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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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Free-form Grid Structure Form Finding based on Machine Learning and Multi-objective Optimisation

arXiv

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arXiv 2024年

作者： Meng, Yiping Sun, Yiming School of Computing Engineering & Digital Technologies Teesside University Tees Valley MiddlesbroughTS1 3BX United Kingdom Department of Automatic Control and System Engineering University of Sheffield United Kingdom

Free-form structural forms are widely used to design spatial structures for their irregular spatial morphology. Current free-form form-finding methods cannot adequately meet the material properties, structural requirements or construction conditions, which brings the deviation between the initial 3D geometric design model and the constructed free-form structure. Thus, the main focus of this paper is to improve the rationality of free-form morphology considering multiple objectives in line with the characteristics and constraints of material. In this paper, glued laminated timber is selected as a case. Firstly, machine learning is adopted based on the predictive capability. By selecting a free-form timber grid structure and following the principles of NURBS, the free-form structure is simplified into free-form curves. The transformer is selected to train and predict the curvatures of the curves considering the material characteristics. After predicting the curvatures, the curves are transformed into vectors consisting of control points, weights, and knot vectors. To ensure the constructability and robustness of the structure, minimising the mass of the structure, stress and strain energy are the optimisation objectives. Two parameters (weight and the z-coordinate of the control points) of the free-from morphology are extracted as the variables of the free-form morphology to conduct the optimisation. The evaluation algorithm was selected as the optimal tool due to its capability to optimise multiple parameters. While optimising the two variables, the mechanical performance evaluation indexes such as the maximum displacement in the z-direction are demonstrated in the 60th step. The optimisation results for structure mass, stress and strain energy after 60 steps show the tendency of oscillation convergence, which indicates the efficiency of the proposal multi-objective optimisation. © 2024, CC BY-NC-ND.

关键词： Morphology

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MoFiM: A morphable fish modeling method for underwater binocular vision system

MoFiM: A morphable fish modeling method for underwater binoc...

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作者： Yin, Jingfang Zhu, Dengming Shi, Min Li, Zhaoxin Duan, Ming Mi, Xiangyuan Wang, Zhaoqi Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Control and Computer Engineering North China Electric Power University Beijing China Institute of Hydrobiology Chinese Academy of Sciences Hubei Wuhan China

Fish morphology is an essential basis for fishery management, as it can reflect the growth status of fishes. Noncontact 3D reconstruction of underwater fish is a new way to obtain fish morphology. While it is difficult to reconstruct fish on account of the inadequate information caused by fish swimming and poor underwater imaging. This article introduces a morphable fish modeling method for the underwater binocular vision system. First, we define a fish representation based on selected landmarks. Then, we propose a chirality-supervision incorporated hourglass network to estimate fish orientation and fish 2D landmarks simultaneously, and calculate fish 3D landmarks by triangulation. Next, we propose a fish modeling method which is based on 3D landmarks and introduce the optimization procedure of fish modeling. Finally, we obtain the complete 3D fish model corresponding to the input images. To train our network and build a parametric model, we constructed an underwater vision dataset and fish instance dataset respectively. We conducted experiments with grass carp as an example, and the experimental results show that our method can achieve effective fish modeling and is useful for noncontact measurement of underwater fish. © 2022 John Wiley & Sons Ltd.

关键词： Morphology

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Cooperative Trajectory Tracking control of Multiple Mobile Robots Under Motor Voltage Losses

Cooperative Trajectory Tracking Control of Multiple Mobile R...

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control Conference (ANZCC), Australian and New Zealand

作者： Zhao-Qing Liu Xiaohua Ge Hao Xie Qing-Long Han Jinchuan Zheng Xian-Ming Zhang School of Science Computing and Engineering Technologies Swinburne University of Technology Melbourne VIC Australia Shanghai Aerospace Control Technology Institute Shanghai China School of Automation Science and Electrical Engineering Beihang University Beijing China

This paper deals with the cooperative trajectory tracking (CTT) control problem of multiple mobile robot (MR) systems subject to motor voltage losses. To account for the adverse effect induced by motor voltage loss, the dc-motor dynamics are first introduced in the multiple MR system (multi-MRS). Then, to guarantee the successful completion of CTT missions even in the presence of motor voltage loss, unknown dynamics, and external disturbances, a resilient adaptive CTT control design approach, including the design of a virtual kinematic control law, a virtual current control law as well as a voltage control law, is developed. In addition, a CTT error dynamics is derived for multi-MRSs by incorporating the simultaneous effects of motor voltage loss, unknown dynamics, and external disturbances. After that, a formal theoretical analysis of the stability for the derived CTT error dynamics is provided. At last, an experimental example study is provided to substantiate the efficacy of the developed resilient adaptive CTT control design approach.

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A Speech Cryptosystem Using the New Chaotic System with a Capsule-Shaped Equilibrium Curve

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Computers, Materials & Continua 2023年第6期75卷 5987-6006页

作者： Mohamad Afendee Mohamed Talal Bonny Aceng Sambas Sundarapandian Vaidyanathan Wafaa Al Nassan Sen Zhang Khaled Obaideen Mustafa Mamat Mohd Kamal Mohd Nawawi Faculty of Informatics and Computing Universiti Sultan Zainal AbidinMalaysia Department of Computer Engineering University of SharjahSharjah26666UAE Department of Mechanical Engineering Universitas Muhammadiyah TasikmalayaIndonesia Research and Development Centre Vel Tech UniversityAvadiChennaiIndia School of Artificial Intelligence and Automationand Key Laboratory of Image Processingand Intelligent Control of Education Ministry of ChinaHuazhong University of Scienceand TechnologyWuhan430074China Institute of Strategic Industrial Decision Modeling School of Quantitative SciencesUniversiti Utara Malaysia06010UUM SintokKedahMalaysia

In recent years,there are numerous studies on chaotic systems with special equilibrium curves having various shapes such as circle,butterfly,heart and *** paper describes a new 3-D chaotic dynamical system with a capsule-shaped equilibrium *** proposed chaotic system has two quadratic,two cubic and two quartic nonlinear *** is noted that the proposed chaotic system has a hidden attractor since it has an infinite number of equilibrium *** is also established that the proposed chaotic system exhibits multi-stability with two coexisting chaotic attractors for the same parameter values but differential initial states.A detailed bifurcation analysis with respect to variations in the system parameters is portrayed for the new chaotic system with capsule equilibrium *** have shown MATLAB plots to illustrate the capsule equilibrium curve,phase orbits of the new chaotic system,bifurcation diagrams and *** an engineering application,we have proposed a speech cryptosystem with a numerical algorithm,which is based on our novel 3-D chaotic system with a capsule-shaped equilibrium *** proposed speech cryptosystem follows its security evolution and implementation on Field Programmable Gate Array(FPGA)*** results show that the proposed encryption system utilizes 33%of the FPGA,while the maximum clock frequency is 178.28 MHz.

关键词： Chaos chaotic systems hidden attractors multi-stability bifurcation speech cryptosystem FPGA design

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SCC-YOLO: An Improved Object Detector for Assisting in Brain Tumor Diagnosis

arXiv

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arXiv 2025年

作者： Bai, Runci Xu, Guibao Shi, Yanze Institute of Cloud Computing and Big Data China Academy of Information and Communications Technology Beijing100080 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221000 China

Brain tumors can lead to neurological dysfunction, cognitive and psychological changes, increased intracranial pressure, and seizures, posing significant risks to health. The You Only Look Once (YOLO) series has shown superior accuracy in medical imaging object detection. This paper presents a novel SCC-YOLO architecture that integrates the SCConv module into YOLOv9. The SCConv module optimizes convolutional efficiency by reducing spatial and channel redundancy, enhancing image feature learning. We examine the effects of different attention mechanisms with YOLOv9 for brain tumor detection using the Br35H dataset and our custom dataset (Brain_Tumor_Dataset). Results indicate that SCC-YOLO improved mAP50 by 0.3% on the Br35H dataset and by 0.5% on our custom dataset compared to YOLOv9. SCC-YOLO achieves state-of-the-art performance in brain tumor detection. Copyright © 2025, The Authors. All rights reserved.

关键词： Health risks

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Multi-omics graph convolutional networks for digestive system tumour classification and early-late stage diagnosis

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CAAI Transactions on Intelligence Technology 2024年第6期9卷 1572-1586页

作者： Lin Zhou Zhengzhi Zhu Hongbo Gao Chunyu Wang Muhammad Attique Khan Mati Ullah Siffat Ullah Khan School of Information Science and Technology University of Science and Technology of ChinaHefeiAnhuiChina Anhui Engineering Research Center on Information Fusion and Control of Intelligent Robot WuhuAnhuiChina Department of Breast Center West District of The Affiliated Hospital of University of Science and Technology of ChinaDivision of Life Sciences and MedicineUniversity of Science and Technology of ChinaHefeiAnhuiChina Institute of Advanced Technology University of Science and Technology of ChinaHefeiAnhuiChina School of Electrical and Electronic Engineering Nanyang Technological UniversitySingaporeSingapore School of Biological and Environmental Engineering Chaohu UniversityChaohu Regional Collaborative Technology Service Center for Rural RevitalizationHefeiChina Department of Artificial Intelligence College of Computer Engineering and SciencePrince Mohammad Bin Fahd UniversityAl-KhobarSaudi Arabia School of Automation Northwestern Polytechnical UniversityXi'anShaanxiChina Institute of Engineering and Computing Science University of Science and Technology of BannuKPKBannuPakistan

The prevalence of digestive system tumours(DST)poses a significant challenge in the global crusade against *** neoplasms constitute 20%of all documented cancer diagnoses and contribute to 22.5%of cancer-related *** accurate diagnosis of DST is paramount for vigilant patient monitoring and the judicious selection of optimal *** this challenge,the authors introduce a novel methodology,denominated as the Multi-omics Graph Transformer Convolutional Network(MGTCN).This innovative approach aims to discern various DST tumour types and proficiently discern between early-late stage tumours,ensuring a high degree of *** MGTCN model incorporates the Graph Transformer Layer framework to meticulously transform the multi-omics adjacency matrix,thereby illuminating potential associations among diverse samples.A rigorous experimental evaluation was undertaken on the DST dataset from The Cancer Genome Atlas to scrutinise the efficacy of the MGTCN *** outcomes unequivocally underscore the efficiency and precision of MGTCN in diagnosing diverse DST tumour types and successfully discriminating between early-late stage DST *** source code for this groundbreaking study is readily accessible for download at https://***/bigone1/MGTCN.

关键词： digestive system tumors early-late stage multi-omics tumor types

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Adaptive global sliding mode control for multilateral teleoperation systems with varying-time delay

Adaptive global sliding mode control for multilateral teleop...

引用

International Conference on Sciences and Techniques of Automatic control and Computer engineering (STA)

作者： Asma Ounissi Neila Mezghani Ben Romdhane Mohamed Boukattaya Laboratory of sciences and technique of automatic control and computing (Lab-STA) National school of engineering of Sfax Sfax Tunisia Laboratory of sciences and technique of automatic control and computing (Lab-STA) Sfax Preparatory Engineering Institute Sfax Tunisia

ISBN: (纸本)9781665482622

In this paper, we suggest an adaptive control for a multilateral teleoperation system (MTS) with an unknown upper limit on the system uncertainty (SU) and varying-time delay (VTD). A novel adaptive global sliding mode (AGSMC) has been addressed, which guarantees the elimination of the reaching phase and forces the tracking error to reach the sliding surface (SS) from the beginning. Moreover, the adaptive tuning law has been addressed in order to deal with the undetermined upper limit of the SU. The convergence and stability analysis of the proposed methods is verified by the Lyapunov stability theory. The simulation is carried out on 1 master, 1 leader, and 3 followers teleoperation system is developed to show the effectiveness of the developed control.

关键词： Uncertainty Simulation Robustness Stability analysis Delays Tuning Sliding mode control

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Simplified control Strategies for Power Converters in a Grid-Connected Hybrid DC-AC Microgrid

Simplified Control Strategies for Power Converters in a Grid...

引用

Future Energy Solutions (FES), International Conference on

作者： Tiago Davi Curi Busarello Marcelo Godoy Simões Hannu Laaksonen Kimmo Kauhaniemi Department of Control Automation and Computing Engineering Federal University of Santa Catarina Blumenau Brazil School of Technology and Innovations University of Vaasa Vaasa Finland

Many typical converter control strategies used in microgrids are complex or require modifications in the power structure. The complexities are due coupling effects among controllers and time-delay caused in exchanging information in the system. This paper proposes simplified control strategies for power converters in a grid-connected hybrid DC-AC microgrid, aiming to ensure precise voltage and current regulation. The used controllers are proportional-resonant, integral-double-lead, proportional-integral and single integral controller. In this paper, the methodology for tuning each controller is carefully described in detail and recommendation for choosing their bandwidth is given. Then, the designed controllers are discretized through the Backward-Euler approximation. The power converters of the microgrid are an inverter, a Buck, a Boost and a bidirectional DC-DC. A case study is conducted through simulations with Matlab/Simulink. Results show that the controlled variables follow their reference signals with negligible steady-state error, proving the efficacy of the simplified control strategies and allowing an stable operation of the microgrid.

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Voting Classifier and Metaheuristic Optimization for Network Intrusion Detection

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Computers, Materials & Continua 2023年第2期74卷 3183-3198页

作者： Doaa Sami Khafaga Faten Khalid Karim Abdelaziz A.Abdelhamid El-Sayed M.El-kenawy Hend K.Alkahtani Nima Khodadadi Mohammed Hadwan Abdelhameed Ibrahim Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt The Department of Civil and Environmental Engineering Florida International UniversityMiamiFLUSA Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

Managing physical objects in the network’s periphery is made possible by the Internet of Things(IoT),revolutionizing human *** attacks and unauthorized access are possible with these IoT devices,which exchange data to enable remote *** attacks are often detected using intrusion detection methodologies,although these systems’effectiveness and accuracy are *** paper proposes a new voting classifier composed of an ensemble of machine learning models trained and optimized using metaheuristic *** employed metaheuristic optimizer is a new version of the whale optimization algorithm(WOA),which is guided by the dipper throated optimizer(DTO)to improve the exploration process of the traditionalWOA *** proposed voting classifier categorizes the network intrusions robustly and *** assess the proposed approach,a dataset created from IoT devices is employed to record the efficiency of the proposed algorithm for binary attack *** dataset records are balanced using the locality-sensitive hashing(LSH)and Synthetic Minority Oversampling Technique(SMOTE).The evaluation of the achieved results is performed in terms of statistical analysis and visual plots to prove the proposed approach’s effectiveness,stability,and *** achieved results confirmed the superiority of the proposed algorithm for the task of network intrusion detection.

关键词： Voting classifier whale optimization algorithm dipper throated optimization intrusion detection internet-of-things

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