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Vibration stimulation enhances robustness in teleoperation robot system with EEG and eye-tracking hybrid control

Frontiers in bioengineering and biotechnology 2025年 13卷 1591316页

作者： Wenbin Zhang Tianjie Wang Chaolong Qin Baoguo Xu Hexuan Hu Tong Wang Ying Shen The College of Computer Science and Software Engineering Hohai University Nanjing China. Department of Rehabilitation Medicine The First Affiliated Hospital of Nanjing Medical University Nanjing China. The State Key Laboratory of Digital Medical Engineering School of Instrument Science and Engineering Southeast University Nanjing China.

Introduction:The application of non-invasive brain-computer interfaces (BCIs) in robotic control is limited by insufficient signal quality and decoding capabilities. Enhancing the robustness of BCIs without increasing the cognitive load remains a major challenge in brain-control technology. Methods:This study presents a teleoperation robotic system based on hybrid control of electroencephalography (EEG) and eye movement signals, and utilizes vibration stimulation to assist motor imagery (MI) training and enhance control signals. A control experiment involving eight subjects was conducted to validate the enhancement effect of this tactile stimulation technique. Results:Experimental results showed that during the MI training phase, the addition of vibration stimulation improved the brain region activation response speed in the tactile group, enhanced the activation of the contralateral motor areas during imagery of non-dominant hand movements, and demonstrated better separability (p = 0.017). In the robotic motion control phase, eye movement-guided vibration stimulation effectively improved the accuracy of online decoding of MI and enhanced the robustness of the control system and success rate of the grasping task. Discussion:The vibration stimulation technique proposed in this study can effectively improve the training efficiency and online decoding rate of MI, helping users enhance their control efficiency while focusing on control tasks. This tactile enhancement technology has potential applications in robot-assisted elderly care, rehabilitation training, and other robotic control scenarios.

关键词： brain-computer interface eye tracking motor imagery teleoperation robot vibrotactile stimulation

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A quantitative pairwise comparison-based constraint handling technique for constrained optimization

arXiv

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arXiv 2023年

作者： Huang, Ting Zhang, Qiang Pedrycz, Witold Yang, Shanlin School of Management Hefei University of Technology Hefei Box 270 Anhui Hefei230009 China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei Box 270 Anhui Hefei230009 China Ministry of Education Engineering Research Center for Intelligent Decision-Making & Information System Technologies Anhui Hefei230009 China Department of Electrical & Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada

This study proposes a new constraint handling technique for assisting metaheuristic optimization algorithms to solve constrained optimization problems more effectively and efficiently. Given any two solutions of any constrained optimization problems, they are first mapped into a two-dimensional Cartesian coordinate system with their objective function value differences and constraint violation differences as the two axes. To the best of our knowledge, we are the first to deal with constraints by building such a Cartesian coordinate system. Then, the Cartesian coordinate system is divided into a series of grids by assigning ranks to different intervals of differences. In this way, a pairwise comparison criterion is derived with the use of the fused ranks, which achieves non-hierarchical comparison neither preferring objective function values nor constraint violations, resulting in more accurate evaluation compared with existing techniques. Moreover, an evaluation function that is equivalent to the pairwise comparison criterion is proposed, which further improves computational efficiency. The effectiveness and efficiency of the proposed constraint handling technique are verified on two well-known public datasets, that is, CEC 2006 and CEC 2017. The results demonstrate that metaheuristic optimization algorithms with using the proposed constraint handling technique can converge to a feasible optimal solution faster and more reliably. Experimental analysis on the parameters involved reveal guidance for their optimal *** Codes 90-08 (Primary) Copyright © 2023, The Authors. All rights reserved.

关键词： Constrained optimization

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Remote Sensing Plateau Forest Segmentation with Boundary Preserving Double Loss Function Collaborative Learning

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Journal of New Media 2022年第4期4卷 165-177页

作者： Ying Ma Jiaqi Zhang Pengyu Liu Zhihao Wei Lingfei Zhang Xiaowei Jia School of Physics and Electronic Information Engineering Qinghai Minzu UniversityXining810007China The Information Department Beijing University of TechnologyBeijing100124China Advanced Information Network Beijing Laboratory Beijing100124China Computational Intelligence and Intelligent Systems Beijing key Laboratory Beijing100124China Institute of Remote Sensing and Geographic Information System School of Earth and Space SciencesPeking UniversityBeijing100871China Department of Computer Science University of Pittsburgh15260USA

Plateau forest plays an important role in the high-altitude ecosystem,and contributes to the global carbon *** forest monitoring request in-suit data from field *** recent development of the remote sensing technic,large-scale satellite data become available for surface *** to the various information contained in the remote sensing data,obtain accurate plateau forest segmentation from the remote sensing imagery still remain *** developed deep learning(DL)models such as deep convolutional neural network(CNN)has been widely used in image processing tasks,and shows possibility for remote sensing ***,due to the unique characteristics and growing environment of the plateau forest,generate feature with high robustness needs to design structures with high *** at the problem that the existing deep learning segmentation methods are difficult to generate the accurate boundary of the plateau forest within the satellite imagery,we propose a method of using boundary feature maps for collaborative *** are three improvements in this ***,design a multi input model for plateau forest segmentation,including the boundary feature map as an additional input label to increase the amount of information at the ***,we apply a strong boundary search algorithm to obtain boundary value,and propose a boundary value loss ***,improve the Unet segmentation network and combine dense block to improve the feature reuse ability and reduces the image information loss of the model during *** then demonstrate the utility of our method by detecting plateau forest regions from ZY-3 satellite regarding to Sanjiangyuan nature *** experimental results show that the proposed method can utilize multiple feature information comprehensively which is beneficial to extracting information from boundary,and the detection accuracy is generally higher than several state-of-art algorit

关键词： Remote sensing forest segmentation boundary preserving double loss function

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Dynamic nitrogen vacancy magnetometry by single-shot optical streaking microscopy

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Photonics Research 2022年第9期10卷 2147-2156页

作者： MARK A.KEPPLER ZACHARY A.STEELMAN ZACHARY N.COKER MILOŠNESLÁDEK PHILIP R.HEMMER VLADISLAV V.YAKOVLEV JOEL N.BIXLER Department of Biomedical Engineering Texas A&M UniversityCollege StationTexas 77843USA SAIC JBSA Fort Sam HoustonTexas 78234USA National Research Council Research Associateship Program WashingtonDC 20001USA IMOMEC Division IMECB-3590 DiepenbeekBelgium Institute for Materials Research(IMO) Hasselt UniversityB-3590 DiepenbeekBelgium Czech Technical University in Prague 27201 KladnoCzech Republic Department of Electrical and Computer Engineering Texas A&M UniversityCollege StationTexas 77843USA Bioeffects Division Airman System DirectorateAir Force Research LaboratoryJBSA Fort Sam HoustonTexas 78234USA

Nitrogen vacancy diamonds have emerged as sensitive solid-state magnetic field sensors capable of producing diffraction limited and sub-diffraction field ***,for the first time,to our knowledge,we extend those measurements to high-speed imaging,which can be readily applied to analyze currents and magnetic field dynamics in circuits on a microscopic *** overcome detector acquisition rate limitations,we designed an optical streaking nitrogen vacancy microscope to acquire two-dimensional spatiotemporal *** demonstrate magnetic field wave imaging with micro-scale spatial extent and~400μs temporal *** validating this system,we detected magnetic fields down to 10μT for 40 Hz magnetic fields using single-shot imaging and captured the spatial transit of an electromagnetic needle at streak rates as high as 110μm/*** design has the capability to be readily extended to full 3D video acquisition by utilizing compressed sensing techniques and a potential for further improvement of spatial resolution,acquisition speed,and *** device opens opportunities to many potential applications where transient magnetic events can be isolated to a single spatial axis,such as acquiring spatially propagating action potentials for brain imaging and remotely interrogating integrated circuits.

关键词： vacancy utilizing overcome

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具有环形接收区域的微波无线能量传输发射天线口径场分布设计方法（英文）

引用

engineering 2023年第11期 63-74页

作者： Xun Li Baoyan Duan Yiqun Zhang Yongxin Guo Shaanxi Key Laboratory of Space Solar Power Station System Xidian University Department of Electrical and Computer Engineering National University of Singapore

This work presents an optimal design method of antenna aperture illumination for microwave power transmission with an annular collection area. The objective is to maximize the ratio of the power radiated on the annular collection area to the total transmitted power. By formulating the aperture amplitude distribution through a summation of a special set of series, the optimal design problem can be reduced to finding the maximum ratio of two real quadratic forms. Based on the theory of matrices, the solution to the formulated optimization problem is to determine the largest characteristic value and its associated characteristic vector. To meet security requirements, the peak radiation levels outside the receiving area are considered to be extra constraints. A hybrid grey wolf optimizer and Nelder–Mead simplex method is developed to deal with this constrained optimization problem. In order to demonstrate the effectiveness of the proposed method, numerical experiments on continuous apertures are conducted; then, discrete arrays of isotropic elements are employed to validate the correctness of the optimized results. Finally,patch arrays are adopted to further verify the validity of the proposed method.

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TomoSAR-ALISTA: Efficient TomoSAR imaging via deep unfolded network

TomoSAR-ALISTA: Efficient TomoSAR imaging via deep unfolded ...

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International Conference on Radar systems (RADAR 2022)

作者： M. Wang Z. Zhang Y. Wang S. Gao X. Qiu Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing 100190 People's Republic of China Key Laboratory of Intelligent Aerospace Big Data Application Technology Suzhou 215123 People's Republic of China Electrical and Computer Engineering Department George Mason University Fairfax VA 22030 USA

ISBN: (数字)9781839537776

Synthetic aperture radar (SAR) tomography (TomoSAR) has attracted remarkable interest for its ability in achieving threedimensional reconstruction along the elevation direction from multiple observations. In recent years, compressed sensing (CS) technique has been introduced into TomoSAR considering for its super-resolution ability with limited samples. Whereas, the CS-based methods suffer from several drawbacks, including weak noise resistance, high computational complexity and complex parameter fine-tuning. Among the different CS algorithms, iterative soft-thresholding algorithm (ISTA) is widely used as a robust reconstruction approach, however, the parameters in the ISTA are manually chosen, which usually requires a time-consuming fine-tuning process to achieve the best performance. Aiming at efficient TomoSAR imaging, a novel sparse unfolding network named analytic learned ISTA (ALISTA) is proposed towards the TomoSAR imaging problem in this paper, and the key parameters of ISTA are learned from training data via deep learning to avoid complex parameter fine-tuning and significantly relieves the training burden. In addition, experiments verify that it is feasible to use traditional CS algorithms as training labels, which provides a tangible supervised training method to achieve better 3D reconstruction performance even in the absence of labeled data in real applications.

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Modulation format identification in fiber communications using single dynamical node-based photonic reservoir computing

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Photonics Research 2021年第1期9卷 I0010-I0017页

作者： QIANG CAI YA GUO PU LI ADONIS BOGRIS KALAN SHORE YAMEI ZHANG YUNCAI WANG Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of EducationTaiyuan University of TechnologyTaiyuan 030024China School of Electronics and Information Northwestern Polytechnical UniversityXi'an 710072China School of Information Engineering Guangdong University of TechnologyGuangzhou 510006China Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai UniversityShanghai 200444China Department of Informatics and Computer Engineering University of West AtticaAthens 12243Greece School of Electronic Engineering Bangor UniversityWales LL571UTUK Key Laboratory of Radar Imaging and Microwave Photonics Ministry of EducationNanjing University of Aeronautics and AstronauticsNanjing 210016China

We present a simple approach based on photonic reservoir computing(P-RC)for modulation format identification(MFI)in optical fiber *** an optically injected semiconductor laser with self-delay feedback is trained with the representative features from the asynchronous amplitude histograms of modulation *** simulations are conducted for three widely used modulation formats(on–off keying,differential phase-shift keying,and quadrature amplitude modulation)for various transmission situations where the optical signal-to-noise ratio varies from 12 to 26 d B,the chromatic dispersion varies from-500 to 500 ps/nm,and the differential group delay varies from 0 to 20 *** these situations,final simulation results demonstrate that this technique can efficiently identify all those modulation formats with an accuracy of>95%after optimizing the control parameters of the P-RC layer such as the injection strength,feedback strength,bias current,and frequency *** proposed technique utilizes very simple devices and thus offers a resource-efficient alternative approach to MFI.

关键词： fiber tuning computing

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Tree-Structured Data Clustering-Driven Neural Network for Intra Prediction in Video Coding

arXiv

引用

arXiv 2021年

作者： Man, Hengyu Fan, Xiaopeng Xiong, Ruiqin Zhao, Debin The Department of Computer Science and Technology Harbin Institute of Technology Harbin150001 China Peng Cheng Laboratory Shenzhen518055 China The Institute of Digital Media School of Electronic Engineering and Computer Science Peking University Beijing100871 China

As a crucial part of video compression, intra prediction utilizes local information of images to eliminate the redundancy in spatial domain. In both the High Efficiency Video Coding (H.265/HEVC) and Versatile Video Coding (H.266/VVC), multiple directional prediction modes are employed to find the texture trend of each block and then the prediction is made based on reference samples in the selected direction. Recently, the intra prediction schemes based on neural networks have achieved great success. In these methods, the networks are trained and applied to intra prediction to assist the directional prediction modes. In this paper, we propose a novel tree-structured data clusteringdriven neural network (dubbed TreeNet) for intra prediction, which builds the networks and clusters the training data in a tree-structured manner. Specifically, in each network split and training process of TreeNet, every parent network on a leaf node is split into two child networks by adding or subtracting Gaussian random noise. Then a data clustering-driven training is applied to train the two derived child networks using the clustered training data of their parent. To test the performance, TreeNet is integrated into VVC and HEVC to combine with or replace the directional prediction modes. In addition, a fast termination strategy is proposed to accelerate the search of TreeNet. The experimental results demonstrate that TreeNet with the fast termination can reach an average of 2.8% Bjøntegaard distortion rate (BD-rate) improvement (up to 8.1%) and 4.9% BD-rate improvement (up to 8.2%) over VVC (VTM-4.0) and HEVC (HM-16.9) with all intra configuration, respectively. Copyright © 2021, The Authors. All rights reserved.

关键词： Textures

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A deep learning approach to concrete water-cement ratio prediction

Results in Materials

引用

Results in Materials 2022年 15卷

作者： Bello, Sururah Apinke Oyedele, Lukumon Olaitan, Olakunle Kazeem Olonade, Kolawole Adisa Olajumoke, Akinropo Musiliu Ajayi, Anuoluwapo Akanbi, Lukman Akinade, Olugbenga Sanni, Mistura Laide Bello, Abdul-Lateef Big Data Enterprise and Artificial Intelligence Laboratory (Big-DEAL) Bristol Business School University of the West of England Bristol United Kingdom Department of Computer Science and Engineering Obafemi Awolowo University Ile-Ife Nigeria Department of Civil Engineering University of Lagos Akoka Nigeria Department of Civil Engineering Obafemi Awolowo University Ile-Ife Nigeria Faculty of Environment and Technology University of the West of England Bristol United Kingdom Department of Computing and Games School of Computing Engineering and Digital Technologies Teeside University Middlesbrough United Kingdom

Concrete is a versatile construction material, but the water content can greatly influence its quality. However, using the trials and error method to determine the optimum water for the concrete mix results in poor quality concrete structures, which often end up in landfills as construction wastes, thus threatening environmental safety. This paper develops deep neural networks to predict the required water for a normal concrete mix. Standard data samples obtained from certified/leading laboratories were fed into a deep learning model (multilayers feedforward neural network) to automate the calibration of mixing power of the concrete water content for improved water control accuracy. We randomly split the data into 70%, 15% and 15%, respectively, to train, validate and test the model. The developed DNN model was subjected to relevant statistical metrics and benchmarked against the random forest, gradient boosting machines, and support vector machines. The performance indices obtained by the DNN model have the highest reliability compared to other models for concrete water prediction. © 2022 The Authors

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Tunable and adjustable broadband RF photonic fractional Hilbert transformer based on a Kerr soliton crystal optical microcomb

Research Square

引用

Research Square 2021年

作者： Tan, Mengxi Xu, Xingyuan Moss, David J. The Optical Sciences Centre Swinburne University of Technology HawthornVIC3122 Australia The Electro-Photonics Laboratory Department of Electrical and Computer System Engineering Monash University ClaytonVIC3800 Australia

We demonstrate an RF photonic fractional Hilbert transformer based on an integrated Kerr microcomb source featuring a record low free spectral range of 49 GHz. By programming and shaping the comb lines according to calculated tap weights for up to 39 wavelengths across the C-band, we achieve tunable bandwidths ranging from 1.2 to 15.3 GHz as well as variable center frequencies from baseband to 9.5 GHz, for both standard integral and arbitrary fractional orders. We experimentally characterize the RF amplitude and phase response of the tunable bandpass and lowpass Hilbert transformers with 90 and 45-degree phase shifts. The experimental results show good agreement with theory, confirming the effectiveness of our approach as a powerful way to implement standard and fractional order Hilbert transformers with broad and variable bandwidths and center frequencies, with high reconfigurability and greatly reduced size and complexity. © 2021, CC BY.

关键词： Optical signal processing

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