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<Article>
<Journal>
				<PublisherName>Tarbiat Modares University</PublisherName>
				<JournalTitle>The Modares Journal of Electrical Engineering</JournalTitle>
				<Issn>2228-527X</Issn>
				<Volume>10</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2011</Year>
					<Month>01</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Anxiety Detection by Periorbital Mean Temperature Signal Analysis</ArticleTitle>
<VernacularTitle>آشکارسازی استرس با استفاده از سیگنال دمای میانگین ناحیه دور چشم</VernacularTitle>
			<FirstPage>101</FirstPage>
			<LastPage>113</LastPage>
			<ELocationID EIdType="pii">12812</ELocationID>
			
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Amin</FirstName>
					<LastName>Derakhshan</LastName>
<Affiliation>Imamreza International University, Mashhad</Affiliation>

</Author>
<Author>
					<FirstName>Mohammad Ali</FirstName>
					<LastName>Khalilzadeh</LastName>
<Affiliation>Islamic Azad University, Mashhad Branch</Affiliation>

</Author>
<Author>
					<FirstName>Amin</FirstName>
					<LastName>Mohammadian</LastName>
<Affiliation>Research Center of Intelligent Signal Processing</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
		<Abstract>It has been demonstrated that anxiety is accompanied by significant warm up in the periorbital area. This warm up was attributed to the increased blood circulation in the area around the eyes. The whole pattern makes physiological and evolutionary sense since it represents a mechanism to facilitate rapid eye movements during preparedness for fight. This increased blood flow dissipates convective heat, which can be monitored through thermal imaging. The evolution of these variables along the timeline and across the 2D space can reveal important clues about anxiety. In this work, we use both facial thermal imaging analysis and poly graph examination to evaluate the effectiveness of thermal imaging in situation of anxiety. The system had been evaluated on six subjects and for each of them four times, each time in two minutes. It operates on the raw temperature signal and tries to improve the information content by suppressing the noise level instead of amplifying the signal as a whole. Finally, a pattern recognition method classifies stressful (deceptive) from non-stressful (non-deceptive) subjects based on a comparative measure between the entire baseline signal and a transient response. The successful classification rate with Multi Layer Perceptron is about 74.7% that is a little better than the LDA method.</Abstract>
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			<Object Type="keyword">
			<Param Name="value">Anxiety</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Thermal Imaging</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Ploy Graph</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Multi-Layer Perceptron(MLP)</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://mjee.modares.ac.ir/article_12812_179db74797bde5f379b623ab73ee7c64.pdf</ArchiveCopySource>
</Article>
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