U. Ha, Yongsu Lee, Hyunki Kim, Taehwan Roh, Joonsung Bae, Changhyeon Kim, H. Yoo
{"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}
引用次数: 11
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.