Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/62109

TitleWireless and wearable EEG acquisition platform for ambulatory monitoring
Author(s)Pinho, F. T.
Correia, J. H.
Sousa, N. J.
Cerqueira, João José
Dias, N. S.
KeywordsEEG
Epilepsy
Wireless
Dry-electrodes
Embedded systems
Issue date2014
PublisherIEEE
JournalIEEE International Conference on Serious Games and Applications for Health
CitationPinho, F., Correia, J. H., Sousa, N. J., Cerqueira, J. J., & Dias, N. S. (2014, May). Wireless and wearable EEG acquisition platform for ambulatory monitoring. In 2014 IEEE 3nd International Conference on Serious Games and Applications for Health (SeGAH) (pp. 1-7). IEEE
Abstract(s)Electroencephalogram (EEG) Ambulatory monitoring has been regarded as a promising tool to improve diagnosis, classification and medication prescription in patients with epilepsy and other paroxysmal diseases. This study presents the development of a wireless and wearable EEG acquisition system for ambulatory monitoring. The platform comprises 32 active dry electrodes, an analog-to-digital conversion unit with 24 bit resolution, 1 ksps sampling frequency per channel and a module for acquisition, processing and wireless transmission based on IGEP COM embedded system development platform under a Linux™ operative system. The base operating system consists of two software frameworks which interact to ensure the real-time requirements of the acquired signals and parallel recording, processing and data transmission. In order to control the analog-to-digital converters and the synchronous reception of converted data, a Linux™ kernel driver was developed. It was also developed an userspace application for data saving, digital processing and wireless transmission via socket TCP-IP on a 802.11 b/g network topology. An application based on C# from .NET development environment was also developed for PC data reception and visualization. This application consists of a TCP socket server for data reception and a graphic environment for signal's visualization. For signal plotting, it was used the open source ZedGraph library. The proposed system may operate on data streaming or event detection modes and presents feasible performance on EEG monitoring of both epileptic inpatients and outpatients
TypeConference paper
URIhttp://hdl.handle.net/1822/62109
ISBN978-1-4799-4823-9
DOI10.1109/SeGAH.2014.7067078
ISSN2330-5649
Publisher versionhttps://ieeexplore.ieee.org/abstract/document/7067078
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:ICVS - Artigos em Revistas Internacionais com Referee

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