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Extracting Stress-Related EEG Patterns from Pre-Sleep EEG for Forecasting Slow-Wave Sleep Deficiency

IEEE Transactions on Neural systems and Rehabilitation Engineering 2024年 32卷 1817-1827页

作者： Su, Cheng-Hua Ko, Li-Wei Jung, Tzyy-Ping Onton, Julie Tzou, Shey-Cherng Juang, Jia-Chi Hsu, Chung-Yao Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu300 Taiwan Institute of Electrical and Control Engineering National Yang Ming Chiao Tung University Hsinchu300 Taiwan Kaohsiung Medical University Drug Development and Value Creation Research Center Department of Biomedical Science and Environmental Biology Kaohsiung807 Taiwan University of California San Diego Swartz Center for Computational Neuroscience La Jolla CA92093 United States National Yang Ming Chiao Tung University Department of Computer Science Hsinchu300 Taiwan University of California San Diego Institute for Neural Computation La Jolla CA92093 United States National Yang Ming Chiao Tung University Department of Biological Science and Technology Hsinchu300 Taiwan Kaohsiung Medical University Hospital Sleep Disorders Center Department of Neurology Kaohsiung807 Taiwan Kaohsiung Medical University College of Medicine Department of Neurology Kaohsiung807 Taiwan

Sleep is vital to our daily activity. Lack of proper sleep can impair functionality and overall health. While stress is known for its detrimental impact on sleep quality, the precise effect of pre-sleep stress on subsequent sleep structure remains unknown. This study introduced a novel approach to study the pre-sleep stress effect on sleep structure, specifically slow-wave sleep (SWS) deficiency. To achieve this, we selected forehead resting EEG immediately before and upon sleep onset to extract stress-related neurological markers through power spectra and entropy analysis. These markers include beta/delta correlation, alpha asymmetry, fuzzy entropy (FuzzEn) and spectral entropy (SpEn). Fifteen subjects were included in this study. Our results showed that subjects lacking SWS often exhibited signs of stress in EEG, such as an increased beta/delta correlation, higher alpha asymmetry, and increased FuzzEn in frontal EEG. Conversely, individuals with ample SWS displayed a weak beta/delta correlation and reduced FuzzEn. Finally, we employed several supervised learning models and found that the selected neurological markers can predict subsequent SWS deficiency. Our investigation demonstrated that the classifiers could effectively predict varying levels of slow-wave sleep (SWS) from pre-sleep EEG segments, achieving a mean balanced accuracy surpassing 0.75. The SMOTE-Tomek resampling method could improve the performance to 0.77. This study suggests that stress-related neurological markers derived from pre-sleep EEG can effectively predict SWS deficiency. Such information can be integrated with existing sleep-improving techniques to provide a personalized sleep forecasting and improvement solution. © 2001-2011 IEEE.

关键词： Entropy

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Small-Scale Testbeds for Connected and Automated Vehicles and Robot Swarms: Challenges and a Roadmap

arXiv

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arXiv 2025年

作者： Xu, Jianye Alrifaee, Bassam Betz, Johannes Mokhtarian, Armin Mittal, Archak Cai, Mengchi Mangharam, Rahul Shehata, Omar M. Elias, Catherine M. Zaech, Jan-Nico Scheffe, Patrick Jahncke, Felix Ulhas, Sangeet Sankaramangalam Arfvidsson, Kaj Munhoz Department of Computer Science RWTH Aachen University Germany Department of Aerospace Engineering University of the Bundeswehr Munich Germany Professorship of Autonomous Vehicle Systems Technical University of Munich Germany Department of Civil Engineering Indian Institute of Technology Bombay India School of Vehicle and Mobility Tsinghua University China Department of Electrical and Systems Engineering University of Pennsylvania United States Mechatronics Engineering Department Faculty of Engineering and Materials Science The German University in Cairo Egypt Department of Computer Science Engineering The German University in Cairo Egypt INSAIT Sofia University "St. Kliment Ohridski" Bulgaria School for Engineering of Matter Transport and Energy Arizona State University United States Division of Decision and Control Systems KTH Royal Institute of Technology Sweden

This article proposes a roadmap to address the current challenges in small-scale testbeds for Connected and Automated Vehicles (CAVs) and robot swarms. The roadmap is a joint effort of participants in the workshop "1st Workshop on Small-Scale Testbeds for Connected and Automated Vehicles and Robot Swarms," held on June 2 at the IEEE Intelligent Vehicles Symposium (IV) 2024 in Jeju, South Korea. The roadmap contains three parts: 1) enhancing accessibility and diversity, especially for underrepresented communities, 2) sharing best practices for the development and maintenance of testbeds, and 3) connecting testbeds through an abstraction layer to support collaboration. The workshop features eight invited speakers, four contributed papers [1]–[4], and a presentation of a survey paper on testbeds [5]. The survey paper provides an online comparative table of more than 25 testbeds, available at https://***/testbeds-survey. The workshop’s own website is available at https://***/iv24-workshop. Copyright © 2025, The Authors. All rights reserved.

关键词： Testbeds

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Cybersecurity Threat Detection in the Behavior of IoT Devices: Analysis of Data Mining Competition Results 18

Cybersecurity Threat Detection in the Behavior of IoT Device...

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18th Conference on computer Science and Intelligence systems, FedCSIS 2023

作者： Czerwinski, Michal Michalak, Marcin Biczyk, Piotr Adamczyk, Blazej Iwanicki, Daniel Kostorz, Iwona Brzeczek, Maksym Janusz, Andrzej Hermansa, Marek Wawrowski, Lukasz Kozlowski, Artur Qed Software Mazowiecka 11/49 Warsaw0-052 Poland Ukasiewicz Research Network - Institute of Innovative Technologies Emag Leopolda 31 Katowice40-189 Poland Efigo Sp. Z O.o. M.Kopernika 8/6 Katowice40-064 Poland Faculty of Mathematics University of Warsaw Banacha 2 Warsaw02-097 Poland Department of Computer Networks and Systems Faculty of Automatic Control University of Technology Electronics and Computer Science Akademicka 16 Gliwice44-100 Poland

ISBN: (纸本)9788396744784

The paper discusses a data science competition centered around the development of an anomaly detection system for IoT devices. The competition utilized a unique environment that allowed for the operation and monitoring of real IoT devices, including scheduling of attacks on these devices. The environment was used to collect the data, which included both normal and attack-induced behavior of IoT devices. The paper presents the background of the competition, the top models submitted, and the competition results. The paper also includes a discussion about restrictions related to the use of synthetic attack data as input for constructing anomaly detection systems. © 2023 Polish Information Processing Society.

关键词： Quality control

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Combined LPV and ultra-local model-based control design approach for autonomous vehicles

Combined LPV and ultra-local model-based control design appr...

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IEEE Conference on Decision and control

作者： Dániel Fényes Tamás Hegedűs Balázs Németh Zoltán Szabó Péter Gáspár Eötvös Loránd Research Network (ELKH) Institute for Computer Science and Control (SZTAKI) Budapest Hungary Department for Control of Transportation and Vehicle Systems Budapest University of Technology and Economics Budapest Hungary

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

The paper presents a novel approach for controlling highly nonlinear systems using the combination of LPV framework and ultra-local model-based solution. Firstly, a new formulation of the ultra-local model is presented, by which the implementation-related issues can be overcome. Secondly, an extended state-space representation is introduced, which includes the nominal model of the considered nonlinear system and the effect of the ultra-local model. This extended state-space representation serves as the basis of LPV-based control design. In this way, the stability of the closed-loop system can be guaranteed, while the variation of the tuning parameter (α) of the ultra-local model can also be handled. The effectiveness and the operation of the proposed control strategy are demonstrated through a vehicle-oriented control problem.

关键词： Uncertainty control design Life estimation Stability analysis Software Closed loop systems Software measurement

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Global solution to sensor network localization: A non-convex potential game approach and its distributed implementation

arXiv

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arXiv 2024年

作者： Xu, Gehui Chen, Guanpu Hong, Yiguang Fidan, Baris Parisini, Thomas Johansson, Karl H. Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing100190 China The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures StockholmSE-10044 Sweden Department of Control Science and Engineering Tongji University Shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210 China The Department of Mechanical and Mechatronics Engineering University of Waterloo WaterlooONN2L 3G1 Canada The Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom The Department of Engineering and Architecture University of Trieste Trieste34127 Italy

Consider a sensor network consisting of both anchor and non-anchor nodes. We address the following sensor network localization (SNL) problem: given the physical locations of anchor nodes and relative measurements among all nodes, determine the locations of all non-anchor nodes. The solution to the SNL problem is challenging due to its inherent non-convexity. In this paper, the problem takes on the form of a multi-player nonconvex potential game in which canonical duality theory is used to define a complementary dual potential function. After showing the Nash equilibrium (NE) correspondent to the SNL solution, we provide a necessary and sufficient condition for a stationary point to coincide with the NE. An algorithm is proposed_ to reach the NE and shown to have convergence rate O(1/√k). With the aim of reducing the information exchange within a network, a distributed algorithm for NE seeking is implemented and its global convergence analysis is provided. Extensive simulations show the validity and effectiveness of the proposed approach to solve the SNL problem. Copyright © 2024, The Authors. All rights reserved.

关键词： Game theory

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Grouping Handwritten Letter Strokes Using a Fuzzy Decision Tree 19th

Grouping Handwritten Letter Strokes Using a Fuzzy Decision T...

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19th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2020

作者： Wróbel, Michal Starczewski, Janusz T. Napoli, Christian Department of Intelligent Computer Systems Czestochowa University of Technology Czestochowa Poland Department of Computer Control and Management Engineering Sapienza University of Rome Roma Italy

ISBN: (纸本)9783030615338

This paper presents an algorithm for grouping strokes. This method includes two stages. Firstly, a set of strokes is transformed into a set of hypotheses that a group of strokes matches the pattern. For this purpose, a method for comparing small groups of strokes is proposed. Then, the set of hypotheses is selected with the use of a decision tree to get a proposition of a word. © 2020, Springer Nature Switzerland AG.

关键词： Decision trees

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Robust control design using ultra-local model-based approach for vehicle-oriented control problems

Robust control design using ultra-local model-based approach...

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European control Conference (ECC)

作者： Dá niel Fé nyes Tamá s Hegedű s Balá zs Né meth Zoltá n Szabó Pé ter Gá spá r Institute for Computer Science and Control (SZTAKI) E&#x00F6 tv&#x00F6 s Lor&#x00E1 nd Research Network (ELKH) Budapest Hungary Department for Control of Transportation and Vehicle Systems Budapest University of Technology and Economics Budapest Hungary

ISBN: (数字)9783907144077

ISBN: (纸本)9781665497336

Model Free control (MFC) with ultra-local model is novel design method to provide high performance control for systems with nonlinear dynamics. The basic concept of this approach is to compute an ultra-local model, which is valid for a short period of time. Although the concept has already been successfully applied for various vehicle control problems, there are some open issues regarding the robustness and the stability of the closed-loop controlled system. This paper presents a method for designing a robust control based on $\mathcal{H}_{\infty}$ synthesis, with which a solution on these issues can be found. In the proposed MFC strategy the ultra-local model-based control is in the inner loop of the control structure. Moreover, a robust $\mathcal{H}_{\infty}$ control for the outer loop is designed, in whose control-oriented model the control of the inner loop is incorporated. The control strategy is implemented in high-fidelity vehicle dynamic environment and its efficiency and operation are demonstrated through a complex simulation example.

关键词： Robust control control design Computational modeling Design methodology Process control Stability analysis Software

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Safe trajectory design for indoor drones using reinforcement-learning-based methods

Safe trajectory design for indoor drones using reinforcement...

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International Symposium on Applied Computational Intelligence and Informatics ( SACI)

作者： Dénes Tompos Balázs Németh Eötvös Loránd Research Network (ELKH) Kende utca 13-17. Institute for Computer Science and Control (SZTAKI) Budapest Hungary Department of Control for Transportation and Vehicle Systems Budapest University of Technology and Economics Stoczek u. 2. Budapest Hungary

This paper proposes a design method for achieving safe trajectory of indoor drones. The trajectory design with a reinforcement-learning-based (RL) agent is facilitated, which can result in efficient and collision-free motion. The method is developed for motion in indoor area with moving mobile robots, and thus, the collision with these obstacles must be avoided. Through RL-based design the fast motion of the drones can be achieved, which must perform a mission between workstations in a manufacturing system. The effectiveness of the design process through a simulation example on a real laboratory environment is illustrated.

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Hierarchical control design of automated vehicles for multi-vehicle scenarios in roundabouts

Hierarchical control design of automated vehicles for multi-...

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European control Conference (ECC)

作者： Balá zs Né meth Zsó fia Farkas Zoltá n Antal Pé ter Gá spá r Institute for Computer Science and Control (SZTAKI) E&#x00F6 tv&#x00F6 s Lor&#x00E1 nd Research Network (ELKH) Budapest Hungary Department of Control for Transportation and Vehicle Systems Budapest University of Technology and Economics Budapest Hungary

ISBN: (数字)9783907144077

ISBN: (纸本)9781665497336

control design for safe and time-efficient motion of automated vehicles in roundabout scenarios poses various challenges, especially adaptation to the actual traffic scenario and coordination of the vehicles. This paper proposes the design of a hierarchical motion control with learning functionality for roundabout scenarios. The control is designed on two levels, such as on cloud level and on vehicle level. The control on the cloud level is designed by using reinforcement learning, with which the maximum speed for the vehicle is achieved. The vehicle level contains a robust controller and a supervisor, with which the collision avoidance of the vehicles is guaranteed. The proposed control on Hardware-in-the-Loop environment with small-scaled indoor vehicles is implemented. The effectiveness of the control and the safe motion of the automated vehicle under various scenarios are demonstrated. The provided scenarios illustrate that safe, i.e., collision-free motion of the automated vehicle can be guaranteed, even if the connection to the cloud has been lost.

关键词： Motion planning Systematics control design Design methodology Europe Reinforcement learning Complexity theory

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Partial-Node-Based State Estimation for Complex Networks With Energy Harvesting Sensors

Partial-Node-Based State Estimation for Complex Networks Wit...

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International Conference on Automation and Computing (ICAC)

作者： Yu-Ang Wang Zidong Wang Fan Wang Lei Zou College of Information Science and Technology Donghua University Shanghai China Department of Computer Science Brunel University London Uxbridge Middlesex United Kingdom Institute for Automatic Control and Complex Systems (AKS) University of Duisburg-Essen Duisburg Germany

In this paper, the recursive partial-node-based (PN-B) state estimation problem is investigated for a class of time-varying complex networks (CNs) with energy harvesting sensors (EHSs). Measurements are transmitted to the remote state estimator by the EHSs only when the current energy level can compensate for the energy consumption. Only a part of the network nodes' measurements, which are available to the users, are utilized to estimate the network states. The objective of this problem is to design a recursive state estimator for CNs with EHSs based on available measurements observed from partial nodes. The upper bound of the estimation error covariance is first established with the help of intensive scholastic techniques and induction approach. Then, the required estimator gain is determined by minimizing such an upper bound. Finally, an illustrative example is presented to verify the effectiveness of the proposed PNB state estimation method.

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