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undergraduate thesis
Traženje sličnosti u podacima kontinuiranog praćenja glukoze
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. urn:nbn:hr:168:918507
Jurčić, Krunoslav
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Jurčić, K. (2019). Traženje sličnosti u podacima kontinuiranog praćenja glukoze (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:918507

Jurčić, Krunoslav. "Traženje sličnosti u podacima kontinuiranog praćenja glukoze." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:918507

Jurčić, Krunoslav. "Traženje sličnosti u podacima kontinuiranog praćenja glukoze." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:918507

Jurčić, K. (2019). 'Traženje sličnosti u podacima kontinuiranog praćenja glukoze', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 25 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:918507

Jurčić K. Traženje sličnosti u podacima kontinuiranog praćenja glukoze [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2019 [cited 2024 December 25] Available at: https://urn.nsk.hr/urn:nbn:hr:168:918507

K. Jurčić, "Traženje sličnosti u podacima kontinuiranog praćenja glukoze", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:168:918507

Metadata
TitleTraženje sličnosti u podacima kontinuiranog praćenja glukoze
Title (english)Similarity Search in Continuous Glucose Monitoring Data
AuthorKrunoslav Jurčić
MentorRatko Magjarević (mentor)
Committee memberRatko Magjarević (predsjednik povjerenstva)
Committee memberSara Žulj (član povjerenstva)
Committee memberGoran Šeketa (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2019-09-02, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Electrical Engineering
Abstract
Temeljna ideja ovog rada bila je istražiti metode traženja sličnosti vremenskih nizova, s posebnim naglaskom na fiziološke i biološke vremenske nizove, te onda procijeniti koje metode bi trebale donositi najpreciznije rezultate. Nakon odabira, metode su implementirane u program za usporedbu odsječaka zapisa o kontinuiranom praćenju razine glukoze u krvi sa zadanim uzorkom u trajanju od sat vremena, sa vremenom uzorkovanja 5 minuta. Za implementaciju je korišten programski jezik Matlab. Tokom razvijanja programa te nakon završne implementacije tri metode traženja sličnosti su se ispostavile najpreciznijima pri radu s ovom vrstom podataka: metoda Euklidske udaljenosti, wavelet dekompozicija i dinamičko vremensko savijanje (DTW). Za svaku metodu su izračunate sličnosti za svaki odsječak zapisa. Rezultati su pokazali da su sve tri metode dovoljno precizne i vjerodostojne da bi se mogle koristiti pri traženju sličnosti među signalima razine glukoze u krvi, što bi se moglo pokazati veoma korisnim pri predikciji promjene razine glukoze u krvi u budućnosti.
Abstract (english)
The main idea of this work was to explore the methods of similarity search using time series, with the main focus being on physiological and biological time series, and choose the methods best suitable for these types of time series. After that, the methods are implemented to a programme for comparison between parts of a continuous glucose monitoring time series and a sample with a full duration of one hour, time sampling being 5 minutes. Programming language used for the implementation of this programme was Matlab. During the development of the programme and after the final implementation three methods of similarity search proved most precise with this type of dana: Euclidean distance, wavelet decomposition and dynamic time warping. Similarity search was made using every one of those methods. The results showed that all three methods provided valuable and useful information, and that all of them could be used when searching for similarity between glucose signals, which might prove very useful for future prediction of change of glucose level.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:918507
Study programmeTitle: Electrical Engineering and Information Technology
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka elektrotehnike i informacijske tehnologije (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka elektrotehnike i informacijske tehnologije)
Type of resourceText
File originBorn digital
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Created on2020-01-07 18:49:11