Feature extraetion for biometrie reeognition with photoplethysmography signals

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dc.authorid0000-0003-1840-9958
dc.authorid0000-0002-4380-9075
dc.authorid0000-0003-0673-4454
dc.authorid0000-0002-8929-3473
dc.contributor.authorKavsaoğlu, Ahmet Reşit
dc.contributor.authorPolat, Kemal
dc.contributor.authorBozkurt, Mehmet Recep
dc.contributor.authorMuthusamy, Hariharan
dc.date.accessioned2021-06-23T18:55:48Z
dc.date.available2021-06-23T18:55:48Z
dc.date.issued2013
dc.departmentBAİBÜ, Mühendislik Fakültesi, Elektrik Elektronik Mühendisliği Bölümüen_US
dc.description2013 21st Signal Processing and Communications Applications Conference, SIU 2013 -- 24 April 2013 through 26 April 2013 -- Haspolat -- 98109en_US
dc.description.abstractPhotoplethysmography (PPG) signals stand out due to features such as readily accessible, high reliability and confidentiality, the ease of use etc. among bio-signals. The feasibility studies carried out on the PPG signals demonstrated that PPG signals contained important features for human recognition and were the availability of biometric identification systems. In this study, twenty new features were extracted from PPG signal as a preliminary study intended to biometric recognition. PPG signals with 10 seconds were recorded from five healthy people using SDPPG (second derivative PPG) data acquisition card. To remove the noise from received raw PPG signals, a FIR low pass filtering with 200 points and 10 Hz cut-off frequency was designed. These twenty new features were obtained from filtered PPG signal and its second derivative. PPG signal with 10 seconds contains eight periods and twenty characteristic features in each person must not change within an individual over a period. This feature symbolizes the consistency in the identification of a person. To test the performance of biometrie recognition system, the k-NN (k-nearest neighbor) classifier was used and achieved 95% of recognition success rate using lO-fold cross validation with twenty new features. The obtained results showed that the developed biometric recognition system based on PPG signal were very promising. © 2013 IEEE.en_US
dc.identifier.doi10.1109/SIU.2013.6531568
dc.identifier.isbn9781467355629
dc.identifier.scopus2-s2.0-84880896360en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/SIU.2013.6531568
dc.identifier.urihttps://hdl.handle.net/20.500.12491/4862
dc.indekslendigikaynakScopusen_US
dc.institutionauthorPolat, Kmeal
dc.language.isotren_US
dc.relation.ispartof2013 21st Signal Processing and Communications Applications Conference, SIU 2013en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBiometriesen_US
dc.subjectClassijicationen_US
dc.subjectDerivativesen_US
dc.subjectFeature Extractionen_US
dc.subjectIdentijicationen_US
dc.subjectPhotoplethysmography (PPG)en_US
dc.subjectBiyometri
dc.subjectFotopletismografi (PPG)
dc.subjectTammlama
dc.subjectSınıflandlrma
dc.subjectTürevIer
dc.titleFeature extraetion for biometrie reeognition with photoplethysmography signalsen_US
dc.title.alternativeFotopletismografi sinyalleri ile biyometrik tanımaya yönelik özellik çıkarımıen_US
dc.typeConference Objecten_US

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