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LDGCN: An Edge-End Lightweight Dual GCN Based on Single-Channel EEG for Driver Drowsiness Monitoring

IEEE Transactions on Consumer Electronics 2025年

作者： Huang, Jingwei Wang, Chuansheng Huang, Jiayan Fan, Haoyi Xue, Xingsi Zhang, Fuquan Fuzhou University College of Computer and Big Data Fuzhou China Polytechnic University of Catalonia Department of Automatic Control Barcelona Spain Putian University New Engineering Industry College Putian China Fujian University of Technology Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian Fuzhou350118 China Minjiang University Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Fuzhou China Minjiang University College of Computer and Control Engineering Fuzhou China Sichuan Conservatory of Music Digital Media Art Key Laboratory of Sichuan Province Chengdu China Minjiang University Fuzhou Technology Innovation Center of Intelligent Manufacturing information System Fuzhou China Fuzhou China

Driver drowsiness electroencephalogram (EEG) signal monitoring can promptly alert drivers of their drowsiness in edge-end Consumer Electronics (CE), thereby reducing the probability of traffic accidents. Graph convolutional networks (GCNs) have shown significant advancements in processing the non-stationary, time-varying, and non-Euclidean nature of EEG signals. However, the existing single-channel EEG adjacency graph construction process lacks interpretability, which hinders the ability of GCNs to effectively extract adjacency graph features, thus affecting the performance of drowsiness monitoring. To address this issue, we propose an edge-end Lightweight Dual Graph Convolutional Network (LDGCN). Specifically, we are the first to incorporate neurophysiological knowledge to design a Baseline Drowsiness Status Adjacency Graph (BDSAG), which characterizes driver drowsiness status. Additionally, to express more features within limited EEG data, we introduce the Augmented Graph-level Module (AGM). This module captures global and local information at the graph level, ensuring that BDSAG features remain intact while enhancing effective feature expression capability. To further enhance the application of CE, we apply Adaptive Pruning Optimization (APO) to the channels and neurons of LDGCN, which nearly halves the inference latency. Experiments on benchmark datasets demonstrate that LDGCN offers the best trade-off between monitoring performance and hardware resource utilization, outperforming existing state-of-the-art algorithms. © 1975-2011 IEEE.

关键词： Neurons

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LDGCN: An Edge-End Lightweight Dual GCN Based on Single-Channel EEG for Driver Drowsiness Monitoring

arXiv

引用

arXiv 2024年

作者： Huang, Jingwei Wang, Chuansheng Huang, Jiayan Fan, Haoyi Grau, Antoni Zhang, Fuquan The College of Computer and Big Data Fuzhou University Fuzhou China The Department of Automatic Control Polytechnic University of Catalonia Barcelona Spain The New Engineering Industry College Putian University Putian China School of Computer and Artificial Intelligence Zhengzhou University China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China College of Computer and Control Engineering Minjiang University Fuzhou China Key Laboratory of Sichuan Province Sichuan Conservatory of Music Chengdu China Fuzhou Technology Innovation Center of Intelligent Manufacturing information System Minjiang University Fuzhou China Fujian Polytechnic Normal University Fujian Province University Fuzhou China

Driver drowsiness electroencephalography (EEG) signal monitoring can timely alert drivers of their drowsiness status, thereby reducing the probability of traffic accidents. Graph convolutional networks (GCNs) have shown significant advancements in processing the non-stationary, time-varying, and non-Euclidean nature of EEG signals. However, the existing single-channel EEG adjacency graph construction process lacks interpretability, which hinders the ability of GCNs to effectively extract adjacency graph features, thus affecting the performance of drowsiness monitoring. To address this issue, we propose an edge-end lightweight dual graph convolutional network (LDGCN). Specifically, we are the first to incorporate neurophysiological knowledge to design a Baseline Drowsiness Status Adjacency Graph (BDSAG), which characterizes driver drowsiness status. Additionally, to express more features within limited EEG data, we introduce the Augmented Graph-level Module (AGM). This module captures global and local information at the graph level, ensuring that BDSAG features remain intact while enhancing effective feature expression capability. Furthermore, to deploy our method on the fourth-generation Raspberry Pi, we utilize Adaptive Pruning Optimization (APO) on both channels and neurons, reducing inference latency by almost half. Experiments on benchmark datasets demonstrate that LDGCN offers the best trade-off between monitoring performance and hardware resource utilization compared to existing state-of-the-art algorithms. All our source code can be found at https://***/BryantDom/Driver-Drowsiness-Monitoring. Copyright © 2024, The Authors. All rights reserved.

关键词： Electroencephalography

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Study of photophysical properties of Cdq2 thin film

引用

Materials Today: Proceedings 2022年 66卷 202-204页

作者： Lougdali, M. El Kouari, Y. Anoua, R. Zazoui, M. El Oudghiri-Idrissi, I. Abboud, Y. Zawadzka, A. Sahraoui, B. Laboratory of Materials Energy and Control System Faculty of Sciences and Technology Hassan II University of Casablanca Mohammedia B.P 146 Morocco Department of Automatic and Measurement Faculty of Physics Astronomy and Informatics Nicolaus Copernicus University Torun Poland Laboratory of Engineering Sciences for Energy National School of Applied Sciences of El Jadida El Jadida BP 1166 Morocco Faculty of Sciences Ben M'sik University of Hassan II of Casablanca Casablanca Morocco Centre for Modern Interdisciplinary Technologies Nicolaus Copernicus University Wilenska 4 Torun 87-100 Poland MOLTECH-Anjou UMR 6200 CNRS UNIV Angers 2 bd Lavoisier Angers 49045 France

In this work, the morphological and optical properties of the cadmium (II) bis(8-hydroxyquinoline) (Cdq2) thin film are presented. The film was elaborated by physical deposition technique. The Atomic Force Microscopy (AFM) image shows a homogenous surface. The transmittance was measured in the range of 300–1200 nm with UV–visible spectroscopy. The emission of the film was characterized via the photoluminescence spectroscopy, a strong luminescence has been found. The measurements done at low temperatures show a decrease of the intensity of luminescence in the temperature range of 77–300 K. © 2022

关键词： Thin films

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Model-Based and Data-Driven control of Event- and Self-Triggered Discrete-Time LTI systems

arXiv

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arXiv 2022年

作者： Wang, Xin Berberich, Julian Sun, Jian Wang, Gang Allgöwer, Frank Chen, Jie The Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing10081 China The Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China The University of Stuttgart Institute for Systems Theory and Automatic Control Stuttgart70550 Germany The Department of Control Science and Engineering Tongji University Shanghai201804 China The State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

The present paper considers the model-based and data-driven control of unknown linear time-invariant discretetime systems under event-triggering and self-triggering transmission schemes. To this end, we begin by presenting a dynamic event-triggering scheme (ETS) based on periodic sampling, and a discrete-time looped-functional approach, through which a model-based stability condition is derived. Combining the model-based condition with a recent data-based system representation, a data-driven stability criterion in the form of linear matrix inequalities (LMIs) is established, which also offers a way of co-designing the ETS matrix and the controller. To further alleviate the sampling burden of ETS due to its continuous/periodic detection, a self-triggering scheme (STS) is developed. Leveraging pre-collected input-state data, an algorithm for predicting the next transmission instant is given, while achieving system stability. Finally, numerical simulations showcase the efficacy of ETS and STS in reducing data transmissions as well as of the proposed co-design methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Linear matrix inequalities

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Asymptotic Theory for Regularized system Identification Part I: Empirical Bayes Hyper-parameter Estimator

arXiv

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arXiv 2022年

作者： Ju, Yue Mu, Biqiang Ljung, Lennart Chen, Tianshi The School of Data Science Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen518172 China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and System Science Chinese Academy of Sciences Beijing100190 China The Division of Automatic Control Department of Electrical Engineering Linköping University LinköpingSE-58183 Sweden

Regularized techniques, also named as kernel-based techniques, are the major advances in system identification in the last decade. Although many promising results have been achieved, their theoretical analysis is far from complete and there are still many key problems to be solved. One of them is the asymptotic theory, which is about convergence properties of the model estimators as the sample size goes to infinity. The existing related results for regularized system identification are about the almost sure convergence of various hyper-parameter estimators. A common problem of those results is that they do not contain information on the factors that affect the convergence properties of those hyper-parameter estimators, e.g., the regression matrix. In this paper, we tackle problems of this kind for the regularized finite impulse response model estimation with the empirical Bayes (EB) hyper-parameter estimator and filtered white noise input. In order to expose and find those factors, we study the convergence in distribution of the EB hyper-parameter estimator, and the asymptotic distribution of its corresponding model estimator. For illustration, we run Monte Carlo simulations to show the efficacy of our obtained theoretical results. Copyright © 2022, The Authors. All rights reserved.

关键词： Monte Carlo methods

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A preliminary analysis of gait performance of patients with multiple sclerosis using a sensorized crutch tip

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IFAC-PapersOnLine 2020年第2期53卷 16462-16467页

作者： Iñigo Sesar Asier Zubizarreta Itziar Cabanes Asier Brull Jon Torres-Unda Ana Rodriguez-Larrad Department of System Engineering and Automatic Control University of the Basque Country (UPV/EHU) Bilbao Spain Department of Physiology University of the Basque Country(UPV/EHU) Leioa Spain

The quality of life and functional mobility of patients with Multiple Sclerosis (MS) can significantly improve with exercise and a rehabilitation therapy adjusted to the needs of each patient. The assessment of gait and functional mobility of patients with MS is usually done based on clinical scales and tests, which have various limitations. This work presents the preliminary results of a clinical study carried out with patients with MS walking with a sensorized crutch tip. This tip allows to define new indicators that can be correlated with the clinical assessment scales and provide further objective and quantitative information to assess gait performance and level of impairment of patients with MS, and characterize their gait patterns. The results suggest that parameters such as the average cycle time and the average percentage of body weight might be useful to evaluate the gait performance and level of disability. Moreover, parameters related with the pitch angle of the crutch allow to determine crutch usage patterns and spot differences between patients with similar functional performance.

关键词： Inertial sensors sensor fusion sensorized crutch tip wearable sensors gait analysis multiple sclerosis

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High-Load Titanium Drilling Using an Accurate Robotic Machining system 9th

High-Load Titanium Drilling Using an Accurate Robotic Machin...

引用

9th IFIP International Precision Assembly Seminar, IPAS 2020

作者： Brownbill, Robert Silk, Philip Whiteside, Peter Hutabarat, Windo Burroughes, Harry Electroimpact UK Ltd. Manor Lane Hawarden DeesideCH5 3ST United Kingdom The Advanced Manufacturing Research Centre - The AMRC University of Sheffield Factory 2050 SheffieldS9 1ZA United Kingdom Department of Automatic Control and System Engineering University of Sheffield Portobello Street SheffieldS1 3JD United Kingdom

ISBN: (纸本)9783030726317

Robotic drilling systems have been used in the manufacture of large aerospace components for a number of years. systems have been developed by several systems integrators in order to accurately drill materials from CFRP to Titanium. These systems, however, have been unable to achieve large diameter holes in Titanium due to reduced structural stiffness and end effector capabilities. Typically, large holes are either drilled using large cartesian CNC-controlled machines or drilled using automated drilling units (ADU). However, there is a pull from aerospace OEMS to move away from large monolithic machines, in favour of flexible robotic system. Flexible robotic systems provide a number of benefits for large structure assembly. The following report primarily outlines drilling trials conducted on the Accurate Robotic Machining system, during which holes from 25 mm to 32 mm ID were drilled in titanium implementing an empirical test schedule. Additionally, a discussion on the benefits of drilling large diameter holes using flexible robotic platforms. © 2021, The Author(s).

关键词： Titanium

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Private and Robust Distributed Nonconvex Optimization via Polynomial Approximation

arXiv

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arXiv 2021年

作者： He, Zhiyu He, Jianping Chen, Cailian Guan, Xinping Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China Automatic Control Laboratory ETH Zürich Zürich8092 Switzerland

There has been work that exploits polynomial approximation to solve distributed nonconvex optimization problems involving univariate objectives. This idea facilitates arbitrarily precise global optimization without requiring local evaluations of gradients at every iteration. Nonetheless, there remains a gap between existing guarantees and practical requirements, e.g., privacy preservation and robustness to network imperfections. To fill this gap and keep the above strengths, we propose a Private and Robust Chebyshev-Proxy-based distributed Optimization Algorithm (PR-CPOA). Specifically, to ensure both the accuracy of solutions and the privacy of local objectives, we design a new privacy-preserving mechanism. This mechanism leverages the randomness in blockwise insertions of perturbed vector states and hence provides a stronger privacy guarantee in the scope of (α, β)-data-privacy. Furthermore, to gain robustness against network imperfections, we use the push-sum consensus protocol as a backbone and discuss its specific enhancements. Thanks to the purely consensus-type iterations, we avoid the privacy-accuracy trade-off and the bother of selecting proper step sizes in different settings. We rigorously analyze the accuracy, privacy, and complexity of the proposed algorithm. We show that the advantages brought by introducing polynomial approximation are maintained when all the above requirements exist. © 2021, CC BY-NC-SA.

关键词： Polynomial approximation

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PoCET: a Polynomial Chaos Expansion Toolbox for Matlab

引用

IFAC-PapersOnLine 2020年第2期53卷 7256-7261页

作者： Felix Petzke Ali Mesbah Stefan Streif Automatic Control & System Dynamics Lab at Technische Universität Chemnitz Faculty for Electrical Engineering and Information Technology Chemnitz Germany Department of Chemical and Biomolecular Engineering University of California Berkeley CA USA

We introduce PoCET: a free and open-scource Polynomial Chaos Expansion Toolbox for Matlab, featuring the automatic generation of polynomial chaos expansion (PCE) for linear and nonlinear dynamic systems with time-invariant stochastic parameters or initial conditions, as well as several simulation tools. It offers a built-in handling of Gaussian, uniform, and beta probability density functions, projection and collocation-based calculation of PCE coefficients, and the calculation of stochastic moments from a PCE. Efficient algorithms for the calculation of the involved integrals have been designed in order to increase its applicability. PoCET comes with a variety of introductory and instructive examples. Throughout the paper we show how to perform a polynomial chaos expansion on a simple ordinary differential equation using PoCET, as well as how it can be used to solve the more complex task of optimal experimental design.

关键词： polynomial chaos simulation tools optimal experiment design optimal control

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Automation Software Architecture in CPPS - Definition, Challenges and Research Potentials

Automation Software Architecture in CPPS - Definition, Chall...

引用

Industrial Cyber-Physical systems (ICPS)

作者： Birgit Vogel– Heuser Eva– Maria Neumann Juliane Fischer Marga Marcos Elisabet Esté vez Esté vez Giacomo Barbieri Lisa Sonnleithner Rick Rabiser Institute of Automation and Information Systems TUM School of Engineering and Design Core Member of MDSI Member of MIRMI Technical University of Munich Garching Germany Institute of Automation and Information Systems TUM School of Engineering and Design Technical University of Munich Garching Germany Department of Automatic Control and System Engineering ETSI Bilbao Basque Country University Bilbao Spain Electronics and Automation Engineering Department University of Ja&#x00E9 n Ja&#x00E9 n Spain Department of Mechanical Engineering Universidad de los Andes Bogot&#x00E1 Colombia CDL VaSiCS LIT CPS Lab Johannes Kepler University Linz Linz Austria

The importance of a mature, maintainable design of automation software in Cyber-Physical Production systems (CPPS) is continuously increasing since a growing proportion of the system functionality is implemented via software. As a result, system complexity is shifting more and more towards the software side. Quality characteristics such as flexibility, maintainability, and extensibility, whose importance is increasing in the context of Industry 4.0, are thus becoming harder to achieve. These challenges can only be solved through sound architectural design. While there is a common understanding of good software architecture and appropriate methods to achieve it in computer science, a suitable architecture definition for automation software that takes all relevant factors into account is still missing in the field of CPPS. Therefore, based on a workshop with international scientists with different perspectives on CPPS, this paper presents influencing factors on automation software architecture. On this basis, a joint definition for software architecture in CPPS, as well as challenges and future research potentials, are derived.

关键词： Computer science Production systems Software architecture Conferences Computer architecture Cyber-physical systems Software

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