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undergraduate thesis
Korištenje algoritama strojnog učenja za detekciju padova
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. urn:nbn:hr:168:377704
Mak, Matea
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Mak, M. (2018). Korištenje algoritama strojnog učenja za detekciju padova (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:377704

Mak, Matea. "Korištenje algoritama strojnog učenja za detekciju padova." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:377704

Mak, Matea. "Korištenje algoritama strojnog učenja za detekciju padova." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:377704

Mak, M. (2018). 'Korištenje algoritama strojnog učenja za detekciju padova', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 25 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:377704

Mak M. Korištenje algoritama strojnog učenja za detekciju padova [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2018 [cited 2024 December 25] Available at: https://urn.nsk.hr/urn:nbn:hr:168:377704

M. Mak, "Korištenje algoritama strojnog učenja za detekciju padova", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:168:377704

Metadata
TitleKorištenje algoritama strojnog učenja za detekciju padova
Title (english)Using Machine Learning Algorithms in Fall Detection
AuthorMatea Mak
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 country2018-07-13, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Electrical Engineering
Abstract
Veliki broj starijih osoba koje žive samostalno izložene su mogućim padovima i zakašnjeloj reakciji na isti. Cilj ovoga rada je stvarnovremenska detekcija padova implementirana pomoću algoritma strojnog učenja. Podaci koji su korišteni u ovome radu snimani su Shimmer 3 uređajem i obrađivani u Matlab-u. Kreiranjem korisničkog sučelja, korištenjem izgeneriranog algoritma strojnog učenja i simulacijom stvarnovremenske detekcije padova postignuti su zadovoljavajući rezultati i ostvaren je dobar početak za stvarnovremensku detekciju padova.
Abstract (english)
A lot of elderly people that live by themself are exposed to possible falling. If nobody reacts on time, there can be very serious consequences. The main goal of this thesis is real-time fall detection with generated machine learning algorithm. We used Shimmer 3 device to collect data and then we prossesed that data in Matlab. Making user interface and using machine learning algorithm, we achieved very accurate real-time simulation of fall detection.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:377704
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 on2019-03-13 22:30:16