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Conference Paper: Eye movement pattern in face recognition is associated with cognitive decline in the elderly

TitleEye movement pattern in face recognition is associated with cognitive decline in the elderly
Authors
KeywordsEye movement
Aging
Face recognition
Holistic processing
Cognitive ability
Hidden Markov Model (HMM)
Issue Date2015
Citation
The 37th Annual Conference of the Cognitive Science Society (CogSci 2015), Pasadena, CA., 22-25 July 2015. How to Cite?
AbstractThe present study investigated the relationship between eye movement pattern in face recognition and cognitive perform-ance during natural aging through modeling and comparing eye movement of young (18-24 years) and older (65-81 years) adults using Hidden Markov Model (HMM) based approach. Young adults recognized faces better than older adults, particularly when measured by the false alarm rate. Older adults’ recognition performance, on the other hand, correlated with their cognitive status assessed by the Montreal Cognitive Assessment (MoCA). Eye movement analysis with HMM revealed two different strategies, namely “analytic” and “holistic”. Participants using the analytic strategy had better recognition performance (particularly in the false alarm rate) than those using the holistic strategy. Significantly more young adults adopted the analytic strategy; whereas more older adults adopted the holistic strategy. Interestingly, older adults with lower cognitive status were associated with higher likelihood of using the holistic strategy. These results suggest an association between holistic eye movement patterns and cognitive decline in the elderly.
DescriptionConference Theme: Mind, Technology, and Society
Persistent Identifierhttp://hdl.handle.net/10722/212263

 

DC FieldValueLanguage
dc.contributor.authorChan, CYH-
dc.contributor.authorChan, AB-
dc.contributor.authorLee, TMC-
dc.contributor.authorHsiao, JH-
dc.date.accessioned2015-07-21T02:30:11Z-
dc.date.available2015-07-21T02:30:11Z-
dc.date.issued2015-
dc.identifier.citationThe 37th Annual Conference of the Cognitive Science Society (CogSci 2015), Pasadena, CA., 22-25 July 2015.-
dc.identifier.urihttp://hdl.handle.net/10722/212263-
dc.descriptionConference Theme: Mind, Technology, and Society-
dc.description.abstractThe present study investigated the relationship between eye movement pattern in face recognition and cognitive perform-ance during natural aging through modeling and comparing eye movement of young (18-24 years) and older (65-81 years) adults using Hidden Markov Model (HMM) based approach. Young adults recognized faces better than older adults, particularly when measured by the false alarm rate. Older adults’ recognition performance, on the other hand, correlated with their cognitive status assessed by the Montreal Cognitive Assessment (MoCA). Eye movement analysis with HMM revealed two different strategies, namely “analytic” and “holistic”. Participants using the analytic strategy had better recognition performance (particularly in the false alarm rate) than those using the holistic strategy. Significantly more young adults adopted the analytic strategy; whereas more older adults adopted the holistic strategy. Interestingly, older adults with lower cognitive status were associated with higher likelihood of using the holistic strategy. These results suggest an association between holistic eye movement patterns and cognitive decline in the elderly.-
dc.languageeng-
dc.relation.ispartofProceedings of the 37th Annual Conference of the Cognitive Science Society, CogSci 2015-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectEye movement-
dc.subjectAging-
dc.subjectFace recognition-
dc.subjectHolistic processing-
dc.subjectCognitive ability-
dc.subjectHidden Markov Model (HMM)-
dc.titleEye movement pattern in face recognition is associated with cognitive decline in the elderly-
dc.typeConference_Paper-
dc.identifier.emailLee, TMC: tmclee@hku.hk-
dc.identifier.emailHsiao, JH: jhsiao@hku.hk-
dc.identifier.authorityLee, TMC=rp00564-
dc.identifier.authorityHsiao, JH=rp00632-
dc.description.naturepostprint-
dc.identifier.hkuros245541-

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