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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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