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undergraduate thesis
Umjetna inteligencija u nosivim uređajima za praćenje zdravlja ispitanika
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. urn:nbn:hr:168:947674
Akmačić, Lovro
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Akmačić, L. (2024). Umjetna inteligencija u nosivim uređajima za praćenje zdravlja ispitanika (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:947674

Akmačić, Lovro. "Umjetna inteligencija u nosivim uređajima za praćenje zdravlja ispitanika." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:947674

Akmačić, Lovro. "Umjetna inteligencija u nosivim uređajima za praćenje zdravlja ispitanika." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:947674

Akmačić, L. (2024). 'Umjetna inteligencija u nosivim uređajima za praćenje zdravlja ispitanika', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 25 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:947674

Akmačić L. Umjetna inteligencija u nosivim uređajima za praćenje zdravlja ispitanika [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2024 [cited 2024 December 25] Available at: https://urn.nsk.hr/urn:nbn:hr:168:947674

L. Akmačić, "Umjetna inteligencija u nosivim uređajima za praćenje zdravlja ispitanika", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:168:947674

Metadata
TitleUmjetna inteligencija u nosivim uređajima za praćenje zdravlja ispitanika
Title (english)Artificial inteligence in portable health monitoring
AuthorLovro Akmačić
MentorRatko Magjarević (mentor)
Committee memberRatko Magjarević (predsjednik povjerenstva)
Committee memberDavorin Ambruš (član povjerenstva)
Committee memberKrunoslav Jurčić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2024-07-08, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Najčešći korišteni senzori u nosivim uređajima su akcelerometri (za praćenje koraka i prijeđene udaljenosti), fotopletizmografski senzori (za praćenje broja otkucaja srca), altimetri (za praćenje altitude) i žiroskopi (za praćenje koraka i prijeđene udaljenosti). Biološki markeri koji se mogu mjeriti ovise o tipu i modelu nosivog uređaja. Najčešće se procjenjuje broj otkucaja srca, krvni tlak, varijacija temperature kože, estimacija varijacije kisika i disanje. Podatci se snimaju i pohranjuju na nosivom uređaju, no moguće je na aplikaciji ili na webu vidjeti pregled snimljenih podataka, unijeti podatke koje uređaj ne mjeri (tjelesna težina i sl.) i poslati snimljene podatke putem e-pošte ili korištenjem drugih ponuđenih servisa. Statističkom analizom podataka zaključeno ja da model Charge 4 mjeri altitudu uz manju grešku, da promjena broja otkucaja srca ima negativnu korelaciju s promjenom altitude i da je moguće vidjeti mijenjanje broja otkucaja srca tijekom sna s obzirom na različite faze sna.
Abstract (english)
The most commonly used sensors in wearable devices are accelerometers (for monitoring steps and distance traveled), photoplethysmographic sensors (for monitoring heart rate), altimeters (for monitoring altitude) and gyroscopes (for monitoring steps and distance traveled). The biological markers that can be measured depend on the type and model of the wearable device. Heart rate, blood pressure, skin temperature variation, oxygen variation estimation and respiration are most often estimated. The data is recorded and stored on the wearable device, but it is possible to see an overview of the recorded data on the application or on the web, enter data that the device does not measure (body weight, etc.) and send the recorded data via e-mail or using other offered services. The statistical analysis of the data concluded that the Charge 4 model measures altitude with a smaller error, that the change in heart rate has a negative correlation with the change in altitude, and that it is possible to see the change in heart rate during sleep with regard to different stages of sleep.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:947674
Study programmeTitle: Computing
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2024-10-12 19:57:31