{"title":"一种基于EMD的呼吸暂停和正常脑电图信号识别方法","authors":"S. Yadav, V. Bajaj, Anil Kumar","doi":"10.1109/RISE.2017.8378152","DOIUrl":null,"url":null,"abstract":"Sleep apnea is a type of sleep syndrome and is caused due to breaks or pause during sleep. A new technique is used in this paper for the discrimination between apnea and normal sleep electroencephalogram (EEG) signals. Here, the empirical mode decomposition (EMD) method is used for the discrimination purpose of apnea and normal sleep EEG signals. In EMD method, EEG signal (which may be non-linear or non-stationary in nature) has been decomposed into oscillatory functions known as intrinsic mode functions (IMFs). After decomposition of EEG signals, two important features termed as energy and entropy has been extracted. These features help in discrimination process of EEG signals.","PeriodicalId":166244,"journal":{"name":"2017 International Conference on Recent Innovations in Signal processing and Embedded Systems (RISE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An EMD based approach for discrimination of apnea and normal EEG signals\",\"authors\":\"S. Yadav, V. Bajaj, Anil Kumar\",\"doi\":\"10.1109/RISE.2017.8378152\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Sleep apnea is a type of sleep syndrome and is caused due to breaks or pause during sleep. A new technique is used in this paper for the discrimination between apnea and normal sleep electroencephalogram (EEG) signals. Here, the empirical mode decomposition (EMD) method is used for the discrimination purpose of apnea and normal sleep EEG signals. In EMD method, EEG signal (which may be non-linear or non-stationary in nature) has been decomposed into oscillatory functions known as intrinsic mode functions (IMFs). After decomposition of EEG signals, two important features termed as energy and entropy has been extracted. These features help in discrimination process of EEG signals.\",\"PeriodicalId\":166244,\"journal\":{\"name\":\"2017 International Conference on Recent Innovations in Signal processing and Embedded Systems (RISE)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Recent Innovations in Signal processing and Embedded Systems (RISE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RISE.2017.8378152\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Recent Innovations in Signal processing and Embedded Systems (RISE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RISE.2017.8378152","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An EMD based approach for discrimination of apnea and normal EEG signals
Sleep apnea is a type of sleep syndrome and is caused due to breaks or pause during sleep. A new technique is used in this paper for the discrimination between apnea and normal sleep electroencephalogram (EEG) signals. Here, the empirical mode decomposition (EMD) method is used for the discrimination purpose of apnea and normal sleep EEG signals. In EMD method, EEG signal (which may be non-linear or non-stationary in nature) has been decomposed into oscillatory functions known as intrinsic mode functions (IMFs). After decomposition of EEG signals, two important features termed as energy and entropy has been extracted. These features help in discrimination process of EEG signals.