{"title":"一种自动脑电信号伪影检测与去除系统","authors":"Chenbei Zhang, Y. Lian, Guoxing Wang","doi":"10.1109/ICECS49266.2020.9294865","DOIUrl":null,"url":null,"abstract":"This paper presents an EEG artifacts detection and removal system (ARDER). It effectively removes several types of artifacts including ocular, muscle and transmission-line by utilizing a two-step approach: (1) identifying the type of artifact being presented, and (2) applying an appropriate technique to remove the detected artifact. Experiment results show the proposed system can preserve EEG information well while efficiently removing various artifacts.","PeriodicalId":404022,"journal":{"name":"2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"ARDER: An Automatic EEG Artifacts Detection and Removal System\",\"authors\":\"Chenbei Zhang, Y. Lian, Guoxing Wang\",\"doi\":\"10.1109/ICECS49266.2020.9294865\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an EEG artifacts detection and removal system (ARDER). It effectively removes several types of artifacts including ocular, muscle and transmission-line by utilizing a two-step approach: (1) identifying the type of artifact being presented, and (2) applying an appropriate technique to remove the detected artifact. Experiment results show the proposed system can preserve EEG information well while efficiently removing various artifacts.\",\"PeriodicalId\":404022,\"journal\":{\"name\":\"2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS)\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICECS49266.2020.9294865\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECS49266.2020.9294865","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ARDER: An Automatic EEG Artifacts Detection and Removal System
This paper presents an EEG artifacts detection and removal system (ARDER). It effectively removes several types of artifacts including ocular, muscle and transmission-line by utilizing a two-step approach: (1) identifying the type of artifact being presented, and (2) applying an appropriate technique to remove the detected artifact. Experiment results show the proposed system can preserve EEG information well while efficiently removing various artifacts.