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1、COMPUTERSIMULATIONSEditor:DietrichStauffer,stauffer@thp.uni-koeln.deMuhammadSahimi,moe@iran.usc.eduNEWCOMPUTATIONALAPPROACHESTOTHEANALYSISOFINTERBEATINTERVALSINHUMANSUBJECTSByMohammadRezaRahimiTabar,FatemehGhasemi,JoachimPeinke,RudolfFriedrich,KamranKaviani,FatemehTaghavi,SaraSadeghi,GolnooshBizhan
2、i,andMuhammadSahimiOMPLEX,SELF-REGULATINGSYSTEMShomogeneous(differentpartsoftheserieshaveidenticalsta-tisticalproperties)iscalledamonofractalseries.CSUCHASTHEHUMANHEARTMUSTHowever,manyphysiologicaltimeseriesareinhomoge-neousinthesensethatdistinctstatisticalandscalingprop-PROCESSINPUTSWITHABROADRANG
3、EOFCHAR-ertiescharacterizedifferentpartsoftheseries.Inaddition,thereissomeevidencethatphysiologicaldynamicscanex-ACTERISTICSTOGENERATEPHYSIOLOGICALhibitnonlinearproperties.6–12Suchfeaturesareoftenas-sociatedwithmultifractalbehavior—thepresenceofdataandtimeseries.1–3Manyofthesephysiologicaltimese-lo
4、ng-rangepower-lawcorrelationsinthehighermomentsriesseemtobehighlychaotic,representnonstationarydata,ofthetimeseries—which,unlikemonofractals,arenon-andfluctuateinanirregularandcomplexmanner.Onehy-linearfunctionsofthesecondmoment’sscalingexpo-pothesisisthattheseeminglychaoticstructureofphysio-nents.1
5、3Upuntilrecently,though,robustdemonstrationlogicaltimeseriesarisesfromexternalandintrinsicofmultifractalityofnonstationarytimeserieswasham-perturbationsthatpushthesystemawayfromahomeostaticperedbyproblemsrelatedtosignificantbiasintheesti-setpoint.Analternativehypothesisisthatthefluctuationsmatesofth
6、edata’ssingularityspectrum,duetothetimearedue,atleastinpart,tothesystem’sunderlyingdynamics.series’divergingnegativemoments.Anewwavelet-basedInthisreview,wedescribenewcomputationalap-multifractalformalismhelpsaddresssuchproblems.13proaches—basedonnewtheoreticalconcepts—foranalyz-Amongphysiologicalt
7、imeseries,thestudyofthestatisti-ingphysiologicaltimeseries.We’llshowthattheapplicationcalpropertiesofheartbeatintervalsequenceshasattractedofthesemethodscouldpotentiallyleadtoanoveldiagnos-muchattention.14–
