{"title":"脑电信号分析研究进展","authors":"Jasjeet Kaur, Amanpreet Kaur","doi":"10.1109/ICACEA.2015.7164844","DOIUrl":null,"url":null,"abstract":"Electroencephalography (EEG) enlighten about the state of the brain i.e. about the electrical bustle going on in the brain. The electrical activity measured as voltage at different points of brain act as basis of EEG. These signals are generally time-varying and non-stationary in nature. These signals can be scrutinized using various signal processing techniques. In this paper, few statistical approaches to analyze EEG data are conversed.","PeriodicalId":202893,"journal":{"name":"2015 International Conference on Advances in Computer Engineering and Applications","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":"{\"title\":\"A review on analysis of EEG signals\",\"authors\":\"Jasjeet Kaur, Amanpreet Kaur\",\"doi\":\"10.1109/ICACEA.2015.7164844\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Electroencephalography (EEG) enlighten about the state of the brain i.e. about the electrical bustle going on in the brain. The electrical activity measured as voltage at different points of brain act as basis of EEG. These signals are generally time-varying and non-stationary in nature. These signals can be scrutinized using various signal processing techniques. In this paper, few statistical approaches to analyze EEG data are conversed.\",\"PeriodicalId\":202893,\"journal\":{\"name\":\"2015 International Conference on Advances in Computer Engineering and Applications\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-03-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"27\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Advances in Computer Engineering and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICACEA.2015.7164844\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Advances in Computer Engineering and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACEA.2015.7164844","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Electroencephalography (EEG) enlighten about the state of the brain i.e. about the electrical bustle going on in the brain. The electrical activity measured as voltage at different points of brain act as basis of EEG. These signals are generally time-varying and non-stationary in nature. These signals can be scrutinized using various signal processing techniques. In this paper, few statistical approaches to analyze EEG data are conversed.