CN106388814A - 基于最优核时频分布可视图的癫痫脑电信号识别方法 - Google Patents
基于最优核时频分布可视图的癫痫脑电信号识别方法 Download PDFInfo
- Publication number
- CN106388814A CN106388814A CN201610887682.1A CN201610887682A CN106388814A CN 106388814 A CN106388814 A CN 106388814A CN 201610887682 A CN201610887682 A CN 201610887682A CN 106388814 A CN106388814 A CN 106388814A
- Authority
- CN
- China
- Prior art keywords
- time
- optimal kernel
- frequency distributions
- adaptive optimal
- indicator vector
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/369—Electroencephalography [EEG]
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/40—Detecting, measuring or recording for evaluating the nervous system
- A61B5/4076—Diagnosing or monitoring particular conditions of the nervous system
- A61B5/4094—Diagnosing or monitoring seizure diseases, e.g. epilepsy
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7203—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/725—Details of waveform analysis using specific filters therefor, e.g. Kalman or adaptive filters
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Public Health (AREA)
- Surgery (AREA)
- Veterinary Medicine (AREA)
- General Health & Medical Sciences (AREA)
- Animal Behavior & Ethology (AREA)
- Biophysics (AREA)
- Pathology (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Molecular Biology (AREA)
- Psychiatry (AREA)
- Physiology (AREA)
- Artificial Intelligence (AREA)
- Signal Processing (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Neurology (AREA)
- Neurosurgery (AREA)
- Evolutionary Computation (AREA)
- Fuzzy Systems (AREA)
- Mathematical Physics (AREA)
- Psychology (AREA)
- Complex Calculations (AREA)
Abstract
Description
Claims (3)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201610887682.1A CN106388814B (zh) | 2016-10-11 | 2016-10-11 | 基于最优核时频分布可视图的癫痫脑电信号识别方法 |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201610887682.1A CN106388814B (zh) | 2016-10-11 | 2016-10-11 | 基于最优核时频分布可视图的癫痫脑电信号识别方法 |
Publications (2)
Publication Number | Publication Date |
---|---|
CN106388814A true CN106388814A (zh) | 2017-02-15 |
CN106388814B CN106388814B (zh) | 2019-06-18 |
Family
ID=59229630
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201610887682.1A Active CN106388814B (zh) | 2016-10-11 | 2016-10-11 | 基于最优核时频分布可视图的癫痫脑电信号识别方法 |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN106388814B (zh) |
Cited By (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106909784A (zh) * | 2017-02-24 | 2017-06-30 | 天津大学 | 基于二维时频图像深度卷积神经网络的癫痫脑电识别方法 |
CN106991409A (zh) * | 2017-04-14 | 2017-07-28 | 山东建筑大学 | 一种运动想象脑电信号特征提取与分类***及方法 |
CN107423668A (zh) * | 2017-04-14 | 2017-12-01 | 山东建筑大学 | 基于小波变换和稀疏表达的脑电信号分类***与方法 |
CN107616793A (zh) * | 2017-09-18 | 2018-01-23 | 电子科技大学 | 一种具有癫痫发作预测功能的脑电监测装置及方法 |
CN108446020A (zh) * | 2018-02-28 | 2018-08-24 | 天津大学 | 融合可视图与深度学习的运动想象意念控制方法及应用 |
CN108960037A (zh) * | 2018-04-28 | 2018-12-07 | 天津大学 | 基于邻居可视长度熵的不同生理状态脑电信号识别方法 |
CN109634405A (zh) * | 2018-11-07 | 2019-04-16 | 湖北汽车工业学院 | 一种基于脑电信号的情绪分类方法、装置和存储介质 |
CN110367933A (zh) * | 2019-07-15 | 2019-10-25 | 天津大学 | 基于复杂网络和深度学习的睡眠阶段分类方法及应用 |
CN110584596A (zh) * | 2019-07-15 | 2019-12-20 | 天津大学 | 基于双输入卷积神经网络的睡眠阶段分类方法及应用 |
CN111543946A (zh) * | 2020-05-08 | 2020-08-18 | 南京邮电大学 | 基于改进变分模态分解算法的癫痫脑电信号自动检测方法 |
CN113288050A (zh) * | 2021-04-23 | 2021-08-24 | 山东师范大学 | 基于图卷积网络的多维增强癫痫发作预测*** |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103110418A (zh) * | 2013-01-24 | 2013-05-22 | 天津大学 | 一种脑电信号特征提取方法 |
CN105467446A (zh) * | 2014-09-04 | 2016-04-06 | 中国石油化工股份有限公司 | 基于径向高斯核的自适应最优核时频分析方法 |
-
2016
- 2016-10-11 CN CN201610887682.1A patent/CN106388814B/zh active Active
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103110418A (zh) * | 2013-01-24 | 2013-05-22 | 天津大学 | 一种脑电信号特征提取方法 |
CN105467446A (zh) * | 2014-09-04 | 2016-04-06 | 中国石油化工股份有限公司 | 基于径向高斯核的自适应最优核时频分析方法 |
Non-Patent Citations (1)
Title |
---|
韩敏 等: "基于自回归模型和关联向量机的癫痫脑电信号自动分类", 《中国生物医学工程学报》 * |
Cited By (16)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106909784B (zh) * | 2017-02-24 | 2019-05-10 | 天津大学 | 基于二维时频图像深度卷积神经网络的癫痫脑电识别装置 |
CN106909784A (zh) * | 2017-02-24 | 2017-06-30 | 天津大学 | 基于二维时频图像深度卷积神经网络的癫痫脑电识别方法 |
CN106991409A (zh) * | 2017-04-14 | 2017-07-28 | 山东建筑大学 | 一种运动想象脑电信号特征提取与分类***及方法 |
CN107423668A (zh) * | 2017-04-14 | 2017-12-01 | 山东建筑大学 | 基于小波变换和稀疏表达的脑电信号分类***与方法 |
CN106991409B (zh) * | 2017-04-14 | 2020-03-27 | 山东建筑大学 | 一种运动想象脑电信号特征提取与分类***及方法 |
CN107616793A (zh) * | 2017-09-18 | 2018-01-23 | 电子科技大学 | 一种具有癫痫发作预测功能的脑电监测装置及方法 |
CN108446020B (zh) * | 2018-02-28 | 2021-01-08 | 天津大学 | 融合可视图与深度学习的运动想象意念控制方法及应用 |
CN108446020A (zh) * | 2018-02-28 | 2018-08-24 | 天津大学 | 融合可视图与深度学习的运动想象意念控制方法及应用 |
CN108960037A (zh) * | 2018-04-28 | 2018-12-07 | 天津大学 | 基于邻居可视长度熵的不同生理状态脑电信号识别方法 |
CN108960037B (zh) * | 2018-04-28 | 2021-08-06 | 天津大学 | 基于邻居可视长度熵的不同生理状态脑电信号识别方法 |
CN109634405A (zh) * | 2018-11-07 | 2019-04-16 | 湖北汽车工业学院 | 一种基于脑电信号的情绪分类方法、装置和存储介质 |
CN110367933A (zh) * | 2019-07-15 | 2019-10-25 | 天津大学 | 基于复杂网络和深度学习的睡眠阶段分类方法及应用 |
CN110584596A (zh) * | 2019-07-15 | 2019-12-20 | 天津大学 | 基于双输入卷积神经网络的睡眠阶段分类方法及应用 |
CN110584596B (zh) * | 2019-07-15 | 2022-05-27 | 天津大学 | 基于双输入卷积神经网络的睡眠阶段分类方法及应用 |
CN111543946A (zh) * | 2020-05-08 | 2020-08-18 | 南京邮电大学 | 基于改进变分模态分解算法的癫痫脑电信号自动检测方法 |
CN113288050A (zh) * | 2021-04-23 | 2021-08-24 | 山东师范大学 | 基于图卷积网络的多维增强癫痫发作预测*** |
Also Published As
Publication number | Publication date |
---|---|
CN106388814B (zh) | 2019-06-18 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN106388814A (zh) | 基于最优核时频分布可视图的癫痫脑电信号识别方法 | |
CN106473736A (zh) | 基于复杂网络的脑电信号分析方法及应用 | |
US20200367800A1 (en) | Method for identifying driving fatigue based on cnn-lstm deep learning model | |
CN106108894A (zh) | 一种提高情绪识别模型时间鲁棒性的情绪脑电识别方法 | |
CN112381008B (zh) | 一种基于并行序列通道映射网络的脑电情感识别方法 | |
CN110070105B (zh) | 基于元学习实例快速筛选的脑电情绪识别方法、*** | |
CN104720796B (zh) | 一种用于癫痫发作时间段的自动检测***及方法 | |
CN106974621B (zh) | 一种基于脑电信号重心频率的视觉诱导晕动症检测方法 | |
CN104586387A (zh) | 一种时、频、空域多参数脑电特征提取与融合方法 | |
CN110432898A (zh) | 一种基于非线性动力学特征的癫痫发作脑电信号分类*** | |
CN107811626A (zh) | 一种基于一维卷积神经网络和s变换的心律失常分类方法 | |
CN105894039A (zh) | 情绪识别模型建立方法、情绪识别方法及装置、智能设备 | |
CN111000555B (zh) | 一种癫痫脑电信号的训练数据生成方法、自动识别模型建模方法和自动识别方法 | |
CN106529476A (zh) | 一种基于深层堆叠网络的脑电信号特征提取及分类方法 | |
CN110321783A (zh) | 一种基于1d卷积神经网络的meg棘波检测方法及*** | |
CN106725452A (zh) | 基于情感诱发的脑电信号识别方法 | |
Wang et al. | A novel multi-scale dilated 3D CNN for epileptic seizure prediction | |
CN107714057A (zh) | 一种基于卷积神经网络的三分类情绪识别模型方法 | |
CN106264499A (zh) | 一种量化心肺***交互作用的分析方法 | |
CN104970790A (zh) | 一种运动想象脑电波解析方法 | |
CN114532993B (zh) | 一种癫痫患者脑电高频振荡信号的自动检测方法 | |
CN114925734B (zh) | 一种基于神经拟态计算的在线神经元分类方法 | |
CN112732092B (zh) | 基于双视图多尺度卷积神经网络的表面肌电信号识别方法 | |
Gerla et al. | Automatic identification of artifacts and unwanted physiologic signals in EEG and EOG during wakefulness | |
CN108509869A (zh) | 基于OpenBCI的特征集优化在线训练方法 |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant | ||
TR01 | Transfer of patent right | ||
TR01 | Transfer of patent right |
Effective date of registration: 20201231 Address after: No.4, Keji Avenue, Daqiuzhuang Industrial Park, Jinghai District, Tianjin Patentee after: TIANJIN FURUILONG METAL PRODUCTS Co.,Ltd. Address before: 300072 Tianjin City, Nankai District Wei Jin Road No. 92 Patentee before: Tianjin University |
|
TR01 | Transfer of patent right | ||
TR01 | Transfer of patent right |
Effective date of registration: 20210915 Address after: 300000 2301, Vanke times center, building 1, Huike building, the intersection of Anshan West Road and Baidi Road, Nankai District, Tianjin Patentee after: Junsheng (Tianjin) Technology Development Co.,Ltd. Address before: No.4, Keji Avenue, Daqiuzhuang Industrial Park, Jinghai District, Tianjin Patentee before: TIANJIN FURUILONG METAL PRODUCTS Co.,Ltd. |