{"title":"小波变换在口腔沟通障碍患者脑电信号分析中的应用","authors":"María Viqueira, B. G. Zapirain, A. M. Zorrilla","doi":"10.1109/ISSPIT.2011.6151549","DOIUrl":null,"url":null,"abstract":"This chapter presents a system for helping people who can't talk or control their movements when communication by speech. The system is based on applying the wavelet transform to EEG signals. In this study it has been used the 64 channels to know in which ones of them exists higher difference between the P300b and the P300a, in order to chose the best four channels that will be used in the application. The results have achieved a 80% success using the bior3.7 the wavelet.","PeriodicalId":288042,"journal":{"name":"2011 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Wavelet Transform for the analysis of EEG signals in patients with oral communications problems\",\"authors\":\"María Viqueira, B. G. Zapirain, A. M. Zorrilla\",\"doi\":\"10.1109/ISSPIT.2011.6151549\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This chapter presents a system for helping people who can't talk or control their movements when communication by speech. The system is based on applying the wavelet transform to EEG signals. In this study it has been used the 64 channels to know in which ones of them exists higher difference between the P300b and the P300a, in order to chose the best four channels that will be used in the application. The results have achieved a 80% success using the bior3.7 the wavelet.\",\"PeriodicalId\":288042,\"journal\":{\"name\":\"2011 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)\",\"volume\":\"69 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSPIT.2011.6151549\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSPIT.2011.6151549","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Wavelet Transform for the analysis of EEG signals in patients with oral communications problems
This chapter presents a system for helping people who can't talk or control their movements when communication by speech. The system is based on applying the wavelet transform to EEG signals. In this study it has been used the 64 channels to know in which ones of them exists higher difference between the P300b and the P300a, in order to chose the best four channels that will be used in the application. The results have achieved a 80% success using the bior3.7 the wavelet.