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Portable System and User Interface for ECG and EMG Acquisition, Conditioning, and Parameters Extraction

Procedia Computer Science 2025年 256卷 1216-1223页

作者： Luiz E. Luiz Wilson J. da Silva Salviano Soares Paulo Leitão João P. Teixeira Research Centre in Digitalization and Intelligent Robotics (CeDRI) Laboratório Associado para a Sustentabilidade e Tecnologia em Regiões de Montanha (SusTEC) Instituto Politécnico de Bragança 5300-253 Bragança Portugal Postgraduate Programme in Electrical Engineering and Industrial Informatics - CPGEI Federal Technological University of Paraná 80230-901 Curitíba Paraná Brazil Engineering Department School of Sciences and Technology University of Trás-os-Montes and Alto Douro (UTAD) Quinta de Prados 5000-801 Vila Real Portugal Institute of Electronics and Informatics Engineering of Aveiro (IEETA) University of Aveiro 3810-193 Aveiro Portugal Intelligent Systems Associate Laboratory (LASI) University of Aveiro 3810-193 Aveiro Portugal

Electrical signals from the human body are constantly the focus of research, searching for a better understanding of physiological events, discovering early signs of disease, and improving life quality. Developing devices that allow research beyond the usual requirements and allow easy adaptation regarding the system’s acquisition, conditioning, and processing parts could be a step toward better understanding some behaviours. Therefore, this work focused on designing a system that goes from the discrete components to a graphical interface, allowing user control of parameters to set the acquisition in a way that favours the specific signal of interest. The resulting system allows the user to change parameters regarding the analogue and digital filtering, sampling frequency and events detection, namely R-peaks, in the electrocardiogram, to estimate heart rate and its frequency fluctuation, and muscle contraction in electromyogram, to analyse contraction strength and muscle fatigue. The system also allows the data to be stored, aiming to generate datasets to further process the data in AI-based algorithms.

关键词： Graphical User Interface Biosignals Printed Circuit Board EMG processing ECG processing

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Observation of non-Hermitian topological disclination states and charge fractionalization

arXiv

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arXiv 2025年

作者： Li, Ruifeng Banerjee, Rimi Mandal, Subhaskar Li, Da Long, Yang Ma, Tianchi Liu, Jianwei Liu, Gui-Geng Chong, Yidong Zhang, Baile Li, Er-Ping College of Information Science & Electronic Engineering Zhejiang Key Laboratory of Intelligent Electromagnetic Control and Advanced Electronic Integration Zhejiang University Hangzhou310027 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Singapore Singapore Department of Physics Indian Institute of Technology Bombay Mumbai400076 India Centre for Disruptive Photonic Technologies Nanyang Technological University Singapore Singapore Research Center for Industries of The Future Westlake University Hangzhou310030 China Department of Electronic and Information Engineering School of Engineering Westlake University Hangzhou310030 China

There has been significant interest in exploring topological disclination states, which effectively probe the band topology of the host material beyond the conventional bulk-edge correspondence. While most studies in this area have primarily focused on Hermitian systems, recent theoretical work predicts that non-Hermiticity can drive topological phase transitions and host topological disclination states associated with fractional charge. However, no experimental observations have been reported to date. Here, we report the first experimental observation of topological disclination states in electric circuits, induced solely by gain and loss. Through admittance matrix measurements and eigenstate analysis, we confirm their emergence and compute the corresponding fractional charge. Moreover, the disclination mode profile and localization effect can be directly visualized via monochromatic field excitation. Additionally, we demonstrate the emergence of degenerate zero-energy topological disclination states, devoid of fractional charge, in distinct non-Hermitian geometries. Our findings open the possibility of non-Hermiticity-induced fractional charges in two-dimensional non-Hermitian lattices, which may pave the way for advancements in active topological photonic devices. © 2025, CC BY.

关键词： Electric network topology

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Decentralized Optimization on Compact Submanifolds by Quantized Riemannian Gradient Tracking

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IEEE Transactions on Signal Processing 2025年

作者： Chen, Jun Liu, Lina Zhu, Tianyi Liu, Yong Dai, Guang Jiang, Yunliang Tsang, Ivor W. Zhejiang Normal University National Special Education Resource Center for Children with Autism Hangzhou311231 China Zhejiang Normal University School of Computer Science and Technology Jinhua321004 China China Mobile Research Institute Beijing100032 China Zhejiang University Institute of Cyber-Systems and Control Hangzhou310027 China State Grid Corporation of China SGIT AI Lab China Zhejiang Normal University Zhejiang Key Laboratory of Intelligent Education Technology and Application Jinhua321004 China Huzhou University School of Information Engineering Huzhou313000 China Centre for Frontier Artificial Intelligence Research A*STAR Singapore

This paper considers the problem of decentralized optimization on compact submanifolds, where a finite sum of smooth (possibly non-convex) local functions is minimized by n agents forming an undirected and connected graph. However, the efficiency of distributed optimization is often hindered by communication bottlenecks. To mitigate this, we propose the Quantized Riemannian Gradient Tracking (Q-RGT) algorithm, where agents update their local variables using quantized gradients. The introduction of quantization noise allows our algorithm to bypass the constraints of the accurate Riemannian projection operator (such as retraction), further improving iterative efficiency. To the best of our knowledge, this is the first algorithm to achieve an O(1/K) convergence rate in the presence of quantization, matching the convergence rate of methods without quantization. Additionally, we explicitly derive lower bounds on decentralized consensus associated with a function of quantization levels. Numerical experiments demonstrate that Q-RGT performs comparably to non-quantized methods while reducing communication bottlenecks and computational overhead. © 1991-2012 IEEE.

关键词： Iterative methods

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The Causal Effect of Personality Traits on the Mental Health in Breast Cancer Patients Under the Occurrence of Negative Life Events 18th

The Causal Effect of Personality Traits on the Mental Hea...

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18th EAI International Conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth 2024

作者： Petrakis, Aristeidis Mylona, Eugenia Kourou, Konstantina Manikis, Georgios Kondylakis, Haridimos Marias, Kostas Poikonen-Saksela, Paula Simos, Panagiotis Karademas, Evangelos Mazzocco, Ketti Pat-Horenczyk, Ruth Sousa, Berta Fotiadis, Dimitrios I. Computational Biomedicine Laboratory FORTH-ICS Heraklion Greece Unit of Medical Technology and Intelligent Information Systems Department of Materials Science and Engineering University of Ioannina Ioannina Greece Foundation for Research and Technology-Hellas Institute of Molecular Biology and Biotechnology Department of Biomedical Research Ioannina Greece Helsinki University Hospital Comprehensive Cancer Center and Helsinki University Helsinki Finland School of Medicine University of Crete Heraklion Greece Department of Psychology University of Crete Rethymno Greece Applied Research Division for Cognitive and Psychological Science European Institute of Oncology Milan Italy Department of Oncology and Hemato-oncology University of Milan Milan Italy School of Social Work and Social Welfare The Hebrew University of Jerusalem Jerusalem Israel Breast Unit Champalimaud Clinical Centre/Champalimaud Foundation Champalimaud Research Lisboa Portugal

ISBN: (纸本)9783031855719

Using longitudinal data from Portugal, Italy, Finland, and Israel, this article attempts to explore the causal relationship between mental health and the Big Five personality traits of breast cancer patients with the appearance of adverse life events. The main conclusion is that patients with high scores in the Big Five personality traits index enjoy better mental health status than patients with low scores in that index. In addition, there is a significant negative correlation between mental health deterioration and personality traits as an index and as individual traits. The negative impact on the mental health of cumulative adverse life events is significant and cannot be moderated by personality traits. Single negative life events have a positive correlation with mental health status deterioration, though not all of them are significant and only work-related problems can moderated significantly by high scores in the personality trait index. Moreover, the most important control variable are the state of exercise, which if it changes from active to not active causes a significant drop in the mental health score and cancer stage. Lastly, this causal relationship is validated by the prediction accuracy of AI/ML models. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering 2025.

关键词： Active learning

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Experimental evaluation of an advanced predictive control technique for variable-speed wind turbine systems

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International Journal of Electrical Power and Energy systems 2025年 168卷

作者： Echiheb, Farah Majout, Btissam Kafazi, Ismail EL Bossoufi, Badre Rabhi, Abdelhamid Bizon, Nicu Zhilenkov, Anton Mobayen, Saleh LIMAS Laboratory Faculty of Sciences Dhar El Mahraz Sidi Mohammed Ben Abdellah University Fez Morocco SMARTilab Laboratory Moroccan School of Engineering Sciences Rabat Morocco MIS Laboratory University of Picardie Jules Verne Amiens80000 France The National University of Science and Technology Politechnica Bucharest Pitești University Centre Pitesti110040 Romania Department of Cyber-Physical Systems St. Petersburg State Marine Technical University Saint-Petersburg190121 Russia of Intelligent Data Science National Yunlin University of Science and Technology Yunlin Douliou640301 Taiwan Energy Systems Research Center Khazar university Mahasti str. 41 BakuAZ1096 Azerbaijan

Wind energy control plays a crucial role in optimizing the performance of Doubly Fed Induction Generators (DFIGs) by maximizing power extraction while ensuring stable grid integration. To achieve this, a Maximum Power Point Tracking (MPPT) strategy is employed to determine the optimal mechanical speed and reference power, enabling efficient wind energy conversion. However, maintaining precise control over the active and reactive power exchange remains a challenge, especially under varying operating conditions. This paper presents an experimental study on the application of deadbeat predictive control to a DFIG-based wind energy system, integrating MPPT for optimal power tracking. The study, conducted using a DSPACE DS1104 test bench, includes the development of a comprehensive mathematical model, an analysis of the deadbeat control strategy, and its implementation in MATLAB/Simulink. Experimental validation demonstrates that the proposed control method achieves faster response time (0.0504 s), reduced Total Harmonic Distortion (THD) to 0.5 %, and enhanced robustness against parameter variations, ensuring both maximum power extraction and high-quality power injection into the grid. These results confirm the superiority of the MPPT-integrated deadbeat predictive control over conventional methods in terms of efficiency, power quality, and system stability. However, while this method shows promising results, its implementation in real-world, large-scale systems requires further investigation to address challenges such as grid stability under fluctuating conditions and the scalability of the control strategy. In terms of practical implications, the proposed control method offers potential for improving the performance and efficiency of DFIG-based wind energy systems, contributing to more sustainable and reliable energy production. The research also holds social implications by advancing renewable energy technologies, which are essential for reducing dependency on fossil

关键词： MATLAB

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Optimal Cooperative Secondary control for Islanded DC Microgrids via a Fully Actuated Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 405-417页

作者： Yi Yu Guo-Ping Liu Yi Huang Peng Shi IEEE Shenzhen Key Laboratory of Control Theory and Intelligent Systems Southern University of Science and TechnologyShenzhen 518055China School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China School of Electrical and Mechanical Engineering the University of AdelaideSA 5005Australia Research and Innovation Centre Obuda University1034 BudapestHungary

DC-DC converter-based multi-bus DC microgrids(MGs) in series have received much attention, where the conflict between voltage recovery and current balancing has been a hot topic. The lack of models that accurately portray the electrical characteristics of actual MGs while is controller design-friendly has kept the issue active. To this end, this paper establishes a large-signal model containing the comprehensive dynamical behavior of the DC MGs based on the theory of high-order fully actuated systems, and proposes distributed optimal control based on this. The proposed secondary control method can achieve the two goals of voltage recovery and current sharing for multi-bus DC MGs. Additionally, the simple structure of the proposed approach is similar to one based on droop control, which allows this control technique to be easily implemented in a variety of modern microgrids with different configurations. In contrast to existing studies, the process of controller design in this paper is closely tied to the actual dynamics of the MGs. It is a prominent feature that enables engineers to customize the performance metrics of the system. In addition, the analysis of the stability of the closed-loop DC microgrid system, as well as the optimality and consensus of current sharing are given. Finally, a scaled-down solar and battery-based microgrid prototype with maximum power point tracking controller is developed in the laboratory to experimentally test the efficacy of the proposed control method.

关键词： DC microgrids distributed control high-order fully actuated system approach linear quadratic regulator microgrid modeling secondary control

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Data-Driven Based Fault Prognosis for Industrial systems:A Concise Overview

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IEEE/CAA Journal of Automatica Sinica 2020年第2期7卷 330-345页

作者： Kai Zhong Min Han Bing Han Faculty of Electronic Information and Electrical Engineering Dalian University of TechnologyDalian 116024China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of TechnologyDalian 116024China State Key Laboratory of Navigation and Safety Technology Shanghai Ship and Shipping Research InstituteShanghai 200135China

Fault prognosis is mainly referred to the estimation of the operating time before a failure occurs,which is vital for ensuring the stability,safety and long lifetime of degrading industrial *** to the results of fault prognosis,the maintenance strategy for underlying industrial systems can realize the conversion from passive maintenance to active *** the increased complexity and the improved automation level of industrial systems,fault prognosis techniques have become more and more ***,the datadriven based prognosis approaches,which tend to find the hidden fault factors and determine the specific fault occurrence time of the system by analysing historical or real-time measurement data,gain great attention from different industrial *** this context,the major task of this paper is to present a systematic overview of data-driven fault prognosis for industrial ***,the characteristics of different prognosis methods are revealed with the data-based ones being ***,based on the different data characteristics that exist in industrial systems,the corresponding fault prognosis methodologies are illustrated,with emphasis on analyses and comparisons of different prognosis ***,we reveal the current research trends and look forward to the future challenges in this *** review is expected to serve as a tutorial and source of references for fault prognosis researchers.

关键词： Data-driven fault prognosis feature extraction industrial systems

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Environmental and health impacts of reduced PM2.5 and trace metals from ship emissions under low-sulfur fuel oil policy in Shanghai, China

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Environmental Pollution 2025年 377卷 126409页

作者： Dong, Xuyang Zhang, Yan Yu, Guangyuan Xiong, Yuqi Han, Zimin Huo, Juntao Huang, Cheng Kan, Haidong Zheng, Mei Ning, Zhi Xie, Bing National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary Department of Environmental Science and Engineering Fudan University Shanghai200438 China Shanghai200062 China MOE Laboratory for National Development and Intelligent Governance Shanghai Institute for Energy and Carbon Neutrality Strategy IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health Fudan University Shanghai200433 China Shanghai Institute of Pollution Control and Ecological Security Shanghai200092 China Shanghai200235 China School of Public Health Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment Shanghai Institute of Infectious Disease and Biosecurity Fudan University Shanghai200032 China Children's Hospital of Fudan University National Centre for Children's Health Shanghai China SKL-ESPC and SEPKL-AERM College of Environmental Sciences and Engineering and Centre for Environment and Health Peking University Beijing100871 China Division of Environment and Sustainability The Hong Kong University of Science and Technology Clear Water Bay Hong Kong Shanghai Engineering Research Center of Biotransformation of Organic Solid Waste School of Ecological and Environmental Sciences East China Normal University Shanghai200241 China

ship emissions can significantly exacerbate air pollution in coastal cities, threatening public health;however, a low-sulfur fuel oil policy, which restricts sulfur content in marine fuels, can effectively mitigate such pollution-driven challenges. This study employed a high-resolution ship emission inventory to assess the impacts of the fuel oil switch on air quality and public health in Shanghai from 2017 to 2021. Results showed a 37.3 % reduction in primary PM2.5 emissions from ships, with even steeper declines of 46.7 and 91.6 % in Ni and V emissions, respectively, leading to notable air quality improvements. Health assessments revealed a reduction in premature mortality attributable to long-term exposure to the contribution of ships to atmospheric PM2.5 concentrations, with deaths decreasing from 630 cases in 2017 to 481 in 2021. Similarly, short-term exposure-related deaths fell from 43 to 29. The port and waterfront areas experienced the most pronounced health benefits. The non-carcinogenic risks posed by trace metals (Ni and V), which were detected along the Huangpu River in 2017, dropped to 0.1 by 2021. Nonetheless, the carcinogenic risk from V persisted as a concern for adults in 2021. An analysis of ship-influenced episodes showed that population-weighted concentrations and short-term premature mortality decreased by over 50 % in densely populated areas and key ports. Despite the low population density in port areas such as Wusongkou and Waigaoqiao, the human health risks linked to ship emissions remained significant. This study demonstrates the effectiveness of low-sulfur fuel oil policy in reducing emissions and health risks, providing a scientific basis for refined pollution control strategies in port cities. © 2025 Elsevier Ltd

关键词： Air quality

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Finite-Time Synchronization of Flux-controlled Complex-Valued Memristive Neural Networks

Finite-Time Synchronization of Flux-Controlled Complex-Value...

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2023 International Conference on Neuromorphic Computing, ICNC 2023

作者： Wang, Yonghuan Wang, Leimin Wu, Genping 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 School of Automation Wuhan430074 China Wuhan Second Ship Design and Research Institute Wuhan430064 China

ISBN: (纸本)9798350316889

In this paper, by using the flux-controlled memristor model, the finite-time synchronization problem of delayed complex-valued memristive neural networks (MCNNs) is studied. Firstly, according to the proposed memristor model, we model the MCNNs as continuous systems on voltage-flux-time (wp, varpi, t) domain. Then, we design a class of approaches to realize state synchronization between the drive and response systems, and the corresponding synchronization conditions are achieved. Finally, the effectiveness of results is illustrated with the simulations. © 2023 IEEE.

关键词： Memristors

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A Reinforcement Learning Approach for Robust Restoration of Generators in Power System

A Reinforcement Learning Approach for Robust Restoration of ...

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2022 Chinese Automation Congress, CAC 2022

作者： Li, Huimiao Yang, Xiaozhou Zhai, Chao Hubei Key Laboratory of Advanced Control and Intelligent Automation Fo Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Future Resilient Systems Singapore-ETH Centre Create Campus Singapore

ISBN: (纸本)9781665465335

In the past decades, cascading blackouts have caused serious damages to power systems and affected the normal operation of society, so it is crucial to quickly restore the damaged power system to normal state. In this paper, a reinforcement learning (RL) approach is developed to achieve the robust restoration of generators in power systems. Firstly, the performance recovery of damaged power system is modeled as markov decision process, and constraints such as line voltage and active power output of generators are considered. Secondly, a RL algorithm is proposed to search the optimal control strategy for generator units recovery. Based on the proposed restoration approach, Q-learning algorithm is employed to obtain the optimal strategy for power supply of generaors in power grids. Finally, numerical simulations are carried out on IEEE 9-bus system under different scenarios of external disturbances and certainties. The simulation results demonstrate the effectiveness and feasibility of the proposed approach. © 2022 IEEE.

关键词： Reinforcement learning

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