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Hand medical monitoring system based on machine learning and optimal EMG feature set

Personal and Ubiquitous Computing 2023年第6期27卷 1991-2007页

作者： Yu, Mingchao Li, Gongfa Jiang, Du Jiang, Guozhang Tao, Bo Chen, Disi Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China Precision Manufacturing Research Institute Wuhan University of Science and Technology Wuhan430081 China Research Center of Biologic Manipulator and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430081 China 3D Printing and Intelligent Manufacturing Engineering Institute Wuhan University of Science and Technology Wuhan430081 China School of Computing University of Portsmouth PortsmouthPO1 3HE United Kingdom

Considering that serious hand function damage will greatly affect the daily life of patients, its recovery mainly depends on the regular inspection and manual training of medical staff, and medical monitoring based on bioelectric signals can largely replace manual re-examination as autonomous rehabilitation technology. So, for the rationality of feature selection and the diversity of classifier design in the gesture recognition process based on electromyography (EMG) signals, this paper proposes a hand medical monitoring system based on feature selection method of feature subset average recognition rate and optimal machine learning algorithm selection, which mainly depends on the prediction of hand movement. At the same time, since most experiments are conducted in different non-public proprietary databases, the comparison between various gesture recognition methods can only be analyzed to a certain extent. Therefore, this paper uses the DB1 dataset in the large publicly available NinaPro database and combines with presently well-known 11 time-domain (TD) features and 5 frequency domain (FD) features, then uses the support vector machine (SVM) classifier to comparative analysis total 136 feature combinations under various feature numbers. Under the premise of ensuring the overall recognition rate of electromyography gesture, this method will be able to reduce the number of features in feature set, according to the change of the average remove redundant features, and construct an optimal reduced EMG feature set. Finally, through the four common hand motion classifiers based on machine learning: SVM, back propagation neural network, linear discriminant analysis, and K-nearest neighbor, this paper tests and verifies the separability of the optimal reduced EMG feature set, and based on this, selects the optimal hand motion classifier to build the optimal hand motion recognition system, improve the hand medical monitoring system, and provide technical reference for the c

关键词： Discriminant analysis

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GCN-Transformer Autoencoder with Knowledge Distillation for Unsupervised Video Anomaly Detection

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Journal of Advanced Computational Intelligence and Intelligent Informatics 2025年第3期29卷 659-667页

作者： Yan, Mingchao Xiong, Yonghua She, Jinhua School of Automation China University of Geosciences No.388 Lumo Road Hongshan District Hubei Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems No.388 Lumo Road Hongshan District Hubei Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education No.388 Lumo Road Hongshan District Hubei Wuhan430074 China School of Engineering Tokyo University of Technology 1404-1 Katakura Hachioji Tokyo192-0982 Japan

Video anomaly detection is crucial in intelligent surveillance, yet the scarcity and diversity of abnormal events pose significant challenges for supervised methods. This paper presents an unsupervised framework that integrates graph attention networks (GATs) and Transformer architectures, combining masked autoencoders (MAEs) with self-distillation training. GATs are utilized to model spatial and inter-frame relationships, while Transformers capture long-range temporal dependencies, overcoming the limitations of traditional MAE and self-distillation approaches. The model employs a two-stage training process: first, a lightweight MAE combined with a GAT-Transformer fusion constructs a knowledge distillation module;second, the student autoencoder is optimized by integrating a graph convolutional autoencoder and a classification head to identify synthetic anomalies. We evaluate the proposed method on three representative datasets—ShanghaiTech Campus, UBnormal, and UCSD Ped2—and achieve promising results. © Fuji Technology Press Ltd.

关键词： Network coding

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MorNet: Asymmetric UNet-like Network with Morphological Opening and Closing for Image Segmentation 17th

MorNet: Asymmetric UNet-like Network with Morphological Open...

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17th International Conference on Intelligent Robotics and Applications, ICIRA 2024

作者： Li, Meng Yun, Juntong Jiang, Du Tao, Bo Li, Gongfa Liu, Rong Liu, Ying Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China Research Center for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430081 China Precision Manufacturing Research Institute Wuhan University of Science and Technology Wuhan430081 China School of Medicine Wuhan University of Science and Technology No. 1 Huangjia Lake University Town Wuhan430065 China School of Mechanical Engineering Hubei Engineering University Xiaogan432000 China

ISBN: (纸本)9789819607761

Image segmentation plays a crucial role in target recognition as it provides an essential prerequisite for identifying targets. However, UNet cannot acquire comprehensive information about the image, which limits its ability to effectively segment small and discrete objects. A new network structure, called MorNet, is proposed. It applies dilation and erosion operations in morphological opening and closing for connected and discrete region segmentation. MorNet effectively integrates global segmentation images, emphasizing small and discrete area segmentation and enhancing the segmentation of large continuous areas. This method enhances the understanding of the location of organs and diseased sites, enabling accurate segmentation. A side-out (SO) monitoring mechanism is introduced into the decoder to provide monitoring information for the original image and the predicted results. Compared with current UNet-like networks, our proposed method achieved the highest Dice scores (96.4635%, 94.0514%, 94.3444%) and PPV scores (94.2226%, 90.2361%, 91.5582%) for liver tumor, brain tumor, and liver segmentation tasks, respectively. The experimental results show that MorNet successfully combines the segmentation of connected and discrete regions. MorNet locates organs and lesions more accurately than current state-of-the-art medical image segmentation models. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Image segmentation

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Group consensus of multi-agent systems with additive noises

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Science China(Information Sciences) 2022年第10期65卷 242-255页

作者： Chuanjian LI Xiaofeng ZONG School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

This paper is concerned with group consensus of multi-agent systems(MASs) that consist of two groups in additive noise environments. First, a control protocol is proposed based on the state information of each agent's neighbors corrupted by additive noises. Second, some sufficient conditions and necessary conditions are obtained for the following two types of group consensus behaviors.(1) Pure group consensus:agents in both groups have the same behavior(weak consensus or strong consensus);(2) hybrid group consensus: agents in different groups achieve different consensus behaviors. It is revealed that the influence between the two groups should be attenuated such that the MASs can achieve group consensus in additive noise environments, i.e., the affected group must fight against the influence that comes from another ***, some simulation examples are given to illustrate the feasibility of the theoretical results.

关键词： group consensus multi-agent systems additive noises pure group consensus hybrid group consensus

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A Robot Coordinate measurement System Based on Pull Wire Sensor and Its Parameter Identification Method 12

A Robot Coordinate Measurement System Based on Pull Wire Sen...

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12th International Conference on CYBER Technology in Automation, control, and Intelligent Systems, CYBER 2022

作者： Gao, Shuang Ma, Kaiwei Gao, Yang Shen, Xin Yang, Mingxing Xu, Fengyu College of Automation and College of Artificial Intelligence Nanjing University of Posts and Telecommunications Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Jiangsu Nanjing China Anhui Province Key Laboratory of Special Heavy Load Robot Anhui Maanshan China College of Automation and College of Artificial Intelligence Nanjing University of Posts and Telecommunications Jiangsu Nanjing China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Aiming at the problems of large robot error and difficult coordinate detection, a robot coordinate measurement system and parameter identification method based on pull wire sensor are proposed. Firstly, a robot coordinate measurement system based on pull wire sensor is established. Secondly, Levenberg-Marquarelt algorithm is used to solve the kinematics parameters of the robot. Finally, the neural network of the whole connection layer is used to predict the optimal compensation amount for secondary compensation. In order to verify the above theory, the robot coordinate measurement system is built and verified on the five degree of freedom robot experimental platform. The results show that the robot coordinate measurement system can measure the robot coordinates quickly and accurately. The secondary compensation method controls the accuracy of the robot to about 2mm, and the optimal error is controlled within 0.012mm. The absolute positioning accuracy of the robot is effectively improved. © 2022 IEEE.

关键词： Robots

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Modified Deep Deterministic Policy Gradient Based Optimal Speed Tracking Strategy for PMSMs

Modified Deep Deterministic Policy Gradient Based Optimal Sp...

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Data Driven control and Learning Systems (DDCLS)

作者： Zhong-Xin Fan Lintao Tang Shihua Li Rongjie Liu School of Automation Southeast University Nanjing P. R. China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing P. R. China Department of Statistics Florida State University Tallahassee FL USA

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

Achieving optimal speed regulation for permanent magnet synchronous motors (PMSMs) remains a challenging task, particularly in selecting the most suitable controller to meet desired objectives. This paper considers the optimal speed tracking problem of PMSMs. We employ a reinforcement learning algorithm to obtain optimal controller with a linear form. The reinforcement learning approach incorporates a critic-actor network structure, which approximates the value function and optimal control, respectively. Specifically, a weight updating method for the critic network is introduced, where the update of the actor network is guided by the critic network. Through data collection and neural network training, dynamic acquisition of the optimal controller gain is achieved. In addition, a novel activation function is implemented in the network, leading to improved control performance concerning dataset size and reduced training time. At final, a real-world PMSM application is presented along with comparisons to demonstrate effectiveness. The desire idea of resulting optimal controllers is not only applicable to linear systems but also capable of approximating arbitrary nonlinear optimal controllers, thus offering practical engineering versatility.

关键词： Training Linear systems Learning systems Neural networks Optimal control Reinforcement learning Data collection

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Particle manipulation behind a turbid medium based on the intensity transmission matrix

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Photonics Research 2022年第10期10卷 2293-2301页

作者： KAIGE LIU HENGKANG ZHANG SHANSHAN DU ZEQI LIU BIN ZHANG XING FU QIANG LIU Key Laboratory of Photonics Control Technology Ministry of EducationTsinghua UniversityBeijing 100084China Department of Precision Instrument State Key Laboratory of Precision Measurement Technology and InstrumentsTsinghua UniversityBeijing 100084China Beijing Institute of Control Engineering Beijing 100190China Beijing Institute of Electronic System Engineering Beijing 100854China

Although optical tweezers can manipulate tiny particles,the distortion caused by the scattering medium restricts their ***-shaping techniques such as the transmission matrix(TM)method are powerful tools to achieve light focusing behind the scattering *** this paper,we propose a method to focus light through a scattering medium in a large area based on the intensity transmission matrix(ITM).Only relying on the intensity distribution,we can calculate the ITM with the number of measurements equal to that of the control *** of the diffraction limit,our method guarantees high energy usage of the light *** on this method,we have implemented particle manipulation with a high degree of freedom on single and multiple *** addition,the manipulation range is enlarged more than 20 times(compared to the memory effect)to 200μm.

关键词： scattering matrix intensity

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A Resonant Cavity Based on Capacitively Loaded Coaxial Structure for Overhauser Magnetic Sensors 2

A Resonant Cavity Based on Capacitively Loaded Coaxial Struc...

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2022 2nd International Conference on Advanced Materials and Mechatronics, ICAMM 2022

作者： Liu, Liping Dong, Haobin Luo, Wang Ge, Jian Liu, Huan School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advance Control and Intelligent Automation for Complex China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

The RF excitation coil is an important component of the Overhauser magnetic sensor, which determines whether the dynamic nucleation polarization of the free radical solution can be carried out smoothly. A capacitance-loaded resonant cavity structure is proposed as the RF excitation of the Overhauser magnetic sensor. The structure and equivalent circuit of the capacitance-loaded coaxial resonant cavity are analyzed and improved on the conventional structure, and the resonant frequency is verified to be consistent with the excitation frequency of the free radical solution by modeling and simulation using COMSOL software. The resonant cavity solid was fabricated, and the cavity was tested by using a vector network analyzer. The results show that the initial resonance point of the homemade resonant cavity is 60.55MHz, and the frequency point can be adjusted to 60.7MHz by adjusting the loading capacitor and tuning capacitor;the resonant cavity return loss S11 is about -19dB, and the quality factor Q value is about 506. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Capacitance

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Double STAR-RIS Enhanced Secure Wireless Communications

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IEEE Transactions on Wireless Communications 2025年

作者： Cai, Yujin Yu, Wenwu Nie, Xiaokai Cheng, Qiang Cui, Tiejun Southeast University School of Mathematics Jiangsu Nanjing211189 China Purple Mountain Laboratories Nanjing211111 China Southeast University School of Automation Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Southeast University Shenzhen Research Institute Shenzhen518057 China Southeast University State Key Laboratory of Millimeter Waves Nanjing210096 China

Simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) have recently been employed to enhance the secure transmission due to the ability to manipulate the full-space electromagnetic signals. Prior works mainly investigate the single STAR-RIS aided secure communication system, which does not reveal the potential of the cooperative inter-STAR-RIS link. In this paper, a double STAR-RIS enhanced secure communication network involving multiple legitimate users (LUs) and eavesdroppers (Eves) is proposed. For fairness, the minimum secrecy rate maximization problem is formulated by jointly optimizing the active beamforming and passive transmission and reflection (T&R) beamforming. To deal with the highly non-convex nonlinear optimization problem, an active and passive beamforming optimization algorithm is proposed by employing the alternating optimization method. Wherein, a low-complexity sequential constraint relaxation (SCR) based algorithm is designed to solve the passive T&R beamforming optimization problem. Simulation results demonstrate that the secure performance in the double STAR-RIS assisted system outperforms that in the single RIS/double RIS/single STAR-RIS aided network. Furthermore, the proposed algorithm significantly reduces computational time (i.e., resource allocation time) compared with the traditional SCR based beamforming optimization algorithm. © 2002-2012 IEEE.

关键词： Cooperative communication

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Stability and Bifurcation control of Fractional BAM Neural Networks with Diffusion and Time Delays 42

Stability and Bifurcation control of Fractional BAM Neural N...

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42nd Chinese control Conference, CCC 2023

作者： Liu, Feng Wang, Wei Cai, Gang Zhou, Feifan Wang, Hua O Yang, Xiuqin School of Automation China University of Geosciences Wuhan430074 China Engineering Research Center of Ministry of Education for Intelligent Technology of Earth Exploration China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Boston University Department of Mechanical Engineering BostonMA02215 United States School of Education Minzu University of China Beijing100081 China

ISBN: (纸本)9789887581543

Based on fractional calculus theory and reaction-diffusion equation theory, a fractional-order time-delay reaction-diffusion neural network with Neumann boundary conditions is investigated. By constructing the phase space basis based on the Laplace operator eigenvector, the system equation is linearized to obtain the characteristic equation. Then, the characteristic equation is analyzed, and the local stability of the system at the equilibrium point is discussed. And taking the time delay as the bifurcation parameter, the stability changes of the system at the equilibrium point and the generation conditions of the Hopf bifurcation are studied when the time delay changes. Moreover, a state feedback controller is designed to control the bifurcation of the system. Finally, the theoretical derivation is verified by numerical simulation. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Time delay

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