• DocumentCode
    2065408
  • Title

    21.9 A wearable EEG-HEG-HRV multimodal system with real-time tES monitoring for mental health management

  • Author

    Unsoo Ha ; Yongsu Lee ; Hyunki Kim ; Taehwan Roh ; Joonsung Bae ; Changhyeon Kim ; Hoi-Jun Yoo

  • Author_Institution
    KAIST, Daejeon, South Korea
  • fYear
    2015
  • fDate
    22-26 Feb. 2015
  • Firstpage
    1
  • Lastpage
    3
  • 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.
  • Keywords
    bioelectric potentials; biomedical equipment; blood; blood vessels; electroencephalography; electromagnetic interference; feedback; neurophysiology; noise; patient monitoring; patient treatment; real-time systems; EEG monitoring; EEG signals interference; EMG signal; autonomie domain change; electromagnetic noise; eye-blinking; human brain; mental activity; mental health classification accuracy; neural domain change; neural domain information; neurofeedback system; real-time monitoring; real-time tES monitoring; spatial resolution; tES stimulation signal; transcranial electrical stimulation; vascular domain change; wearable EEG-HEG-HRV multimodal system; wearable mental health management system; Biomedical monitoring; Current measurement; Electrodes; Electroencephalography; Heart rate variability; Monitoring; Real-time systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Solid- State Circuits Conference - (ISSCC), 2015 IEEE International
  • Conference_Location
    San Francisco, CA
  • Print_ISBN
    978-1-4799-6223-5
  • Type

    conf

  • DOI
    10.1109/ISSCC.2015.7063093
  • Filename
    7063093