首页|基于机器学习的焦虑脑电识别技术分析

基于机器学习的焦虑脑电识别技术分析

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阐述基于机器学习的焦虑脑电状态识别,需要对数据采集和预处理.在焦虑脑电状态识别中,脑电信号特征通常从五个波段中提取,机器学习算法会使用这些频谱特征来区分焦虑和非焦虑状态.
Analysis of Anxiety EEG Recognition Technology Based on Machine Learning
This paper describes machine learning based anxiety EEG state recognition,which requires data collection and preprocessing.In the recognition of anxious EEG states,EEG signal features are usually extracted from five bands,and machine learning algorithms use these spectral features to distinguish between anxious and non anxious states.

EEG signalsanxiety recognitiondata processingmachine learning

邱江、王在俊、刘人杰

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中国民用航空飞行学院,四川 618300

脑电信号 焦虑识别 数据处理 机器学习

2024

电子技术
上海市电子学会,上海市通信学会

电子技术

影响因子:0.296
ISSN:1000-0755
年,卷(期):2024.53(1)
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