6Accelerometer-basedgaitrecognitionviavotingbysignaturepoints.pdf

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1、Accelerometer-basedgaitrecognitionviaIdentificationasvotingbysignaturepoints:Beforegaitrecognition,thevotingbysignaturepointsgait’sstepcyclesaredetectedandsegmentedinadvance.TheneachstepcycleisnormalisedtothesamelengthL.AssumethatgaitxhasmstepG.Pan,Y.ZhangandZ.Wucycles

2、separatedbymþ1pointst1,t2,...,tmþ1,wheretheithcycleoccupiestheintervalðti;tiþ1,wedefinetherelativelocationofasignaturepointsinthestepcycleperiodasAnovelalgorithmtorecognisehumanidentitiesviagaitbybody-wornaccelerometersispresented.Itusesaccelerationinformationtomeasure

3、rlocðsÞ¼sti;wheretiissubjecttos[ðti;tiþ1ð4Þhumangaitdynamics.Acceleration-basedgaitrecognitionisanon-intrusivebiometricmeasurement,whichisinsensitivetochangesofGiventhetrainingsetB¼fðb;lÞgnwithnidentity-knowngaits,iii¼1lightingconditionsandviewpoint.Theproposedalgori

4、thmfirstwherebiisagaitandliisitsidentity(orlabel),thesetofallthesignatureextractssignaturepointsfromgaitaccelerationsignals,andthenident-npointsinthetrainingsetcanbewrittenasT¼

5、thadatasetof30subjectsshowthattheproposednaturepointfrombialsohasthelabellialgorithmsignificantlyoutperformsotherexistingmethodsandSupposethataisaninputgaitwithunknownidentity.Foreachsig-achievesahighrecognitionrateof96.7%forthecaseoffivenaturepoints[SðaÞ,wepredictitsla

6、belbythenearestneighbouraccelerometers.method.Thatis,weusethelabelofthenearestsignaturepointinTasthepredictedlabelofs.Thedistancemetricoftwosignaturepointss1ands2isdefinedfornearestneighbourfindinginthespaceofthesigna-Introduction:Theemergingpervasivecomputingparadigmem

7、phasisesturepoint:thatcomputingbethoroughlyintegratedintoeverydayactivities,andservicesbeprovidedinanunobtrusivemanner,whichrequiresthejQðs2ÞQðs1Þj;ifjrlocðs1Þrlocðs2Þj,dawarenessofuseridentity.Manyminiaturisedsensors,ranginginsizedistðs1;s2Þ¼þ1otherwiseð5Þfrommicr

8、ometrestomillimetres,arebeingwidelyusedinourdailylife.Inparticular,wearableaccelerometershavebeenemployedinThetemporalconstr