{"title":"利用脑电图信号进行生物特征识别及控制电子设备","authors":"Ms.S.Anitha Jebamani, M. Ragavi, K. Nivetha.","doi":"10.1109/ICNWC57852.2023.10127259","DOIUrl":null,"url":null,"abstract":"The direct link between computer systems and the human brain is known as a “brain computer interface,” or BCI. The BCI reads the waves composed of the brain at exclusive places inside the human head, translates those indicators into movements and instructions,which can control the computer systems. We endorse combining this generation with home automation. This interface device is especially helpful for people who are severely disabled or confined and lack reliable muscular control over the parts of their bodies that are engaged with surrounding peripherals. The machine entails two components: an EEG sensor circuit and Arduino microcontroller board. The mind waves are captured using electrodes. These indicators are filtered and amplified to take away noise. These analog signs are converted to digital. The digital alerts are decoded and are used to exchange on a device","PeriodicalId":197525,"journal":{"name":"2023 International Conference on Networking and Communications (ICNWC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Biometric Recognition Using EEG Signals And Controlling The Electrical Devices\",\"authors\":\"Ms.S.Anitha Jebamani, M. Ragavi, K. Nivetha.\",\"doi\":\"10.1109/ICNWC57852.2023.10127259\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The direct link between computer systems and the human brain is known as a “brain computer interface,” or BCI. The BCI reads the waves composed of the brain at exclusive places inside the human head, translates those indicators into movements and instructions,which can control the computer systems. We endorse combining this generation with home automation. This interface device is especially helpful for people who are severely disabled or confined and lack reliable muscular control over the parts of their bodies that are engaged with surrounding peripherals. The machine entails two components: an EEG sensor circuit and Arduino microcontroller board. The mind waves are captured using electrodes. These indicators are filtered and amplified to take away noise. These analog signs are converted to digital. The digital alerts are decoded and are used to exchange on a device\",\"PeriodicalId\":197525,\"journal\":{\"name\":\"2023 International Conference on Networking and Communications (ICNWC)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Conference on Networking and Communications (ICNWC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNWC57852.2023.10127259\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Networking and Communications (ICNWC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNWC57852.2023.10127259","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Biometric Recognition Using EEG Signals And Controlling The Electrical Devices
The direct link between computer systems and the human brain is known as a “brain computer interface,” or BCI. The BCI reads the waves composed of the brain at exclusive places inside the human head, translates those indicators into movements and instructions,which can control the computer systems. We endorse combining this generation with home automation. This interface device is especially helpful for people who are severely disabled or confined and lack reliable muscular control over the parts of their bodies that are engaged with surrounding peripherals. The machine entails two components: an EEG sensor circuit and Arduino microcontroller board. The mind waves are captured using electrodes. These indicators are filtered and amplified to take away noise. These analog signs are converted to digital. The digital alerts are decoded and are used to exchange on a device