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1、OPENRevealingReal-TimeEmotionalResponses:aPersonalizedAssessmentSUBJECTAREAS:COMPUTATIONALbasedonHeartbeatDynamicsBIOPHYSICSBIOMEDICALENGINEERING1,2,31,2,4331,2GaetanoValenza,LucaCiti,AntonioLanata´,EnzoPasqualeScilingo&RiccardoBarbieriAPPLIEDMATHEMAT
2、ICSCOMPUTATIONALSCIENCE1NeuroscienceStatisticsResearchLaboratory,MassachusettsGeneralHospital,HarvardMedicalSchool,Boston,MA,02114,2USA,DepartmentofBrainandCognitiveSciences,MassachusettsInstituteofTechnology,Cambridge,MA02139,USA,34ReceivedDepartment
3、ofInformationEngineeringandResearchCentreEPiaggio,UniversityofPisa,Pisa,Italy,SchoolofComputerScience25September2013andElectronicEngineering,UniversityofEssex,Colchester,CO43SQ,UK.Accepted4March2014Emotionrecognitionthroughcomputationalmodelingandanal
4、ysisofphysiologicalsignalshasbeenwidelyinvestigatedinthelastdecade.MostoftheproposedemotionrecognitionsystemsrequirerelativelyPublishedlong-timeseriesofmultivariaterecordsanddonotprovideaccuratereal-timecharacterizationsusing21May2014short-timeseries.
5、Toovercometheselimitations,weproposeanovelpersonalizedprobabilisticframeworkabletocharacterizetheemotionalstateofasubjectthroughtheanalysisofheartbeatdynamicsexclusively.Thestudyincludesthirtysubjectspresentedwithasetofstandardizedimagesgatheredfromth
6、einternationalaffectivepicturesystem,alternatinglevelsofarousalandvalence.DuetotheintrinsicCorrespondenceandnonlinearityandnonstationarityoftheRRintervalseries,aspecificpoint-processmodelwasdevisedforrequestsformaterialsinstantaneousidentificationcons
7、ideringautoregressivenonlinearitiesuptothethird-orderaccordingtoshouldbeaddressedtotheWiener-Volterrarepresentation,thustrackingveryfaststimulus-responsechanges.FeaturesfromtheG.V.(g.valenza@ieee.instantaneousspectrumandbispectrum,aswellasthedominantL
8、yapunovexponent,wereextractedandorg)consideredasinputfeaturestoasupportvectormachineforclassification.Results,estimatingemotionseach10seconds,achieveanoverallaccuracyinrecognizingfouremotionalstatesbasedonthecircumplexmodelofaffectof79.29%,wit
