Brain computer interface-based smart environmental control system

Ou, CZ; Lin, BS; Chang, CJ; Lin, CT

Brain computer interface-based smart environmental control system

Ou, CZ Lin, BS Chang, CJ Lin, CT

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the 2012 8th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2012, 2012, pp. 281 - 284
Issue Date:: 2012-10-11

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Field	Value	Language
dc.contributor.author	Ou, CZ	en_US
dc.contributor.author	Lin, BS	en_US
dc.contributor.author	Chang, CJ	en_US
dc.contributor.author	Lin, CT https://orcid.org/0000-0001-8371-8197	en_US
dc.date.issued	2012-10-11	en_US
dc.identifier.citation	Proceedings of the 2012 8th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2012, 2012, pp. 281 - 284	en_US
dc.identifier.isbn	9780769547121	en_US
dc.identifier.uri	http://hdl.handle.net/10453/121235
dc.description.abstract	A Brain computer interface-based Smart Environmental Control System (BSECS) was proposed in this study. Many environmental control systems have been proposed to improve human life quality recently. However, few researches focused on environment control by using human's physiological state directly. Based on the advantage of our technique on Brain Computer Interface (BCI), we combined BCI technique with Universal Plug and Play (UPnP) home networking for smart house applications. Our BSECS mainly consists of a wireless physiological signal acquisition module, an embedded signal processing module, a Simple Control Protocol (SCP)/ Power Line Communication (PLC) environment controller, and a host system. Here, the physiological signal acquisition module and embedded signal processing module were designed for long-term electroencephalogram (EEG) monitoring and real-time cognitive state detection respectively. The advantages of low-power consumption and small volume of the above modules are suitable for smart house applications in daily life. The proposed BSECS has been verified in a practical demo room, and can be simply extended and integrated with the UPnP home networking for other applications. © 2012 IEEE.	en_US
dc.relation.ispartof	Proceedings of the 2012 8th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2012	en_US
dc.relation.isbasedon	10.1109/IIH-MSP.2012.74	en_US
dc.title	Brain computer interface-based smart environmental control system	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	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:

A Brain computer interface-based Smart Environmental Control System (BSECS) was proposed in this study. Many environmental control systems have been proposed to improve human life quality recently. However, few researches focused on environment control by using human's physiological state directly. Based on the advantage of our technique on Brain Computer Interface (BCI), we combined BCI technique with Universal Plug and Play (UPnP) home networking for smart house applications. Our BSECS mainly consists of a wireless physiological signal acquisition module, an embedded signal processing module, a Simple Control Protocol (SCP)/ Power Line Communication (PLC) environment controller, and a host system. Here, the physiological signal acquisition module and embedded signal processing module were designed for long-term electroencephalogram (EEG) monitoring and real-time cognitive state detection respectively. The advantages of low-power consumption and small volume of the above modules are suitable for smart house applications in daily life. The proposed BSECS has been verified in a practical demo room, and can be simply extended and integrated with the UPnP home networking for other applications. © 2012 IEEE.

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http://hdl.handle.net/10453/121235