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    Dry Electrode Based Wearable Wireless Brain–Computer Interface System

    Source: Journal of Nanotechnology in Engineering and Medicine:;2011:;volume( 002 ):;issue: 003::page 31007
    Author:
    Wang Yu
    ,
    Xu Bing
    ,
    Gui Qiang
    ,
    Guo Kai
    ,
    Pei WeiHua
    ,
    Liu Jian
    ,
    Chen HongDa
    DOI: 10.1115/1.4005487
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Brain–computer interface (BCI) technology is a key issue in neural engineering, which can manipulate machine by electroencephalography (EEG). An important question surrounding the use of the BCI is the design of a wearable electroencephalography recording and processing equipment. We report the design and fabrication of a novel system based on dry electrodes, in which skin preparation and application of electrolytic gel are not required. In this study, an EEG-based BCI system, which includes a wireless transmitter module and an receiver module was designed, EEG is acquired using dry electrodes, amplified and processed by an application-specific integrated circuit (ASIC), and transmitted to the receiver by RF chip. The BCI system can obtain the subject’s degree of concentration, and those trained subjects have the ability of controlling the machine by changing their EEG signals. A experiment that controlling a toy car using the BCI system is successfully performed. The wearable transmitter module weighs 39 g only and easy to wear. The transmitter consumes 60 mW of dc power and generates an output power of 0 dBm. The BCI system is suitable for long-term EEG monitoring in users’ daily life. This system is feasible for further extension.
    keyword(s): Electrodes , Computers , Brain , Electroencephalography , Signals AND Manufacturing ,
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      Dry Electrode Based Wearable Wireless Brain–Computer Interface System

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    http://yetl.yabesh.ir/yetl1/handle/yetl/147298
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    contributor authorWang Yu
    contributor authorXu Bing
    contributor authorGui Qiang
    contributor authorGuo Kai
    contributor authorPei WeiHua
    contributor authorLiu Jian
    contributor authorChen HongDa
    date accessioned2017-05-09T00:46:16Z
    date available2017-05-09T00:46:16Z
    date copyrightAugust, 2011
    date issued2011
    identifier issn1949-2944
    identifier otherJNEMAA-28064#031007_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/147298
    description abstractBrain–computer interface (BCI) technology is a key issue in neural engineering, which can manipulate machine by electroencephalography (EEG). An important question surrounding the use of the BCI is the design of a wearable electroencephalography recording and processing equipment. We report the design and fabrication of a novel system based on dry electrodes, in which skin preparation and application of electrolytic gel are not required. In this study, an EEG-based BCI system, which includes a wireless transmitter module and an receiver module was designed, EEG is acquired using dry electrodes, amplified and processed by an application-specific integrated circuit (ASIC), and transmitted to the receiver by RF chip. The BCI system can obtain the subject’s degree of concentration, and those trained subjects have the ability of controlling the machine by changing their EEG signals. A experiment that controlling a toy car using the BCI system is successfully performed. The wearable transmitter module weighs 39 g only and easy to wear. The transmitter consumes 60 mW of dc power and generates an output power of 0 dBm. The BCI system is suitable for long-term EEG monitoring in users’ daily life. This system is feasible for further extension.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleDry Electrode Based Wearable Wireless Brain–Computer Interface System
    typeJournal Paper
    journal volume2
    journal issue3
    journal titleJournal of Nanotechnology in Engineering and Medicine
    identifier doi10.1115/1.4005487
    journal fristpage31007
    identifier eissn1949-2952
    keywordsElectrodes
    keywordsComputers
    keywordsBrain
    keywordsElectroencephalography
    keywordsSignals AND Manufacturing
    treeJournal of Nanotechnology in Engineering and Medicine:;2011:;volume( 002 ):;issue: 003
    contenttypeFulltext
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