{"title":"双正交小波在脑电信号压缩中的应用","authors":"A. Bousbia-Salah, M. A. Ait-Ameur, M. Kedir-Talha","doi":"10.1145/2093698.2093707","DOIUrl":null,"url":null,"abstract":"Compression of EEG signals is gaining importance in biomedical engineering due to the potential applications in telemedicine. In this paper, we propose a signal compression electro-encephalographic (EEG) method based on discrete wavelet transform (DWT). In order to do this, we developed an algorithm that makes the compression and recovery of these signals using the best suited method, the biorthogonal wavelet. The implementation of this algorithm on real signals (normal and pathological) gave satisfactory compression rates ranging from 65% to 90%, ensuring a good recovery.","PeriodicalId":91990,"journal":{"name":"... International Symposium on Applied Sciences in Biomedical and Communication Technologies. International Symposium on Applied Sciences in Biomedical and Communication Technologies","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Biorthogonal wavelet for EEG signal compression\",\"authors\":\"A. Bousbia-Salah, M. A. Ait-Ameur, M. Kedir-Talha\",\"doi\":\"10.1145/2093698.2093707\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Compression of EEG signals is gaining importance in biomedical engineering due to the potential applications in telemedicine. In this paper, we propose a signal compression electro-encephalographic (EEG) method based on discrete wavelet transform (DWT). In order to do this, we developed an algorithm that makes the compression and recovery of these signals using the best suited method, the biorthogonal wavelet. The implementation of this algorithm on real signals (normal and pathological) gave satisfactory compression rates ranging from 65% to 90%, ensuring a good recovery.\",\"PeriodicalId\":91990,\"journal\":{\"name\":\"... International Symposium on Applied Sciences in Biomedical and Communication Technologies. International Symposium on Applied Sciences in Biomedical and Communication Technologies\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-10-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"... International Symposium on Applied Sciences in Biomedical and Communication Technologies. International Symposium on Applied Sciences in Biomedical and Communication Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2093698.2093707\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"... International Symposium on Applied Sciences in Biomedical and Communication Technologies. International Symposium on Applied Sciences in Biomedical and Communication Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2093698.2093707","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Compression of EEG signals is gaining importance in biomedical engineering due to the potential applications in telemedicine. In this paper, we propose a signal compression electro-encephalographic (EEG) method based on discrete wavelet transform (DWT). In order to do this, we developed an algorithm that makes the compression and recovery of these signals using the best suited method, the biorthogonal wavelet. The implementation of this algorithm on real signals (normal and pathological) gave satisfactory compression rates ranging from 65% to 90%, ensuring a good recovery.
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