A wireless Electrooculography-based human-computer interface for baseball game

Lin, CT; Wu, SL; Jiang, WL; Liang, JW; Chen, SA

A wireless Electrooculography-based human-computer interface for baseball game

Lin, CT

Wu, SL Jiang, WL Liang, JW Chen, SA

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Publication Type:: Conference Proceeding
Citation:: ICICS 2013 - Conference Guide of the 9th International Conference on Information, Communications and Signal Processing, 2013
Issue Date:: 2013-01-01

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Field	Value	Language
dc.contributor.author	Lin, CT https://orcid.org/0000-0001-8371-8197	en_US
dc.contributor.author	Wu, SL	en_US
dc.contributor.author	Jiang, WL	en_US
dc.contributor.author	Liang, JW	en_US
dc.contributor.author	Chen, SA	en_US
dc.date.issued	2013-01-01	en_US
dc.identifier.citation	ICICS 2013 - Conference Guide of the 9th International Conference on Information, Communications and Signal Processing, 2013	en_US
dc.identifier.uri	http://hdl.handle.net/10453/120976
dc.description.abstract	Gaming control becomes popular based on the development of human-computer interface (HCI). Among many kinds of physiological signals, Electrooculography (EOG) signal is more stable which can be used to control HCI systems based on eye movement detection and signal processing methods. However, there are currently no effective multi-directional classification methods for monitoring eye movements. In addition, many EOG-based HCI systems have been developed with traditional wet electrodes. Those traditional electrodes require conductive gel and skin preparation on some users. Here, we describe a signal processing method used in a wireless EOG-based HCI system with dry electrodes for detecting eye movements to have 9 options. This system includes wireless EOG signal acquisition device, dry electrodes and an EOG signal processing algorithm. The EOG signal processing algorithm is based on 9 options of eye movement and blink signals. The results demonstrated an application of baseball game control using the proposed wireless HCI system. This system provides an effective and convenient method for eye movement detection. © 2013 IEEE.	en_US
dc.relation.ispartof	ICICS 2013 - Conference Guide of the 9th International Conference on Information, Communications and Signal Processing	en_US
dc.relation.isbasedon	10.1109/ICICS.2013.6782884	en_US
dc.title	A wireless Electrooculography-based human-computer interface for baseball game	en_US
dc.type	Conference Proceeding
utslib.for	0806 Information Systems	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Gaming control becomes popular based on the development of human-computer interface (HCI). Among many kinds of physiological signals, Electrooculography (EOG) signal is more stable which can be used to control HCI systems based on eye movement detection and signal processing methods. However, there are currently no effective multi-directional classification methods for monitoring eye movements. In addition, many EOG-based HCI systems have been developed with traditional wet electrodes. Those traditional electrodes require conductive gel and skin preparation on some users. Here, we describe a signal processing method used in a wireless EOG-based HCI system with dry electrodes for detecting eye movements to have 9 options. This system includes wireless EOG signal acquisition device, dry electrodes and an EOG signal processing algorithm. The EOG signal processing algorithm is based on 9 options of eye movement and blink signals. The results demonstrated an application of baseball game control using the proposed wireless HCI system. This system provides an effective and convenient method for eye movement detection. © 2013 IEEE.

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http://hdl.handle.net/10453/120976