U. Ha, Yongsu Lee, Hyunki Kim, Taehwan Roh, Joonsung Bae, Changhyeon Kim, H. Yoo
{"title":"21.9可穿戴EEG-HEG-HRV多模态系统,实时tES监测,用于心理健康管理","authors":"U. Ha, Yongsu Lee, Hyunki Kim, Taehwan Roh, Joonsung Bae, Changhyeon Kim, H. Yoo","doi":"10.1109/ISSCC.2015.7063093","DOIUrl":null,"url":null,"abstract":"Recently, wearable mental health management systems have been actively studied based on EEG monitoring and transcranial electrical stimulation (tES) [1]. It was reported that mental activities cause neural, vascular and autonomie domain changes in the human brain [2]. However, the previous neurofeedback system [1] used only neural domain information with low spatial resolution (~10cm) EEG signals. Furthermore, EEG signals are easily interfered by tES stimulation signal, eye-blinking and EMG signals so that it is difficult to monitor in real-time during stimulation and to avoid electromagnetic noise for accurate mental health classification.","PeriodicalId":188403,"journal":{"name":"2015 IEEE International Solid-State Circuits Conference - (ISSCC) Digest of Technical Papers","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"21.9 A wearable EEG-HEG-HRV multimodal system with real-time tES monitoring for mental health management\",\"authors\":\"U. Ha, Yongsu Lee, Hyunki Kim, Taehwan Roh, Joonsung Bae, Changhyeon Kim, H. Yoo\",\"doi\":\"10.1109/ISSCC.2015.7063093\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recently, wearable mental health management systems have been actively studied based on EEG monitoring and transcranial electrical stimulation (tES) [1]. It was reported that mental activities cause neural, vascular and autonomie domain changes in the human brain [2]. However, the previous neurofeedback system [1] used only neural domain information with low spatial resolution (~10cm) EEG signals. Furthermore, EEG signals are easily interfered by tES stimulation signal, eye-blinking and EMG signals so that it is difficult to monitor in real-time during stimulation and to avoid electromagnetic noise for accurate mental health classification.\",\"PeriodicalId\":188403,\"journal\":{\"name\":\"2015 IEEE International Solid-State Circuits Conference - (ISSCC) Digest of Technical Papers\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-03-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE International Solid-State Circuits Conference - (ISSCC) Digest of Technical Papers\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSCC.2015.7063093\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Solid-State Circuits Conference - (ISSCC) Digest of Technical Papers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSCC.2015.7063093","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
21.9 A wearable EEG-HEG-HRV multimodal system with real-time tES monitoring for mental health management
Recently, wearable mental health management systems have been actively studied based on EEG monitoring and transcranial electrical stimulation (tES) [1]. It was reported that mental activities cause neural, vascular and autonomie domain changes in the human brain [2]. However, the previous neurofeedback system [1] used only neural domain information with low spatial resolution (~10cm) EEG signals. Furthermore, EEG signals are easily interfered by tES stimulation signal, eye-blinking and EMG signals so that it is difficult to monitor in real-time during stimulation and to avoid electromagnetic noise for accurate mental health classification.