prikaz prve stranice dokumenta Identifikacija osobe zasnovana na usporednoj analizi elektrokardiograma i hoda
No public access
master's thesis
Identifikacija osobe zasnovana na usporednoj analizi elektrokardiograma i hoda
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2014. urn:nbn:hr:168:605539
Luetić, Ivan
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Luetić, I. (2014). Identifikacija osobe zasnovana na usporednoj analizi elektrokardiograma i hoda (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:605539

Luetić, Ivan. "Identifikacija osobe zasnovana na usporednoj analizi elektrokardiograma i hoda." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2014. https://urn.nsk.hr/urn:nbn:hr:168:605539

Luetić, Ivan. "Identifikacija osobe zasnovana na usporednoj analizi elektrokardiograma i hoda." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2014. https://urn.nsk.hr/urn:nbn:hr:168:605539

Luetić, I. (2014). 'Identifikacija osobe zasnovana na usporednoj analizi elektrokardiograma i hoda', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 25 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:605539

Luetić I. Identifikacija osobe zasnovana na usporednoj analizi elektrokardiograma i hoda [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2014 [cited 2024 December 25] Available at: https://urn.nsk.hr/urn:nbn:hr:168:605539

I. Luetić, "Identifikacija osobe zasnovana na usporednoj analizi elektrokardiograma i hoda", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2014. Available at: https://urn.nsk.hr/urn:nbn:hr:168:605539

Metadata
TitleIdentifikacija osobe zasnovana na usporednoj analizi elektrokardiograma i hoda
Title (english)Human identification by comparative analysis of ECG and gait
AuthorIvan Luetić
MentorRatko Magjarević (mentor)
Committee memberRatko Magjarević (predsjednik povjerenstva)
Committee memberVedran Bilas (član povjerenstva)
Committee memberDarko Vasić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2014-07-09, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U ovom radu predložena je metoda identifikacije osoba zasnovana na nakupini empirijskih razlaganja (EEMD - Ensemble Empirical Mode Decomposition) prvog odvoda elektrokardiograma (EKG-a) i rekonstrukciji atraktora signala hoda, dobivenog korištenjem akcelerometra postavljenom na pojasu, u faznom prostoru korištenjem aproksimacijske geometrije pravokutnika. Predobradbom EKG-a uklanja se utjecaj šuma i smetnji te varijabilnosti srčanog ritma. EKG se razloži na intrinzične funkcije (IMF - Intrinsic mode functions) i Welchovom metodom se izračunaju spektri istih. IMF-ovi i pripadajući spektri predstavljaju izlučene značajke signala otkucaja srca. Ljudski hod promatra se kao dinamički sustav, a neparne svojstvene vrijednosti rekonstruiranog atraktora dobivene singularnom spektralnom analizom predstavljaju izlučene značajke. K-najbližih susjeda metoda koristi se kao klasifikator. Najbolja postignuta točnost identifikacije je 94%.
Abstract (english)
This paper presents a method of human identification based on ensemble empirical mode decomposition (EEMD) of an one-lead electrocardiogram (ECG) signal and by box approx-imation geometry of reconstructed attractors in latent space of a gait signal measured by an accelerometer located on the waist. Pre-processing of the ECG signal eliminates effects of noise and heart rate variability. The ECG signal is decomposed into a number of intrinsic mode functions (IMFs) and IMF’s spectrums are obtained using Welch method. IMFs and corresponding spectrums respresnt significant heartbeat signal features. Human gait is considered as a dynamical system and the features are the eigenvalues of the reconstructed attractor in the odd principal dimensions obtained using the Singular Spectrum Analysis. The K-nearest neighbours (K-NN) method is applied as the classifier tool. The best achieved identification accuracy is 94%.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:605539
Study programmeTitle: Information and Communication Technology
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka informacijske i komunikacijske tehnologije (magistar/magistra inženjer/inženjerka informacijske i komunikacijske tehnologije)
Type of resourceText
File originBorn digital
Access conditionsClosed access
Terms of useLicence In copyright icon
Public note
Created on2018-02-06 10:11:34