Cell-phone based Drowsiness Monitoring and Management system

Wang, YT; Cheng, CK; Huang, KC; Lin, CT; Wang, Y; Jung, TP

Cell-phone based Drowsiness Monitoring and Management system

Wang, YT Cheng, CK Huang, KC Lin, CT

Wang, Y Jung, TP

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Publication Type:: Conference Proceeding
Citation:: 2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Conference Publications, 2012, pp. 200 - 203
Issue Date:: 2012-12-01

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Field	Value	Language
dc.contributor.author	Wang, YT	en_US
dc.contributor.author	Cheng, CK	en_US
dc.contributor.author	Huang, KC	en_US
dc.contributor.author	Lin, CT https://orcid.org/0000-0001-8371-8197	en_US
dc.contributor.author	Wang, Y	en_US
dc.contributor.author	Jung, TP	en_US
dc.date.issued	2012-12-01	en_US
dc.identifier.citation	2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Conference Publications, 2012, pp. 200 - 203	en_US
dc.identifier.isbn	9781467322935	en_US
dc.identifier.uri	http://hdl.handle.net/10453/120700
dc.description.abstract	In recent years, driving fatigue and cognitive lapses have gained increasing attentions in the fields of public security, especially regarding the safe manipulation of vehicles. Studies have explored the relation between electroencephalogram (EEG) and driving behavior and several of them further proposed effective approaches (e.g., auditory feedback) to arouse subjects from drowsiness. However, these studies were performed under laboratory-oriented configurations using tethered, ponderous EEG equipment. In real environments, the setup of bulky cognitive monitoring equipment with a long-prep time is not feasible. Therefore, this study extends previous laboratory work by developing an on-line Drowsiness Monitoring and Management (DMM) System featuring a mobile wireless dry-sensor EEG headgear and a cell-phone based real-time EEG processing platform. The DMM system can continuously observe EEG dynamics, deliver arousing feedback to users experiencing momentary cognitive lapses, and assess the efficacy of the feedback in near real-time. © 2012 IEEE.	en_US
dc.relation.ispartof	2012 IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Electronics and Systems for Better Life and Better Environment, BioCAS 2012 - Conference Publications	en_US
dc.relation.isbasedon	10.1109/BioCAS.2012.6418462	en_US
dc.title	Cell-phone based Drowsiness Monitoring and Management system	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:

In recent years, driving fatigue and cognitive lapses have gained increasing attentions in the fields of public security, especially regarding the safe manipulation of vehicles. Studies have explored the relation between electroencephalogram (EEG) and driving behavior and several of them further proposed effective approaches (e.g., auditory feedback) to arouse subjects from drowsiness. However, these studies were performed under laboratory-oriented configurations using tethered, ponderous EEG equipment. In real environments, the setup of bulky cognitive monitoring equipment with a long-prep time is not feasible. Therefore, this study extends previous laboratory work by developing an on-line Drowsiness Monitoring and Management (DMM) System featuring a mobile wireless dry-sensor EEG headgear and a cell-phone based real-time EEG processing platform. The DMM system can continuously observe EEG dynamics, deliver arousing feedback to users experiencing momentary cognitive lapses, and assess the efficacy of the feedback in near real-time. © 2012 IEEE.

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http://hdl.handle.net/10453/120700