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Electroencephalogram and Event-Related Potential in Mild Cognitive Impairment: Recent Developments in Signal Processing, Machine Learning, and Deep Learning

IEEE Journal of Selected Areas in Sensors

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IEEE Journal of Selected Areas in Sensors 2025年 2卷 162-184页

作者： Azami, Hamed Mirjalili, Mina Rajji, Tarek K. Wu, Chien-Te Humeau-Heurtier, Anne Jung, Tzyy-Ping Wei, Chun-Shu Trinh, Thanh-Tung Liu, Yi-Hung University of Toronto Centre for Addiction and Mental Health TorontoONM5S 1A1 Canada University of Texas Southwestern Medical Center DallasTX75390 United States University of Florida Department of Occupational Therapy GainesvilleFL32611 United States University of Florida Center for Cognitive Aging and Memory McKnight Brain Institute GainesvilleFL32611 United States University of Angers LARIS SFR MATHSTIC AngersF-49000 France University of California Institute for Neural Computation Institute of Engineering in Medicine La Jolla CA92093 United States National Yang Ming Chiao Tung University Department of Computer Science Hsinchu City30010 Taiwan National Taipei University of Technology Graduate Institute of Manufacturing Technology College of Mechanical and Electrical Engineering Taipei10608 Taiwan Vietnam National University Department of Information and Communication Technology Faculty of Nontraditional Security HSB Hanoi720325 Viet Nam National Yang Ming Chiao Tung University Institute of Electrical and Control Engineering Hsinchu City30010 Taiwan

Mild cognitive impairment (MCI) is an early stage of non-age-related cognitive decline with an increased risk of progressing to dementia. Early detection of MCI is essential for implementing preventative strategies that can delay or prevent the onset of dementia, ultimately improving patient outcomes and reducing healthcare costs. Electroencephalograms (EEGs) and event-related potentials (ERPs) have shown significant promise in detecting MCI due to their affordability, real-time monitoring capabilities, and noninvasiveness. EEG provides continuous brain activity data, while ERPs offer insights into specific cognitive processes by analyzing brain responses to stimuli. These methods can complement each other in MCI diagnosis by providing a comprehensive view of overall brain function and detailed information on specific cognitive processes. However, EEG and ERP are susceptible to noise and interindividual variability, which can hinder their reliability. In addition, applying machine learning models on EEG or ERP for MCI detection presents challenges such as the risk of overfitting and difficulties in interpreting the underlying decision-making process. This review emphasizes recent advancements in signal processing and feature extraction methods applied to EEG and ERP data and explores the use of machine learning and deep learning techniques to enhance diagnostic accuracy and interpretative depth. By integrating these methodologies, the review highlights how EEG and ERP can contribute to a more effective understanding and monitoring of cognitive changes associated with MCI, underscoring the importance of early diagnosis for timely intervention and improved patient care. Finally, the review focuses on future research directions, including the development of advanced analytical techniques and multimodal integration approaches involving EEG and ERP to further improve diagnostic accuracy and clinical application. © 2024 IEEE.

关键词： Deep learning

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GLOBAL INTERNAL STABILIZABILITY DOES NOT IMPLY GLOBAL EXTERNAL STABILIZABILITY FOR SMALL SENSOR DISTURBANCES

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IEEE TRANSACTIONS ON AUTOMATIC control 1995年第12期40卷 2119-2122页

作者： FREEMAN, R Center for Control Engineering and Computation Department of Electrical and Computer Engineering University of California Santa Barbara CA USA

It was shown in [1] that for control-affine nonlinear systems, global asymptotic stabilizability via continuous state feedback implies global input-to-state stabilizability with respect to actuator disturbances. We show that the analogous result for sensor disturbances does not hold: we construct a second-order system which admits a continuous memoryless globally asymptotically stabilizing state feedback controller but for which no such controller can prevent finite escape times from every initial condition in the presence of small sensor disturbances.

关键词： Asymptotic stability Actuators Sensor systems control systems Nonlinear systems Nonlinear control systems State feedback Robust stability control theory Working environment noise

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Tracking controllers for systems linear in the unmeasured states

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AUTOMATICA 1996年第5期32卷 735-746页

作者： Freeman, RA Kokotovic, PV [a] Center for Control Engineering and Computation Department of Electrical and Computer Engineering University of California Santa Barbara CA 93106 U.S.A.

We introduce a class of extended strict feedback nonlinear systems in which unmeasured states enter the system equations in a linear (affine) fashion. For such systems, we present a procedure for constructing dynamic partial state feedback controllers that achieve the global asymptotic tracking of given reference trajectories while maintaining internal boundedness. The controller dynamic order is equal to the number of unmeasured states. To illustrate our design procedure, we construct such a tracking controller for a nonlinear electromechanical rotor/platform system. Copyright (C) 1996 Elsevier Science Ltd.

关键词： nonlinear systems global stability tracking disturbance rejection dynamic output feedback Lyapunov methods

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Fundamental design tradeoffs in filtering, prediction, and smoothing

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IEEE TRANSACTIONS ON AUTOMATIC control 1997年第9期42卷 1240-1251页

作者： Goodwin, GC Seron, MM Centre for Integrated Dynamics and Control Department of Electrical and Computer Engineering University of Newcastle NSW Australia Center for Control Engineering and Computation University of California Santa Barbara CA USA

This paper examines fundamental design tradeoffs that apply to all linear filtering, prediction, and smoothing problems, We introduce sensitivity functions that quantify filter performance, and we show that their frequency response satisfies constraints imposed by unstable poles and nonminimum phase zeros of the system, The constraints allow one to determine, a priori, whether or not a desired filter performance is attainable and how different arrangements of the measurement system influence the achievable performance.

关键词： Bode limits linear filtering performance limits

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Converse Lyapunov theorems and robust asymptotic stability for hybrid systems

Converse Lyapunov theorems and robust asymptotic stability f...

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2005 American control Conference, ACC

作者： Cai, Chaohong Teel, Andrew R. Goebel, Rafal Center for Control Engineering and Computation Department of Electrical and Computer Engineering University of California Santa Barbara

ISBN: (纸本)0780390989

We state results on the existence of smooth Lyapunov functions for hybrid systems whose solutions satisfy a class-K script L sign script L sign estimate with respect to two measures. The class-K script L sign script L sign estimate, a natural extension of class-K script L sign estimate, is in terms of the elapsed time and the number of jumps that have occurred. The main result is that a smooth Lyapunov function exists if and only if the class-K script L sign script L sign estimate is robust. In turn, sufficient conditions for robustness are given. Special cases include systems with compact attractors. Most of the results parallel, and unify, what has been developed previously for differential inclusions and difference inclusions. © 2005 AACC.

关键词： Hybrid computers

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CONTRACTION AND CONCENTRATION OF MEASURES WITH APPLICATIONS TO THEORETICAL NEUROSCIENCE

arXiv

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arXiv 2025年

作者： Betteti, Simone Bullo, Francesco Department of Information Engineering Università degli Studi di Padova Padova35131 Italy Center for Control Dynamical Systems and Computation University of California at Santa Barbara Santa BarbaraCA93106 IT United States

We investigate the asymptotic behavior of probability measures associated with stochastic dynamical systems featuring either globally contracting or Br-contracting drift terms. While classical results often assume constant diffusion and gradient-based drifts, we extend the analysis to spatially inhomogeneous diffusion and non-integrable vector fields. We establish sufficient conditions for the existence and uniqueness of stationary measures under global contraction, showing that convergence is preserved when the contraction rate dominates diffusion inhomogeneity. For systems contracting only outside of a compact set and with constant diffusion, we demonstrate mass concentration near the minima of an associated non-convex potential, like in multistable regimes. The theoretical findings are illustrated through Hopfield networks, highlighting implications for memory retrieval dynamics in noisy *** Codes 35Q84, 60G10 © 2025, CC BY.

关键词： Random processes

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Comparative Study of Parametric Disturbances Effect on Cart-Inverted Pendulum System Stabilization 1

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International Conference on Modern Electronics Devices and Communication Systems, MEDCOM 2021

作者： Verma, Neelam Valluru, Sudarshan K. Department of Electrical Engineering Center for Control of Dynamical Systems and Computation Delhi Technological University Delhi India

ISBN: (数字)9789811963834

ISBN: (纸本)9789811963827

The main motivation behind the present work was to validate the impact of pendulum mass, cart mass, and length of pendulum on stabilization and swing-up of cart-inverted pendulum. Inverted pendulum system is a classic benchmark example of underactuated electro-mechanical systems, where the degree of freedom is less than the number of inputs available. PID controller was designed for a set of parameter values of the system. MATLAB simulation was carried out for different values of pendulum mass (0.2–0.25 kg), pendulum length (0.3–0.34 m), and cart mass (2.3–2.45 kg). The performance of considered cart- inverted pendulum system is demonstrated with simulation results for a different set of results, and a comparative analysis was made to comment on their effects on swing-up and stabilization. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Stabilization

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computation of Hopf Bifurcation Points in the Magnetic Levitation System 4th

Computation of Hopf Bifurcation Points in the Magnetic Levit...

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4th International Conference on Information and Communication Technology for Intelligent Systems, ICTIS 2020

作者： Valluru, Sudarshan K. Gupta, Anshul Verma, Aditya Center for Control of Dynamical Systems and Computation Department of Electrical Engineering Delhi Technological University Delhi110042 India

ISBN: (纸本)9789811570773

This research brief aims to study the bifurcation analysis of an electromagnetic levitation (maglev) system. The bifurcation analysis involves first performing the numerical analysis, and then the simulations using MATLAB are analyzed to verify the results. The study requires derivation of a mathematical model for the maglev system, which can be used for the bifurcation analysis. The bifurcation analysis involves a numerical comparison of the system equations with the predefined constraints. The input voltage is being used as the bifurcation parameter, which is by ball’s position, ball’s velocity, and the current flowing through the circuit. The analysis allows us to compute a combination of values of parameters, when simulations are performed to check system characteristics, periodic oscillations at these values are obtained. Hence, it proves the existence of Hopf bifurcation at the computed value of system parameters. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Hopf bifurcation

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Optimization Strategy of Bio-Inspired Metaheuristic Algorithms Tuned PID controller for PMBDC Actuated Robotic Manipulator 3

Optimization Strategy of Bio-Inspired Metaheuristic Algorith...

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3rd International Conference on Computing and Network Communications, CoCoNet 2019

作者： Valluru, Sudarshan K. Singh, Madhusudan Center for Control of Dynamical Systems and Computation Department of Electrical Engineering Delhi Technological University Delhi110042 India

The present article makes an attempt to evaluate the computational performance of genetic meta heuristic optimized control algorithms. Here, the multi-objective bio inspired algorithm (MOGA) and adaptive particle swarm optimization (APSO) algorithm are used to tune linear PID (L-PID) and nonlinear PID(NL-PID) controllers to implement performance and execution control of permanent magnet brushed DC (PMBDC) motor actuated robotic manipulator. The MOGA, APSO optimised nonlinear and linear PID controllers have been validated for their response efficacy and compared in respect of the steady-state error, overshoot and settling time of PMBDC driven robotic Manipulator. The efficacy of metaheuristics such as APSO and MOGA tuned NL-PID controller are better as compared to the L- PID controlled objects. Experimental results show that the NL-PID controller mends the controlled objects' performace with a reduction in both the overshoot as well as the settling time, if tuned either with MOGA or APSO for L-PID controllers while NL-PID controller tuned with APSO gives satisfactory dynamic response of the system. © 2020 The Authors. Published by Elsevier B.V.

关键词： Permanent magnets

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Exploiting the Intrinsic Neighborhood Semantic Structure for Domain Adaptation in EEG-based Emotion Recognition

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IEEE Transactions on Affective Computing 2025年

作者： Yang, Yi Wang, Ze Song, Yu Jia, Ziyu Wang, Boyu Jung, Tzyy-Ping Wan, Feng Macau University of Science and Technology Macao Centre for Mathematical Sciences Respiratory Disease AI Laboratory on Epidemic Intelligence and Medical Big Data Instrument Applications Faculty of Innovation Engineering 999078 China Tianjin University of Technology School of Electrical Engineering and Automation Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin300384 China Chinese Academy of Sciences Beijing Key Laboratory of Brainnetome and Brain-Computer Interface and Brainnetome Center Institute of Automation Beijing100045 China Western University Department of Computer Science Brain Mind Institute LondonONN6A 3K7 Canada University of California at San Diego Swartz Center for Computational Neuroscience Institute for Neural Computation La Jolla CA92093 United States University of Macau Department of Electrical and Computer Engineering Faculty of Science and Technology China University of Macau Centre for Cognitive and Brain Sciences Centre for Artificial Intelligence and Robotics Institute of Collaborative Innovation 999078 China

Due to the inherent non-stationarity and individual differences present in electroencephalogram (EEG) signals, developing a generalizable model that performs well on new subjects is challenging in EEG-based emotion recognition. Most existing domain adaptation (DA) methods typically mitigate these discrepancies by aligning the marginal distributions of domain feature representations. However, when there is a significant difference in the class-conditional distribution between domain features and labels, the domain-invariant features learned by aligning marginal distributions may have limited discriminative ability for unlabeled target instances or even prove counterproductive. To address this issue, we propose a Neighborhood Semantic Aware Learning-based Dynamic Graph Attention Convolution (NSAL-DGAT) approach that learns target semantic information by considering the inter-domain semantic topological structure, thereby improving classifier adaptation for target instances. Specifically, the proposed NSAL framework is designed to capitalize on the insight that after domain feature alignment, some target samples and their neighboring source samples exhibit similar semantics. By leveraging the neighborhood topological structure, we extract and incorporate semantic target features to train a more transferable classifier. Besides, we implement an entropy weighting mechanism to emphasize representative target semantic information, encouraging target instances to prioritize high-confidence individuals within the source neighborhood. We have conducted extensive experiments on the public SEED dataset and our collected the Hearing-Impaired EEG Dataset (HIED). The experimental results underscore the efficacy of our proposed NSAL-DGAT approach, showcasing state-of-the-art accuracy in subject-dependent as well as subject-independent scenarios. The source code is available at https://***/YYingDL/NSAL-DGAT. © 2010-2012 IEEE.

关键词： Speech analysis

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