C. Kezi Selva Vijila, P. Kanagasabapathy, Stanly Johnson Jeyaraj, K. Rajasekaran
{"title":"利用人工智能技术消除feg干扰","authors":"C. Kezi Selva Vijila, P. Kanagasabapathy, Stanly Johnson Jeyaraj, K. Rajasekaran","doi":"10.1109/ICISIP.2006.4286090","DOIUrl":null,"url":null,"abstract":"In this paper, artificial intelligence like hybrid neuro fuzzy logic technique is proposed to cancel the major non-linear interference called maternal electrocardiogram for the extraction of fetal electrocardiogram (FECG). Conventional filtering techniques are not suitable due to an overlap in spectral content of the fetal and the interference. The performance evaluation of the proposed technique is done on the extracted fetal signal in terms of signal to noise ratio, mean square error, and number of membership functions, learning rates and processing time. Comparison is made between the proposed technique and the neural network. It shows that neuro fuzzy logic successfully cancels the interference in fetal electrocardiogram.","PeriodicalId":187104,"journal":{"name":"2006 Fourth International Conference on Intelligent Sensing and Information Processing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Interference Cancellation in FECG using Artificial Intelligence Techniques\",\"authors\":\"C. Kezi Selva Vijila, P. Kanagasabapathy, Stanly Johnson Jeyaraj, K. Rajasekaran\",\"doi\":\"10.1109/ICISIP.2006.4286090\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, artificial intelligence like hybrid neuro fuzzy logic technique is proposed to cancel the major non-linear interference called maternal electrocardiogram for the extraction of fetal electrocardiogram (FECG). Conventional filtering techniques are not suitable due to an overlap in spectral content of the fetal and the interference. The performance evaluation of the proposed technique is done on the extracted fetal signal in terms of signal to noise ratio, mean square error, and number of membership functions, learning rates and processing time. Comparison is made between the proposed technique and the neural network. It shows that neuro fuzzy logic successfully cancels the interference in fetal electrocardiogram.\",\"PeriodicalId\":187104,\"journal\":{\"name\":\"2006 Fourth International Conference on Intelligent Sensing and Information Processing\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 Fourth International Conference on Intelligent Sensing and Information Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICISIP.2006.4286090\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 Fourth International Conference on Intelligent Sensing and Information Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISIP.2006.4286090","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Interference Cancellation in FECG using Artificial Intelligence Techniques
In this paper, artificial intelligence like hybrid neuro fuzzy logic technique is proposed to cancel the major non-linear interference called maternal electrocardiogram for the extraction of fetal electrocardiogram (FECG). Conventional filtering techniques are not suitable due to an overlap in spectral content of the fetal and the interference. The performance evaluation of the proposed technique is done on the extracted fetal signal in terms of signal to noise ratio, mean square error, and number of membership functions, learning rates and processing time. Comparison is made between the proposed technique and the neural network. It shows that neuro fuzzy logic successfully cancels the interference in fetal electrocardiogram.