Mrs. Mayuri Tushar Deshmukh, Dr. Shekhar R Suralkar
{"title":"基于机器学习的癫痫发作早期检测系统","authors":"Mrs. Mayuri Tushar Deshmukh, Dr. Shekhar R Suralkar","doi":"10.46335/ijies.2023.8.5.3","DOIUrl":null,"url":null,"abstract":"-An epileptic seizure is considered the most conspicuous neurological disorder nowadays that can distress to all ages, people.Around 6 decades million people all over the world are travail from epilepsy.Electroencephalograph (EEG) signals are most commonly used for the analysis and detection ofseizures.As EEG signal contains anenormous amount of clatterartifact-included information, so many researchers are trying to support automatic structures for completefeature extraction. This paper provides areview of popular seizure detection methods and performance analysis of the proposed K-Nearest neighbor (KNN), Support Vector Machine(SVM), and Regional Neural Network(RNN) algorithms.","PeriodicalId":286065,"journal":{"name":"International Journal of Innovations in Engineering and Science","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Early Detection System for Epileptic Seizures By Using Machine Learning\",\"authors\":\"Mrs. Mayuri Tushar Deshmukh, Dr. Shekhar R Suralkar\",\"doi\":\"10.46335/ijies.2023.8.5.3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"-An epileptic seizure is considered the most conspicuous neurological disorder nowadays that can distress to all ages, people.Around 6 decades million people all over the world are travail from epilepsy.Electroencephalograph (EEG) signals are most commonly used for the analysis and detection ofseizures.As EEG signal contains anenormous amount of clatterartifact-included information, so many researchers are trying to support automatic structures for completefeature extraction. This paper provides areview of popular seizure detection methods and performance analysis of the proposed K-Nearest neighbor (KNN), Support Vector Machine(SVM), and Regional Neural Network(RNN) algorithms.\",\"PeriodicalId\":286065,\"journal\":{\"name\":\"International Journal of Innovations in Engineering and Science\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Innovations in Engineering and Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.46335/ijies.2023.8.5.3\",\"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 Journal of Innovations in Engineering and Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46335/ijies.2023.8.5.3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Early Detection System for Epileptic Seizures By Using Machine Learning
-An epileptic seizure is considered the most conspicuous neurological disorder nowadays that can distress to all ages, people.Around 6 decades million people all over the world are travail from epilepsy.Electroencephalograph (EEG) signals are most commonly used for the analysis and detection ofseizures.As EEG signal contains anenormous amount of clatterartifact-included information, so many researchers are trying to support automatic structures for completefeature extraction. This paper provides areview of popular seizure detection methods and performance analysis of the proposed K-Nearest neighbor (KNN), Support Vector Machine(SVM), and Regional Neural Network(RNN) algorithms.