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The applied principles of EEG analysis methods in neuroscience and clinical neurology

Military Medical Research 2024年第6期11卷 907-941页

作者： Hao Zhang Qing-Qi Zhou He Chen Xiao-Qing Hu Wei-Guang Li Yang Bai Jun-Xia Han Yao Wang Zhen-Hu Liang Dan Chen Feng-Yu Cong Jia-Qing Yan Xiao-Li Li School of Systems Science Beijing Normal UniversityBeijing 100875China College of Electrical and Control Engineering North China University of TechnologyBeijing 100041China School of Automation Science and Engineering South China University of TechnologyGuangzhou 510641China Department of Psychology the State Key Laboratory of Brain and Cognitive Sciencesthe University of Hong KongHong Kong SAR 999077China HKU-Shenzhen Institute of Research and Innovation Shenzhen 518057GuangdongChina Department of Health Technology and Informatics the Hong Kong Polytechnic UniversityHong Kong SAR 999077China Department of Rehabilitation Medicine the First Afliated Hospital of Nanchang UniversityNanchang 330006China Rehabilitation Medicine Clinical Research Center of Jiangxi Province Nanchang 330006China Beijing Key Laboratory of Learning and Cognition School of PsychologyCapital Normal UniversityBeijing 100048China School of Communication Science Beijing Language and Culture UniversityBeijing 100083China Institute of Electrical Engineering Yanshan UniversityQinhuangdao 066004HebeiChina School of Computer Science Wuhan UniversityWuhan 430072China School of Biomedical Engineering Faculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalian 116081LiaoningChina Guangdong Artifcial Intelligence and Digital Economy Laboratory(Guangzhou) Guangzhou 510335China.

Electroencephalography(EEG)is a non-invasive measurement method for brain *** to its safety,high resolution,and hypersensitivity to dynamic changes in brain neural signals,EEG has aroused much interest in scientific research and medical *** article reviews the types of EEG signals,multiple EEG signal analysis methods,and the application of relevant methods in the neuroscience feld and for diagnosing neurological ***,3 types of EEG signals,including time-invariant EEG,accurate event-related EEG,and random event-related EEG,are ***,5 main directions for the methods of EEG analysis,including power spectrum analysis,time-frequency analysis,connectivity analysis,source localization methods,and machine learning methods,are described in the main section,along with diferent sub-methods and effect evaluations for solving the same ***,the application scenarios of different EEG analysis methods are emphasized,and the advantages and disadvantages of similar methods are *** article is expected to assist researchers in selecting suitable EEG analysis methods based on their research objectives,provide references for subsequent research,and summarize current issues and prospects for the future.

关键词： Electroencephalogram analysis methods Applied principles Neuroscience Diagnosis Neurological diseases

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Distributed Learning by Local Training ADMM

Distributed Learning by Local Training ADMM

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IEEE Conference on Decision and Control

作者： Xiaoxing Ren Nicola Bastianello Karl H. Johansson Thomas Parisini Department of Electrical and Electronic Engineering Imperial College London London United Kingdom 2School of Electrical Engineering and Computer Science and Digital Futures KTH Royal Institute of Technology Stockholm Sweden Department of Electronic Systems Aalborg University Denmark Department of Engineering and Architecture University of Trieste Trieste Italy

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In this paper, we focus on distributed learning over peer-to-peer networks. In particular, we address the challenge of expensive communications (which arise when e.g. training neural networks), by proposing a novel local training algorithm, LTADMM. We extend the distributed ADMM enabling the agents to perform multiple local gradient steps per communication round (local training). We present a preliminary convergence analysis of the algorithm under a graph regularity assumption, and show how the use of local training does not compromise the accuracy of the learned model. We compare the algorithm with the state of the art for a classification task, and in different set-ups. The results are very promising showing a great performance of LT-ADMM, and paving the way for future important theoretical developments.

关键词： Training computer aided instruction Analytical models Accuracy Distance learning Neural networks Classification algorithms Topology Peer-to-peer computing Convergence

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Performance Bounds for Policy-Based Reinforcement Learning Methods in Zero-Sum Markov Games with Linear Function Approximation

Performance Bounds for Policy-Based Reinforcement Learning M...

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IEEE Conference on Decision and Control

作者： Anna Winnicki R. Srikant Department of Electrical and Computer Engineering Coordinated Science Laboratory University of Illinois at Urbana-Champaign C3.ai Digital Transformation Institute

Until recently, efficient policy iteration algorithms for zero-sum Markov games that converge were unknown. Therefore, model-based RL algorithms for such problems could not use policy iteration in the planning modules of the algorithms. In an earlier paper, we showed that a convergent policy iteration algorithm can be obtained by using a commonly used technique in RL called lookahead. However, the algorithm could be applied to the function approximation setting only in the special case of linear MDPs (Markov Decision Processes). In this paper, we obtain performance bounds for policy-based RL algorithms for general settings, including one where policy evaluation is performed using noisy samples of (state, action, reward) triplets from a single sample path of a given policy.

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Practical and Ethical Considerations for Generative AI in Medical Imaging 2nd

Practical and Ethical Considerations for Generative AI in...

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2nd International Workshop on Fairness of AI in Medical Imaging, FAIMI 2024, and 3rd International Workshop on Ethical and Philosophical Issues in Medical Imaging, EPIMI 2024, Held in Conjunction with the International Conference on Medical Image Computing and computer Assisted Interventions, MICCAI 2024

作者： Jha, Debesh Rauniyar, Ashish Hagos, Desta Haileselassie Sharma, Vanshali Tomar, Nikhil Kumar Zhang, Zheyuan Isler, Ilkin Durak, Gorkem Wallace, Michael Yazici, Cemal Berzin, Tyler Biswas, Koushik Bagci, Ulas Machine and Hybrid Intelligence Laboratory Northwestern University Evanston United States SINTEF Digital Trondheim Norway Department of Electrical Engineering and Computer Science Howard University WashingtonDC United States Department of Computer Science University of Central Florida Orlando United States Mayo Clinic Florida Jacksonville United States Department of Medicine University of Chicago Chicago United States Beth Israel Deaconess Medical Center Harvard Medical School Boston United States

ISBN: (纸本)9783031727863

Generative Artificial Intelligence (AI) has the potential to transform medicine. It is helpful to clinicians and radiologists for diagnosis, screening, treatment planning, interventions, and drug development. It benefits the clinical flow with real-time decision-support systems. While generative AI can potentially improve healthcare, it also introduces new ethical issues that require careful analysis and mitigation strategies. This work emphasizes the ethical aspects of generative AI in medical imaging, aiming to ensure that advancements in this field align with established ethical principles and societal values. We delve into the ethical implications surrounding bias, fairness, patient privacy, consent, transparency, explainability, intellectual property, and data ownership. Furthermore, we discuss regulations governing the use of synthetic medical data. To promote equitable application of these powerful tools, we also propose clear guidelines for promoting fairness, mitigating bias, and ensuring diversity within generative AI models. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Differential privacy

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Distributed Massive MIMO-Aided Task Offloading in Satellite-Terrestrial Integrated Multi-Tier VEC Networks

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IEEE Transactions on Vehicular Technology 2025年

作者： Liu, Yixin Liang, Shaoling Wang, Kunlun Chen, Wen Li, Yonghui Karagiannidis, George K. East China Normal University School of Communication and Electronic Engineering Shanghai200241 China Guangxi Key Laboratory of Digital Infrastructure Nanning530000 China Shanghai Jiao Tong University Department of Electronic Engineering Shanghai200240 China University of Sydney School of Electrical and Information Engineering Australia Aristotle University of Thessaloniki Department of Electrical and Computer Engineering Thessaloniki54 124 Greece

This paper proposes a distributed massive multiple-input multiple-output (DM-MIMO) aided multi-tier vehicular edge computing (VEC) system. In particular, each vehicle terminal (VT) offloads its computational task to the roadside unit (RSU) by orthogonal frequency division multiple access (OFDMA), which can be computed locally at the RSU and offloaded to the central processing unit (CPU) via massive satellite access points (SAPs) for remote computation. By considering the partial task offloading model, we consider the joint optimization of the task offloading, subchannel allocation and precoding optimization to minimize the total cost in terms of total delay and energy consumption. To solve this non-convex problem, we transform the original problem into three sub-problems and use the alternate optimization algorithm to solve it. First, we transform the subcarrier allocation problem of discrete variables into the convex optimization problem of continuous variables. First, we transform the subcarrier allocation problem of discrete variables into the convex optimization problem of continuous variables. Then, we use multiple quadratic transformations and the Lagrange multiplier method to transform the non-convex subproblem of optimizing precoding vectors into a convex problem, while the task offloading subproblem is a convex problem. Given the subcarrier and the task allocation and precoding result, we finally find the joint optimized results by the iterative optimization algorithm. Simulation results show that our proposed algorithm is superior to other benchmarks. © 1967-2012 IEEE.

关键词： Convex optimization

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CVNN-based Channel Estimation and Equalization in OFDM Systems Without Cyclic Prefix

arXiv

引用

arXiv 2023年

作者： dos Santos Sousa, Heitor Soares, Jonathan Aguiar Mayer, Kayol Soares Arantes, Dalton Soares The Digital Communications Laboratory - Com-Lab Department of Communications School of Electrical and Computer Engineering University of Campinas - Unicamp SP Campinas13083-852 Brazil

In modern communication systems operating with Orthogonal Frequency-Division Multiplexing (OFDM), channel estimation requires minimal complexity with one-tap equalizers. However, this depends on cyclic prefixes, which must be sufficiently large to cover the channel impulse response. Conversely, the use of cyclic prefix (CP) decreases the useful information that can be conveyed in an OFDM frame, thereby degrading the spectral efficiency of the system. In this context, we study the impact of CPs on channel estimation with complex-valued neural networks (CVNNs). We show that the phase-transmittance radial basis function neural network offers superior results, in terms of required energy per bit, compared to classical minimum mean-squared error and least squares algorithms in scenarios without CP. © 2023, CC BY.

关键词： Orthogonal frequency division multiplexing

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Lane Detection Using Hough Transform and Kalman Filter

Lane Detection Using Hough Transform and Kalman Filter

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E-mobility, Power Control and Smart Systems (ICEMPS), International Conference on

作者： Rajesh Kannan Megalingam Nidhin Chuzhiyil Pradeep Aswin Reghu Sreesankar Ajith Sreemangalam Abdul Ayaaz Avinash Hegde Kota Department of Electronics and Communication Engineering Humanitarian Technology (HuT) Labs Amrita Vishwa Vidyapeetham Amritapuri India Electrical and Computer Engineering Department Digital Design Environment Laboratory (DDEL) University of Cincinnati Cincinnati OH USA

ISBN: (数字)9798350394399

ISBN: (纸本)9798350394405

The objective of this paper is to implement an effective and robust lane detection system for autonomous vehicles. This can be achieved by generating road images using MATLAB, converting them into a bird's-eye view for a clear perspective of the lanes, and then applying the Kalman filter for accurate lane detection. After using the Hough transform and Kalman filter the lanes on a video clip that has been recorded from inside a car using a phone camera will be detected. The system is implemented in real-world scenarios to ensure its effectiveness and reliability in various road conditions and environments. The goal is to improve road safety and navigation by providing precise lane information.

关键词： Accuracy Lane detection Filtering Power control Process control Transforms Road safety

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Annapoorna – Food, Water and Medicine Delivery Teleoperated Robot with Telemedicine Facility

Annapoorna – Food, Water and Medicine Delivery Teleoperated...

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E-mobility, Power Control and Smart Systems (ICEMPS), International Conference on

作者： Rajesh Kannan Megalingam Sakthiprasad Kuttankulangara Manoharan Avinash Hegde Kota Department of Electronics and Communication Engineering Humanitarian Technology (HuT) Labs Amrita Vishwa Vidyapeetham Amritapuri India Electrical and Computer Engineering Department Digital Design Environment Laboratory (DDEL) University of Cincinnati Cincinnati OH USA

ISBN: (数字)9798350394399

ISBN: (纸本)9798350394405

Annapoorna is a tele-operated robot to deliver food, water, and medicines to COVID patients in isolation wards. It is equipped with a telemedicine facility for doctors and nurses to interact with patients remotely. This greatly reduces direct contact of doctors, nurses, and food service staff with patients during COVID or other pandemic times, thereby reducing infection risk. The battery powered robot reaches each bedside to serve food and medicines to the patients in isolation wards. The robot can be controlled by smartphone app or wireless joystick controller. The tablet attached at the top of the robot serves dual purpose. The doctors and nurses can interact with the patient with any online meeting portals like Skype, Google Hangout, Zoom etc. In addition, the operator can control the robot using the tablet camera there by saving additional cost for the camera.

关键词： COVID-19 Wireless communication Navigation Tuberculosis Telemedicine Robot vision systems Cameras

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engineering CsPbI2Br Perovskite Thin Film Morphology with Ionic Liquid Additives for Enhanced Performance Solar Cells

Engineering CsPbI2Br Perovskite Thin Film Morphology with Io...

引用

IEEE Conference Photovoltaic Specialists (PVSC)

作者： Gulzhan Zhumadil Vladimir Pavlenko Gaukhar Nigmetova Zhuldyz Yelzhanova Mannix P. Balanay Annie Ng Department of Electrical and Computer Engineering School of Engineering and Digital Sciences Nazarbayev University Astana Kazakhstan National Laboratory of Astana Nazarbayev University Astana Kazakhstan Department of Chemistry Sciences and Humanities Nazarbayev University Astana Kazakhstan

ISBN: (数字)9781665464260

ISBN: (纸本)9781665475822

Ionic liquids (ILs) have emerged as a promising class of additive for modulating perovskite crystallization behavior and thin film morphology. However, the influence of incorporating ILs directly within the cesium lead iodide bromide (CsPbI 2 Br) perovskite precursor system is less explored. This work aims to investigate the impact of using various IL additives in the bulk of the CsPbI 2 Br perovskite material and how it affects thin film formation. We study the morphology of CsPbI 2 Br when incorporated with five different ILs based on the common 1-ethyl-3-methylimidazolium [EMIM] + cation, but varying the anion: bis(pentafluoroethylsulfonyl)imide ([EMIM] + [PFSI] − ), bis(trifluoromethylsulfonyl)imide ([EMIM] + [TFSI] − ), diethyl phosphate ([EMIM] + [DEP] − ), dimethyl phosphate ([EMIM] + [DMP] − ), and hexafluorophosphate ([EMIM] + [PF6] − ). Through characterization of the perovskite films, we found that the morphology of CsPbI 2 Br is largely different depending on the choice of IL used. These morphological changes provide insights into how different IL-perovskite interactions affect crystallization and thus thin film quality. The experimental results help in understanding of IL-mediated crystallization, facilitating the development of additive engineering for high-performance perovskite solar cells (PSCs).

关键词： Photovoltaic systems Additives Systematics Liquids Films Photovoltaic cells Microscopy Morphology Crystallization Perovskites

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From Circuits to SoC Processors: Arithmetic Approximation Techniques & Embedded Computing Methodologies for DSP Acceleration

arXiv

引用

arXiv 2023年

作者： Leon, Vasileios K. National Technical University of Athens School of Electrical and Computer Engineering Division of Computer Science Microprocessors and Digital Systems Laboratory 9 Heroon Polytechniou Zografou Campus Athens15780 Greece

The recent end of Dennard’s Scaling and the declining Moore’s Law have signified a new era for computing systems. Power efficiency has now become a critical factor for both cloud and edge computing. Concurrently, the rapid growth of compute-intensive applications from the digital Signal Processing (DSP) and Artificial Intelligence (AI) domains challenges the resources of computing systems. As a result, the computing industry is forced to find alternative design approaches and computing platforms to sustain increased power efficiency, while providing sufficient performance. Among the examined solutions, Approximate Computing, Hardware Acceleration, and Heterogeneous Computing have gained great momentum. Approximate Computing is a novel design paradigm that exploits the inherent error resilience of DSP/AI applications to deliver gains in power, area, and/or performance by reducing the quality of the results. Hardware Acceleration refers to the execution of demanding computational tasks on specialized hardware, such as the Application-Specific Integrated Circuits (ASICs) and the Field-Programmable Gate Arrays (FPGAs), rather than general-purpose processors. Finally, Heterogeneous Computing refers to versatile processing architectures, such as the Vision Processing Units (VPUs), which integrate more than one type of processor and various memory technologies. In this Dissertation, we introduce design solutions and methodologies, built on top of the preceding computing paradigms, for the development of energy-efficient DSP and AI accelerators. In particular, we adopt the promising paradigm of Approximate Computing and apply new approximation techniques in the design of arithmetic circuits. Based on our methodology, these arithmetic approximation techniques are then combined with hardware design techniques to implement approximate ASIC- and FPGA-based DSP and AI accelerators. Moreover, we propose methodologies for the efficient mapping of DSP/AI kernels on distinctive embe

关键词： digital signal processing

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