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

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

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Electroencephalography(EEG)is a non-invasive measurement method for brain activity.Due to its safety,high resolution,and hypersensitivity to dynamic changes in brain neural signals,EEG has aroused much interest in scientific research and medical felds.This 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 diseases.First,3 types of EEG signals,including time-invariant EEG,accurate event-related EEG,and random event-related EEG,are introduced.Second,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 problem.Finally,the application scenarios of different EEG analysis methods are emphasized,and the advantages and disadvantages of similar methods are distinguished.This 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.

Electroencephalogram analysis methodsApplied principlesNeuroscienceDiagnosisNeurological diseases

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

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School of Systems Science,Beijing Normal University,Beijing 100875,China

College of Electrical and Control Engineering,North China University of Technology,Beijing 100041,China

School of Automation Science and Engineering,South China University of Technology,Guangzhou 510641,China

Department of Psychology,the State Key Laboratory of Brain and Cognitive Sciences,the University of Hong Kong,Hong Kong SAR 999077,China

HKU-Shenzhen Institute of Research and Innovation,Shenzhen 518057,Guangdong,China

Department of Health Technology and Informatics,the Hong Kong Polytechnic University,Hong Kong SAR 999077,China

Department of Rehabilitation Medicine,the First Afliated Hospital of Nanchang University,Nanchang 330006,China

Rehabilitation Medicine Clinical Research Center of Jiangxi Province,Nanchang 330006,China

Beijing Key Laboratory of Learning and Cognition,School of Psychology,Capital Normal University,Beijing 100048,China

School of Communication Science,Beijing Language and Culture University,Beijing 100083,China

Institute of Electrical Engineering,Yanshan University,Qinhuangdao 066004,Hebei,China

School of Computer Science,Wuhan University,Wuhan 430072,China

School of Biomedical Engineering,Faculty of Electronic Information and Electrical Engineering,Dalian University of Technology,Dalian 116081,Liaoning,China

Guangdong Artifcial Intelligence and Digital Economy Laboratory(Guangzhou),Guangzhou 510335,China

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2024

10.1186/s40779-023-00502-7

军事医学研究(英文)

军事医学研究(英文)

CSTPCD
ISSN：2095-7467
年,卷(期)：2024.11(6)