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dc.contributor.authorLin, Chin-Tengen_US
dc.contributor.authorLiu, Chi-Hsienen_US
dc.contributor.authorWang, Po-Shengen_US
dc.contributor.authorKing, Jung-Taien_US
dc.contributor.authorLiao, Lun-Deen_US
dc.date.accessioned2020-01-02T00:04:19Z-
dc.date.available2020-01-02T00:04:19Z-
dc.date.issued2019-11-01en_US
dc.identifier.urihttp://dx.doi.org/10.3390/mi10110720en_US
dc.identifier.urihttp://hdl.handle.net/11536/153369-
dc.description.abstractA brain-computer interface (BCI) is a type of interface/communication system that can help users interact with their environments. Electroencephalography (EEG) has become the most common application of BCIs and provides a way for disabled individuals to communicate. While wet sensors are the most commonly used sensors for traditional EEG measurements, they require considerable preparation time, including the time needed to prepare the skin and to use the conductive gel. Additionally, the conductive gel dries over time, leading to degraded performance. Furthermore, requiring patients to wear wet sensors to record EEG signals is considered highly inconvenient. Here, we report a wireless 8-channel digital active-circuit EEG signal acquisition system that uses dry sensors. Active-circuit systems for EEG measurement allow people to engage in daily life while using these systems, and the advantages of these systems can be further improved by utilizing dry sensors. Moreover, the use of dry sensors can help both disabled and healthy people enjoy the convenience of BCIs in daily life. To verify the reliability of the proposed system, we designed three experiments in which we evaluated eye blinking and teeth gritting, measured alpha waves, and recorded event-related potentials (ERPs) to compare our developed system with a standard Neuroscan EEG system.en_US
dc.language.isoen_USen_US
dc.subjectelectroencephalography (EEG)en_US
dc.subjectbrain-computer interface (BCI)en_US
dc.subjectdry sensoren_US
dc.subjectevent-related potential (ERP)en_US
dc.titleDesign and Verification of a Dry Sensor-Based Multi-Channel Digital Active Circuit for Human Brain Electroencephalography Signal Acquisition Systemsen_US
dc.typeArticleen_US
dc.identifier.doi10.3390/mi10110720en_US
dc.identifier.journalMICROMACHINESen_US
dc.citation.volume10en_US
dc.citation.issue11en_US
dc.citation.spage0en_US
dc.citation.epage0en_US
dc.contributor.department電控工程研究所zh_TW
dc.contributor.department腦科學研究中心zh_TW
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.contributor.departmentBrain Research Centeren_US
dc.identifier.wosnumberWOS:000502255300006en_US
dc.citation.woscount0en_US
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