gradient algorithm integrating long and short-term rewards for soft continuum arm control

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Science China(Technological Sciences) 2022年第10期65卷 2409-2419页

作者： DONG Xiang ZHANG Jing CHENG Long XU WenJun SU Hang MEI Tao School of Electrical Engineering and Automation Anhui UniversityHefei 230601China State Key Laboratory for Control and Management of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Robotics Research Center Peng Cheng LaboratoryShenzhen 518055China

The soft continuum arm has extensive application in industrial production and human life due to its superior safety and flexibility. Reinforcement learning is a powerful technique for solving soft arm continuous control problems, which can learn an effective control policy with an unknown system model. However, it is often affected by the high sample complexity and requires huge amounts of data to train, which limits its effectiveness in soft arm control. An improved policy gradient method, policy gradient integrating long and short-term rewards denoted as PGLS, is proposed in this paper to overcome this issue. The shortterm rewards provide more dynamic-aware exploration directions for policy learning and improve the exploration efficiency of the algorithm. PGLS can be integrated into current policy gradient algorithms, such as deep deterministic policy gradient(DDPG). The overall control framework is realized and demonstrated in a dynamics simulation environment. Simulation results show that this approach can effectively control the soft arm to reach and track the targets. Compared with DDPG and other model-free reinforcement learning algorithms, the proposed PGLS algorithm has a great improvement in convergence speed and performance. In addition, a fluid-driven soft manipulator is designed and fabricated in this paper, which can verify the proposed PGLS algorithm in real experiments in the future.

关键词： soft arm control Cosserat rod deep reinforcement learning policy gradient algorithm high sample complexity

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Few-shot working condition recognition of a sucker-rod pumping system based on a 4-dimensional time-frequency signature and meta-learning convolutional shrinkage neural network

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Petroleum Science 2023年第2期20卷 1142-1154页

作者： Yun-Peng He Chuan-Zhi Zang Peng Zeng Ming-Xin Wang Qing-Wei Dong Guang-Xi Wan Xiao-Ting Dong State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyangLiaoning 110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyangLiaoning 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyangLiaoning 110169China University of Chinese Academy of Sciences Beijing100049China Shenyang University of Technology ShenyangLiaoning 110870China School of Automation and Electrical Engineering Shenyang Ligong UniversityShenyangLiaoning 110159China

The accurate and intelligent identification of the working conditions of a sucker-rod pumping system is necessary. As onshore oil extraction gradually enters its mid-to late-stage, the cost required to train a deep learning working condition recognition model for pumping wells by obtaining enough new working condition samples is expensive. For the few-shot problem and large calculation issues of new working conditions of oil wells, a working condition recognition method for pumping unit wells based on a 4-dimensional time-frequency signature (4D-TFS) and meta-learning convolutional shrinkage neural network (ML-CSNN) is proposed. First, the measured pumping unit well workup data are converted into 4D-TFS data, and the initial feature extraction task is performed while compressing the data. Subsequently, a convolutional shrinkage neural network (CSNN) with a specific structure that can ablate low-frequency features is designed to extract working conditions features. Finally, a meta-learning fine-tuning framework for learning the network parameters that are susceptible to task changes is merged into the CSNN to solve the few-shot issue. The results of the experiments demonstrate that the trained ML-CSNN has good recognition accuracy and generalization ability for few-shot working condition recognition. More specifically, in the case of lower computational complexity, only few-shot samples are needed to fine-tune the network parameters, and the model can be quickly adapted to new classes of well conditions.

关键词： Few-shot learning Indicator diagram Meta-learning Soft thresholding Sucker-rod pumping system Time–frequency signature Working condition recognition

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Robust Tracking for Electromagnetic-Actuated Microrobot Via Sliding Mode Control 49

Robust Tracking for Electromagnetic-Actuated Microrobot Via ...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Wu, Yihang Qu, Ziyao Chang, Xiaocong Hu, Zhijian Yang, Rongni Ma, Renjie Harbin Institute of Technology State Key Laboratory of Robotics and Systems Harbin China School of Electrical and Electronic Engineering Nanyang Technological University Singapore School of Control Science and Engineering Shandong University Jinan China

ISBN: (纸本)9798350331820

Microrobots can work in small, enclosed spaces and complete complex tasks. It has potential applications in the field of biomedical and life sciences. This paper focuses on investigating robust dynamic tracking for electromagnetic-actuated microrobot via sliding mode control. First, we generalize the planar motion to the case of spatial trajectory tracking and then establish the three-dimensional tracking error model of microrobot. Then, we deploy a novel sliding control strategy and ensure the stability of sliding mode dynamics, once the robotic state reaches the sliding surface and sustains there in the sequel. Finally, the numerical simulation is conducted, compared to the traditional proportion-integration-differentiation control strategy, to verify the effectiveness and advantages of our proposed control scheme. © 2023 IEEE.

关键词： Sliding mode control

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Multifunctional Flexible Humidity Sensor systems Towards Noncontact Wearable Electronics

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Nano-Micro Letters 2022年第9期14卷 187-220页

作者： Yuyao Lu Geng Yang Yajing Shen Huayong Yang Kaichen Xu State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical EngineeringZhejiang UniversityHangzhou 310027People’s Republic of China Department of Biomedical Engineering City University of Hong KongHong KongPeople’s Republic of China

In the past decade,the global industry and research attentions on intelligent skin-like electronics have boosted their applications in diverse fields including human healthcare,Internet of Things,human–machine interfaces,artificial intelligence and soft *** them,flexible humidity sensors play a vital role in noncontact measurements relying on the unique property of rapid response to humidity *** work presents an overview of recent advances in flexible humidity sensors using various active functional materials for contactless *** categories of humidity sensors are highlighted based on resistive,capacitive,impedance-type and voltage-type working ***,typical strategies including chemical doping,structural design and Joule heating are introduced to enhance the performance of humidity *** on the noncontact perception capability,human/plant healthcare management,human-machine interactions as well as integrated humidity sensor-based feedback systems are *** burgeoning innovations in this research field will benefit human society,especially during the COVID-19 epidemic,where cross-infection should be averted and contactless sensation is highly desired.

关键词： Flexible electronics Flexible humidity sensors Noncontact detection Healthcare monitoring Human-machine interactions COVID-19 epidemic

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Spatiotemporally controlled emergence of nanoparticle microvortices under electric field

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Aggregate 2024年第2期5卷 290-300页

作者： Qi Pan Xijian Lin Shiyuan Wei Jinghong Su Hansen Zhao Xiaojie Duan Guoqing Hu Yan He Department of Chemistry Key Laboratory of Bioorganic Phosphorus Chemistry and Chemical Biology(Ministry of Education)Tsinghua UniversityBeijingChina Department of Biomedical Engineering College of Future TechnologyPeking UniversityBeijingChina Academy for Advanced Interdisciplinary Studies Peking UniversityBeijingChina The State Key Laboratory of Nonlinear Mechanics Institute of MechanicsChinese Academy of SciencesBeijingChina School of Engineering Science University of Chinese Academy of SciencesBeijingChina Department of Engineering Mechanics State Key Laboratory of Fluid Power and Mechatronic SystemsZhejiang UniversityHangzhouChina

Controlled assembly of nanoparticles(NPs)has garnered much interest over the past two *** established techniques,new methods utilizing local short-range or large-scale long-range interactions remain to be explored to achieve diverse micro-and nanoscale ***,we report the controlled emergence of vortex-pair arrays within monodispersed gold nanorods by applying a direct current electric field across a pair of sawtooth *** employing in situ darkfield microscopy and particle collective analysis,we elucidate the mechanism behind the formation and stabilization of the NP vortices,attributing it to the combined effects of the electrode shape,high NP density,and high solution *** further explore the controllability of the vortex-pair arrays and obtain multiple complex vortice *** findings will facilitate the investigation of efficient and controlled dynamic assembly of NPs under external fields and help manufacture next-generation optoelectronic functional materials.

关键词： dynamic assembly electric field gold nanoparticles sawtooth electrodes vortex

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A New Noise-Tolerant Dual-Neural-Network Scheme for Robust Kinematic Control of Robotic Arms With Unknown Models

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IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1778-1791页

作者： Ning Tan Peng Yu Zhiyan Zhong Fenglei Ni IEEE the School of Computer Science and Engineering&Key Laboratory of Machine Intelligence and Advanced Computing Ministry of EducationSun Yat-sen UniversityGuangzhou 510006China the School of Automation Guangdong Polytechnic Normal UniversityGuangzhou 510665China the State Key Laboratory of Robotics and Systems Harbin Institute of Technology(HIT)Harbin 150080China

Taking advantage of their inherent dexterity,robotic arms are competent in completing many tasks *** a result of the modeling complexity and kinematic uncertainty of robotic arms,model-free control paradigm has been proposed and investigated ***,robust model-free control of robotic arms in the presence of noise interference remains a problem worth *** this paper,we first propose a new kind of zeroing neural network(ZNN),i.e.,integration-enhanced noise-tolerant ZNN(IENT-ZNN)with integration-enhanced noisetolerant ***,a unified dual IENT-ZNN scheme based on the proposed IENT-ZNN is presented for the kinematic control problem of both rigid-link and continuum robotic arms,which improves the performance of robotic arms with the disturbance of noise,without knowing the structural parameters of the robotic *** finite-time convergence and robustness of the proposed control scheme are proven by theoretical ***,simulation studies and experimental demonstrations verify that the proposed control scheme is feasible in the kinematic control of different robotic arms and can achieve better results in terms of accuracy and robustness.

关键词： Dual zeroing neural networks(ZNN) finite-time convergence model-free robot control robustness analysis

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A skin-integrated device for neck posture monitoring and correction

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Microsystems & Nanoengineering 2023年第6期9卷 221-234页

作者： Hu Luo Tianhao Jin Yu Zhang Bohao Tian Yuru Zhang Dangxiao Wang State Key Lab of Virtual Reality Technology and Systems and Bejing Advanced Innovation Center for Biomedical Engineering Beihang UniversityNo.37 Xueyuan RoadHaidian District100191 BejingChina School of General Engineering Beihang UniversityNo.37 Xueyuan RoadHaidian DistrictBejingChina Peng Cheng Laboratory Shenzhen 518055China

Cervical spondylosis is a common disease that is often caused by long-term abnormal cervical curvature due to activities such as reading books and using computers or *** paper explores building an untethered and skin-integrated device in an e-skin form factor to monitor and haptically correct neck *** proposed design features a multilayered structure that integrates all flexible electronic circuits and components into a compact skin space while being untethered and skin *** accelerometer in the e-skin attaches to the neck for posture sensing,while four vibration actuators closely touch the neck skin to provide localized vibrotactile stimuli that encode four-direction correction cues of neck flexion±αand lateral bending±β.To ensure the reliability of posture sensing and vibrotactile rendering during neck movement,it is necessary to prevent the e-skin device from shifting ***,a hollow structure-based method is implemented for stably attaching the e-skin to the neck *** validated the e-skin device's sensing precision,skin-conformal compliance,stickiness,stability and effectiveness during the motion of neck postures,including its discrimination of localized four-direction vibrotactile cues.A user study verified the device's performance for sensing and correcting different abnormal neck postures during activities such as using smartphones,reading books,and processing computer *** proposed e-skin device may create opportunities for more convenient cervical spondylosis prevention and rehabilitation.

关键词： correction rendering shifting

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Representation of Human Arm Dynamic Intents with An Electrical-Impedance-Tomography (EIT)-Driven Musculoskeletal Model for Human-Robot Interaction

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IEEE Transactions on robotics 2025年 41卷 3278-3296页

作者： Zheng, Enhao Liu, Xiaodong Xu, Chenfeng Zhou, Zhihao Wang, Qining State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Institute for Artificial Intelligence Peking University Beijing100871 China Faculty of Engineering School of Advanced Manufacturing and Robotics Peking University The Institute for Artificial Intelligence Beijing100871 China

Representing human arm dynamic intent is essential for efective human-robot interaction. Accurately and robustly decoding these intentions through mathematical modeling of neuromuscular processes poses signifcant challenges. This study introduces an EIT-driven musculoskeletal model which integrates an EIT sensing system with methods for muscle identifcation, parameter estimation, and musculoskeletal system modeling. Unlike existing muscle-signal techniques, EIT captures muscle activities from the anatomical cross-sectional plane, providing both activation dynamics and morphological features. We validated our method through multi-DoF wrist kinematics estimation under varying contraction intensities, arm endpoint stifness estimation, and robotic variable admittance control. Our approach achieves accuracy comparable to state-of-the-art methods while requiring fewer training samples and a more compact sensing system. The model incorporates physiological constraints, minimizing decoding errors and ensuring interaction safety. This method enables reliable intent decoding with practical training demands. Future work will enhance the EIT system for complex tasks. © 2025 IEEE. All rights reserved.

关键词： Muscle

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