Steady-state visual evoked potential based classification system for detecting migraine seizures

Ko, LW; Lai, KL; Huang, PH; Lin, CT; Wang, SJ

Steady-state visual evoked potential based classification system for detecting migraine seizures

Ko, LW Lai, KL Huang, PH Lin, CT

Wang, SJ

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Publication Type:: Conference Proceeding
Citation:: International IEEE/EMBS Conference on Neural Engineering, NER, 2013, pp. 1299 - 1302
Issue Date:: 2013-12-01

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Field	Value	Language
dc.contributor.author	Ko, LW	en_US
dc.contributor.author	Lai, KL	en_US
dc.contributor.author	Huang, PH	en_US
dc.contributor.author	Lin, CT https://orcid.org/0000-0001-8371-8197	en_US
dc.contributor.author	Wang, SJ	en_US
dc.date.issued	2013-12-01	en_US
dc.identifier.citation	International IEEE/EMBS Conference on Neural Engineering, NER, 2013, pp. 1299 - 1302	en_US
dc.identifier.isbn	9781467319690	en_US
dc.identifier.issn	1948-3546	en_US
dc.identifier.uri	http://hdl.handle.net/10453/120898
dc.description.abstract	The recurrent migraine attacks between interictal phenomenon is triggered by the migraineurs' brain lacking for habituation, due to the stimulations from the outside world that increase the excitability of brain activity, which have been considered as the possible reasons for migraine seizure. The variation of habituation level within the migraine cycle is proposed to be a critical symptom to describe the physiological states of migraine headache. This study proposed Steady-State Visual Evoked Potentials (SSVEP) examination to utilize habituation for classifying the different physiologic states of migraine cycle, and implement a classification system to determine different migraine states. The developed system may be extended to detect migraine seizure, and provide an opportunity to a clinically individual-based headache monitoring program, aiming for early migraine detection. © 2013 IEEE.	en_US
dc.relation.ispartof	International IEEE/EMBS Conference on Neural Engineering, NER	en_US
dc.relation.isbasedon	10.1109/NER.2013.6696179	en_US
dc.title	Steady-state visual evoked potential based classification system for detecting migraine seizures	en_US
dc.type	Conference Proceeding
utslib.for	0902 Automotive Engineering	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:

The recurrent migraine attacks between interictal phenomenon is triggered by the migraineurs' brain lacking for habituation, due to the stimulations from the outside world that increase the excitability of brain activity, which have been considered as the possible reasons for migraine seizure. The variation of habituation level within the migraine cycle is proposed to be a critical symptom to describe the physiological states of migraine headache. This study proposed Steady-State Visual Evoked Potentials (SSVEP) examination to utilize habituation for classifying the different physiologic states of migraine cycle, and implement a classification system to determine different migraine states. The developed system may be extended to detect migraine seizure, and provide an opportunity to a clinically individual-based headache monitoring program, aiming for early migraine detection. © 2013 IEEE.

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http://hdl.handle.net/10453/120898