CN107157477B - 脑电信号特征识别系统及方法 - Google Patents
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- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
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- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
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Abstract
Description
导联数 | Total(%) | Delta(%) | Theta(%) | Alpha(%) | Beta(%) | Gamma(%) |
4导 | 69.79 | 42.09 | 44.21 | 53.52 | 53.44 | 56.82 |
6导 | 69.83 | 54.76 | 52.27 | 59.79 | 69.17 | 72.01 |
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CN108171009A (zh) * | 2017-12-21 | 2018-06-15 | 东南大学 | 基于二维自回归模型参数估计的脑电信号间因果关系检测方法 |
CN108236464B (zh) * | 2017-12-29 | 2021-02-23 | 重庆邮电大学 | 基于脑电信号的特征提取方法及其检测提取系统 |
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CN109222966A (zh) * | 2018-10-09 | 2019-01-18 | 山东大学 | 一种基于变分自编码器的脑电信号情感分类方法 |
CN109271964B (zh) * | 2018-10-11 | 2021-04-23 | 刘仕琪 | 基于深度学习模型与长短记忆网络的情绪识别方法及系统 |
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CN114533062B (zh) * | 2022-01-14 | 2024-04-23 | 中国人民解放军火箭军工程大学 | 基于微分熵和二叉树支持向量机的脑疲劳检测方法及装置 |
CN114081494B (zh) * | 2022-01-21 | 2022-05-06 | 浙江大学 | 一种基于大脑外侧缰核信号的抑郁状态检测系统 |
CN114403902A (zh) * | 2022-03-30 | 2022-04-29 | 中山大学 | 一种脑网络连通性的检测方法和装置 |
CN114469095A (zh) * | 2022-04-19 | 2022-05-13 | 之江实验室 | 基于脑电非线性特征的注意偏向训练效果评估方法及系统 |
CN117462148B (zh) * | 2023-12-28 | 2024-05-14 | 慧创科仪(北京)科技有限公司 | 一种用于脑电检测设备的导联配置装置、方法和存储介质 |
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CN103340624A (zh) * | 2013-07-22 | 2013-10-09 | 上海交通大学 | 少通道下运动想象脑电特征的提取方法 |
CN103690165A (zh) * | 2013-12-12 | 2014-04-02 | 天津大学 | 一种跨诱发模式情绪脑电识别建模方法 |
CN105894039A (zh) * | 2016-04-25 | 2016-08-24 | 京东方科技集团股份有限公司 | 情绪识别模型建立方法、情绪识别方法及装置、智能设备 |
WO2017064826A1 (ja) * | 2015-10-16 | 2017-04-20 | 国立大学法人広島大学 | 感性評価方法 |
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CN102715911A (zh) * | 2012-06-15 | 2012-10-10 | 天津大学 | 基于脑电特征的情绪状态识别方法 |
CN103340624A (zh) * | 2013-07-22 | 2013-10-09 | 上海交通大学 | 少通道下运动想象脑电特征的提取方法 |
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