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Multi level SVM for subject independent agitation detection

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dc.contributor.author Sakr G.E.
dc.contributor.author Elhajj I.H.
dc.contributor.author Wejinya U.C.
dc.contributor.editor
dc.date 2009
dc.date.accessioned 2017-10-04T11:06:43Z
dc.date.available 2017-10-04T11:06:43Z
dc.date.issued 2009
dc.identifier 10.1109/AIM.2009.5229958
dc.identifier.isbn 9.7814244285e+012
dc.identifier.issn
dc.identifier.uri http://hdl.handle.net/10938/14081
dc.description.abstract The need to automate the detection of agitation for dementia patients is a major requirement for caregivers. This research aims at detecting the agitation status of the subjects using soft computing techniques that does not require supervision beyond the training phase. An autonomous multi-sensory device has been developed to achieve automatic assessment of agitation and to control stimulation that will reduce the agitation level automatically. The focus of this paper is the agitation detection algorithm. Three vital signs are monitored for agitation detection: the Heart Rate (HR) the Galvanic Skin Response (GSR) and Skin Temperature (ST). These measures are fed into a new SVM architecture: The Multi level SVM learning machine. Results show very high detection accuracy of agitation, quick adaptation to the subject and a strong correlation between the physiological signals monitored and the emotional states of the subjects. The result is a learning algorithm that is Subject-Independent. ©2009 IEEE.
dc.format.extent
dc.format.extent Pages: (538-543)
dc.language English
dc.publisher NEW YORK
dc.relation.ispartof Publication Name: IEEE-ASME International Conference on Advanced Intelligent Mechatronics, AIM; Conference Title: 2009 IEEE-ASME International Conference on Advanced Intelligent Mechatronics, AIM 2009; Conference Date: 14 July 2009 through 17 July 2009; Conference Location: Singapore; Publication Year: 2009; Pages: (538-543);
dc.relation.ispartofseries
dc.relation.uri
dc.source Scopus
dc.subject.other
dc.title Multi level SVM for subject independent agitation detection
dc.type Conference Paper
dc.contributor.affiliation Sakr, G.E., American University of Beirut, Electrical and Computer Engineering Dept., Beirut, Lebanon
dc.contributor.affiliation Elhajj, I.H., American University of Beirut, Electrical and Computer Engineering Dept., Beirut, Lebanon
dc.contributor.affiliation Wejinya, U.C., University of Arkansas, Department of Mechanical Engineering, Fayetteville, AR, United States
dc.contributor.authorAddress Sakr, G. E.; American University of Beirut, Electrical and Computer Engineering Dept., Beirut, Lebanon; email: ges07@aub.edu.lb
dc.contributor.authorCorporate University: American University of Beirut; Faculty: Faculty of Engineering and Architecture; Department: Electrical and Computer Engineering;
dc.contributor.authorDepartment Electrical and Computer Engineering
dc.contributor.authorDivision
dc.contributor.authorEmail ges07@aub.edu.lb; ie05@aub.edu.lb; uwejinya@uark.edu
dc.contributor.authorFaculty Faculty of Engineering and Architecture
dc.contributor.authorInitials Sakr, GE
dc.contributor.authorInitials Elhajj, IH
dc.contributor.authorInitials Wejinya, UC
dc.contributor.authorOrcidID
dc.contributor.authorReprintAddress Sakr, GE (reprint author), Amer Univ Beirut, Dept Elect and Comp Engn, Beirut, Lebanon.
dc.contributor.authorResearcherID
dc.contributor.authorUniversity American University of Beirut
dc.description.cited American Psychiatric Association, 1994, DIAGN STAT MAN MENT; CULTER NR, 1996, UNDERSTANDING ALZHEI, P65; FOOK VFS, 2007, E HLTH NETW APPL SER, P68; Kecman V., 2001, LEARNING SOFT COMPUT; Kistler A, 1998, INT J PSYCHOPHYSIOL, V29, P35, DOI 10.1016-S0167-8760(97)00087-1; LIAO WH, 2005, IEEE COMP SOC C, V3, P70; Murray DR, 2003, CHEST, V123, P664, DOI 10.1378-chest.123.3.664; ROD K, 2000, INT J PSYCHOPHYSIOL, V37, P121; Rosenblatt Adam, 2005, Cleve Clin J Med, V72 Suppl 3, pS3; SAKR GE, 2008, ADV INT MECH IEEE AS; Tamura T., 1997, P 19 ANN INT C IEEE, V3, P999, DOI 10.1109-IEMBS.1997.756513; TULEN JHM, 1989, PHARMACOL BIOCHEM BE, V32, P9, DOI 10.1016-0091-3057(89)90204-9; *US BUR CENS, 2006, 65 US; Vapnik V.N., STAT LEARNING THEORY; Zhai J., 2006, FLAIRS C, P395
dc.description.citedCount 3
dc.description.citedTotWOSCount 2
dc.description.citedWOSCount 2
dc.format.extentCount 6
dc.identifier.articleNo 5229958
dc.identifier.coden
dc.identifier.pubmedID
dc.identifier.scopusID 70350435877
dc.identifier.url
dc.publisher.address 345 E 47TH ST, NEW YORK, NY 10017 USA
dc.relation.ispartofConference Conference Title: 2009 IEEE-ASME International Conference on Advanced Intelligent Mechatronics, AIM 2009 : Conference Date: 14 July 2009 through 17 July 2009 , Conference Location: Singapore.
dc.relation.ispartofConferenceCode 78051
dc.relation.ispartofConferenceDate 14 July 2009 through 17 July 2009
dc.relation.ispartofConferenceHosting
dc.relation.ispartofConferenceLoc Singapore
dc.relation.ispartofConferenceSponsor
dc.relation.ispartofConferenceTitle 2009 IEEE-ASME International Conference on Advanced Intelligent Mechatronics, AIM 2009
dc.relation.ispartofFundingAgency
dc.relation.ispartOfISOAbbr
dc.relation.ispartOfIssue
dc.relation.ispartOfPart
dc.relation.ispartofPubTitle IEEE-ASME International Conference on Advanced Intelligent Mechatronics, AIM
dc.relation.ispartofPubTitleAbbr IEEE ASME Int Conf Adv Intellig Mechatron AIM
dc.relation.ispartOfSpecialIssue
dc.relation.ispartOfSuppl
dc.relation.ispartOfVolume
dc.source.ID WOS:000277062800092
dc.type.publication Series
dc.subject.otherAuthKeyword
dc.subject.otherChemCAS
dc.subject.otherIndex Agitation levels
dc.subject.otherIndex Automatic assessment
dc.subject.otherIndex Dementia patients
dc.subject.otherIndex Detection accuracy
dc.subject.otherIndex Detection algorithm
dc.subject.otherIndex Emotional state
dc.subject.otherIndex Galvanic skin response
dc.subject.otherIndex Heart rates
dc.subject.otherIndex Learning machines
dc.subject.otherIndex Multi-level
dc.subject.otherIndex Multi-sensory devices
dc.subject.otherIndex Physiological signals
dc.subject.otherIndex Skin temperatures
dc.subject.otherIndex Softcomputing techniques
dc.subject.otherIndex Strong correlation
dc.subject.otherIndex Training phase
dc.subject.otherIndex Vital sign
dc.subject.otherIndex Asymptotic analysis
dc.subject.otherIndex Learning algorithms
dc.subject.otherIndex Mechatronics
dc.subject.otherIndex Skin
dc.subject.otherIndex Soft computing
dc.subject.otherIndex Support vector machines
dc.subject.otherIndex Intelligent mechatronics
dc.subject.otherKeywordPlus
dc.subject.otherWOS Automation and Control Systems
dc.subject.otherWOS Computer Science, Artificial Intelligence
dc.subject.otherWOS Computer Science, Theory and Methods
dc.subject.otherWOS Engineering, Electrical and Electronic


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