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Estimation of driver attention using Visually Evoked Potentials
We propose a system for estimating driver attention levels using Visually evoked potentials (VEP), computed from the EEG signals of the visual cortex. We investigate the use of both steady state VEP (SSVEP) and pattern onset VEP (POVEP) for this purpose. The subject fixates on a flickering stimulus,...
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creator | Reddy, B Srinath Basir, Otman A. Leat, Susan J. |
description | We propose a system for estimating driver attention levels using Visually evoked potentials (VEP), computed from the EEG signals of the visual cortex. We investigate the use of both steady state VEP (SSVEP) and pattern onset VEP (POVEP) for this purpose. The subject fixates on a flickering stimulus, generating a Steady State VEP (SSVEP). Occasionally, a random stimulus is flashed on the screen, and the subsequent POVEP is also analyzed. It is seen that the SSVEP is related to the attention levels of the subjects. The sudden stimulus also generates local maxima/minima values for the POVEP, at the P2 and N2 components. Entropy measures of the frequency response of both the responses could also be used to characterize the occurrence of stimuli. We also propose a system architecture for a driver alertness system, which fuses the above process and a vision based traffic analysis system, to alert the driver well in advance of any decrease in attention. |
doi_str_mv | 10.1109/IVS.2007.4290179 |
format | book_chapter |
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We investigate the use of both steady state VEP (SSVEP) and pattern onset VEP (POVEP) for this purpose. The subject fixates on a flickering stimulus, generating a Steady State VEP (SSVEP). Occasionally, a random stimulus is flashed on the screen, and the subsequent POVEP is also analyzed. It is seen that the SSVEP is related to the attention levels of the subjects. The sudden stimulus also generates local maxima/minima values for the POVEP, at the P2 and N2 components. Entropy measures of the frequency response of both the responses could also be used to characterize the occurrence of stimuli. 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We also propose a system architecture for a driver alertness system, which fuses the above process and a vision based traffic analysis system, to alert the driver well in advance of any decrease in attention.</description><subject>Brain Computing</subject><subject>Cameras</subject><subject>Driver Attention</subject><subject>Electroencephalography</subject><subject>Electrooculography</subject><subject>Fatigue</subject><subject>Frequency</subject><subject>Machine vision</subject><subject>Road accidents</subject><subject>SSVEP</subject><subject>Steady-state</subject><subject>Telecommunication traffic</subject><subject>Visual Evoked Potential</subject><subject>Wireless sensor networks</subject><issn>1931-0587</issn><issn>2642-7214</issn><isbn>1424410673</isbn><isbn>9781424410675</isbn><isbn>1424410681</isbn><isbn>9781424410682</isbn><fulltext>true</fulltext><rsrctype>book_chapter</rsrctype><creationdate>2007</creationdate><recordtype>book_chapter</recordtype><sourceid>6IE</sourceid><recordid>eNpFkF1LwzAYheMX2E3vBW_yB1rzvkma5EpkVB0MFBy7HVn7ZkTrKk032L93zIFXD5wHDofD2B2IAkC4h-nio0AhTKHQCTDujI1AoVIgSgvnLMNSYW4Q1MW_MPKSZeAk5EJbc81GKX0KoTUiZOyxSkP89kPsNrwLvOnjjnruh4E2x2yb4mbNFzFtfdvuebXrvqjh793R-zbdsKtwAN2eOGbz52o-ec1nby_TydMsXxvh8uA1aqes8gFQUVBGulXZWCucJgoGdUBfAiFR7UDWtalrrSyFldEESssxu_-rjUS0_OkPk_v98nSC_AXpA0x2</recordid><startdate>200706</startdate><enddate>200706</enddate><creator>Reddy, B Srinath</creator><creator>Basir, Otman A.</creator><creator>Leat, Susan J.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>200706</creationdate><title>Estimation of driver attention using Visually Evoked Potentials</title><author>Reddy, B Srinath ; Basir, Otman A. ; Leat, Susan J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-g709-fa5259484af124ef4739b6d88095eef725f2a61e2eec913cc7cc548efb75e1453</frbrgroupid><rsrctype>book_chapters</rsrctype><prefilter>book_chapters</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Brain Computing</topic><topic>Cameras</topic><topic>Driver Attention</topic><topic>Electroencephalography</topic><topic>Electrooculography</topic><topic>Fatigue</topic><topic>Frequency</topic><topic>Machine vision</topic><topic>Road accidents</topic><topic>SSVEP</topic><topic>Steady-state</topic><topic>Telecommunication traffic</topic><topic>Visual Evoked Potential</topic><topic>Wireless sensor networks</topic><toplevel>online_resources</toplevel><creatorcontrib>Reddy, B Srinath</creatorcontrib><creatorcontrib>Basir, Otman A.</creatorcontrib><creatorcontrib>Leat, Susan J.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Reddy, B Srinath</au><au>Basir, Otman A.</au><au>Leat, Susan J.</au><format>book</format><genre>bookitem</genre><ristype>CHAP</ristype><atitle>Estimation of driver attention using Visually Evoked Potentials</atitle><btitle>2007 IEEE Intelligent Vehicles Symposium</btitle><stitle>IVS</stitle><date>2007-06</date><risdate>2007</risdate><spage>588</spage><epage>593</epage><pages>588-593</pages><issn>1931-0587</issn><eissn>2642-7214</eissn><isbn>1424410673</isbn><isbn>9781424410675</isbn><eisbn>1424410681</eisbn><eisbn>9781424410682</eisbn><abstract>We propose a system for estimating driver attention levels using Visually evoked potentials (VEP), computed from the EEG signals of the visual cortex. We investigate the use of both steady state VEP (SSVEP) and pattern onset VEP (POVEP) for this purpose. The subject fixates on a flickering stimulus, generating a Steady State VEP (SSVEP). Occasionally, a random stimulus is flashed on the screen, and the subsequent POVEP is also analyzed. It is seen that the SSVEP is related to the attention levels of the subjects. The sudden stimulus also generates local maxima/minima values for the POVEP, at the P2 and N2 components. Entropy measures of the frequency response of both the responses could also be used to characterize the occurrence of stimuli. We also propose a system architecture for a driver alertness system, which fuses the above process and a vision based traffic analysis system, to alert the driver well in advance of any decrease in attention.</abstract><pub>IEEE</pub><doi>10.1109/IVS.2007.4290179</doi><tpages>6</tpages></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | ISSN: 1931-0587 |
ispartof | 2007 IEEE Intelligent Vehicles Symposium, 2007, p.588-593 |
issn | 1931-0587 2642-7214 |
language | eng |
recordid | cdi_ieee_primary_4290179 |
source | IEEE Xplore All Conference Series |
subjects | Brain Computing Cameras Driver Attention Electroencephalography Electrooculography Fatigue Frequency Machine vision Road accidents SSVEP Steady-state Telecommunication traffic Visual Evoked Potential Wireless sensor networks |
title | Estimation of driver attention using Visually Evoked Potentials |
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