基于机器学习的焦虑脑电识别技术分析
Analysis of Anxiety EEG Recognition Technology Based on Machine Learning
邱江 1王在俊 1刘人杰1
作者信息
- 1. 中国民用航空飞行学院,四川 618300
- 折叠
摘要
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.
Abstract
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.
关键词
脑电信号/焦虑识别/数据处理/机器学习Key words
EEG signals/anxiety recognition/data processing/machine learning引用本文复制引用
出版年
2024
NETL
NSTL
万方数据