國家衛生研究院 NHRI:Item 3990099045/12348

NHRI > Institute of Biomedical Engineering and Nanomedicine > Lun-De Liao > Periodical Articles > Item 3990099045/12348

Please use this identifier to cite or link to this item: http://ir.nhri.org.tw/handle/3990099045/12348

Title:	Design and verification of a dry sensor-based multi-channel digital active circuit for human brain electroencephalography signal acquisition systems
Authors:	Lin, CT;Liu, CH;Wang, PS;King, JT;Liao, LD
Contributors:	Institute of Biomedical Engineering and Nanomedicine
Abstract:	A 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.
Date:	2019-10-25
Relation:	Micromachines. 2019 Oct 25;10(11):Article number 720.
Link to:	http://dx.doi.org/10.3390/mi10110720
JIF/Ranking 2023:	http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=2072-666X&DestApp=IC2JCR
Cited Times(WOS):	https://www.webofscience.com/wos/woscc/full-record/WOS:000502255300006
Cited Times(Scopus):	https://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85075574505
Appears in Collections:	[Lun-De Liao] Periodical Articles

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