{"title":"利用 SSVEP 脑机接口构建和评估电话拨号系统","authors":"Jinsha Liu, Boning Li, Jianting Cao","doi":"10.24297/ijct.v23i.9539","DOIUrl":null,"url":null,"abstract":"This study presents a SSVEP based BCI system, designed for dialing a phone number through EEG signals. Our SSVEP system leverages a tablet-based stimulator and OpenBCI Cyton board, employing Canonical Correlation Analysis for EEG signal classification. Tested on 7 participants, the system demonstrated a high accuracy rate of 98.1% in identifying the observed keys. The use of a tablet-based SSVEP stimulator was found to reduce visual fatigue compared to traditional LED stimulators. Despite its initial success, further validation with a larger cohort and in varied real-world conditions is required. This work signifies a promising advancement in utilizing BCIs in practical applications.","PeriodicalId":210853,"journal":{"name":"INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY","volume":"5 7","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Construct and Evaluate a Phone Dialing System Leveraging SSVEP Brain-Computer Interface\",\"authors\":\"Jinsha Liu, Boning Li, Jianting Cao\",\"doi\":\"10.24297/ijct.v23i.9539\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study presents a SSVEP based BCI system, designed for dialing a phone number through EEG signals. Our SSVEP system leverages a tablet-based stimulator and OpenBCI Cyton board, employing Canonical Correlation Analysis for EEG signal classification. Tested on 7 participants, the system demonstrated a high accuracy rate of 98.1% in identifying the observed keys. The use of a tablet-based SSVEP stimulator was found to reduce visual fatigue compared to traditional LED stimulators. Despite its initial success, further validation with a larger cohort and in varied real-world conditions is required. This work signifies a promising advancement in utilizing BCIs in practical applications.\",\"PeriodicalId\":210853,\"journal\":{\"name\":\"INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY\",\"volume\":\"5 7\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-11-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24297/ijct.v23i.9539\",\"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 COMPUTERS & TECHNOLOGY","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24297/ijct.v23i.9539","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Construct and Evaluate a Phone Dialing System Leveraging SSVEP Brain-Computer Interface
This study presents a SSVEP based BCI system, designed for dialing a phone number through EEG signals. Our SSVEP system leverages a tablet-based stimulator and OpenBCI Cyton board, employing Canonical Correlation Analysis for EEG signal classification. Tested on 7 participants, the system demonstrated a high accuracy rate of 98.1% in identifying the observed keys. The use of a tablet-based SSVEP stimulator was found to reduce visual fatigue compared to traditional LED stimulators. Despite its initial success, further validation with a larger cohort and in varied real-world conditions is required. This work signifies a promising advancement in utilizing BCIs in practical applications.