Mobilna aplikacija za sledenje frekvenci dihanja

diplomsko delo

Matej Štern (Author), Aleš Holobar (Mentor)

Abstract

V diplomskem delu predstavljamo mobilno aplikacijo, ki s pomočjo vgrajenega pospeškometra meri premike prsnega koša ter sproti vrednoti in izrisuje amplitudo in frekvenco dihanja. Aplikacijo smo zasnovali na operacijskem sistemu Android, testirali pa smo jo na mobilnih telefonih Samsung Galaxy S3 I9300, Samsung Galaxy Note N7000 in Samsung Galaxy Ace S5830. Delovanje aplikacije smo preverili na štirih odraslih zdravih prostovoljcih in enem dojenčku. Meritve dihalnih vzorcev smo opravili tako v mirovanju kot tudi neposredno po krajši telesni vadbi. Posnemali smo tudi različne dihalne motnje in ovrednotili zaznavo nenavadnih dihalnih vzorcev, kot so plitko in hitro dihanje, začasno prekinjeno dihanje in zadržan vdih. V vseh primerih je aplikacija uspešno zaznala praktično vse vdihe in izdihe ter uspešno ovrednotila njihovo frekvenco in amplitudo.

Keywords

razvoj aplikacij;mobilne aplikacije;Android;sledenje frekvenci dihanja;dihanje;zaznavanje dihanja;frekvenca dihanja;pospeškometer;bolezni dihalnega trakta;diplomske naloge;

Data

Language:	Slovenian
Year of publishing:	2013
Typology:	2.11 - Undergraduate Thesis
Organization:	UM FERI - Faculty of Electrical Engineering and Computer Science
Publisher:	[M. Štern]
UDC:	[004.42:621.395.721.5]:612.2(043.2)
COBISS:	17554966
Views:	1169
Downloads:	141
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	MOBILE APPLICATION FOR DETECTION OF RESPIRATORY RATE
Secondary abstract:	This thesis presents a mobile application which, with the help of a built-in accelerometer, measures movements of the chest area, and simultaneously evaluates and delineates amplitude and frequency of breathing. Application was designed for Android operating system, and tested on following mobile phones: Samsung Galaxy S3 I9300, Samsung Galaxy Note N7000 and Samsung Galaxy Ace S5830. The application was tested on four completely healthy adult volunteers and one infant. The measurements of breathing patterns were made both in resting state, and immediately after a short physical activity. We also mimicked different respiratory disorders, and evaluated detection of unusual breathing patterns, such as: shallow and rapid breathing, temporarily suspended breathing, and breath hold. In all cases, the application successfully detected all of inhalations and exhalations, and also successfully evaluated their frequency and amplitude.
Secondary keywords:	application development;mobile applications;respiration;breathing;measurement;accelerometer;
URN:	URN:SI:UM:
Type (COBISS):	Bachelor thesis/paper
Thesis comment:	Univ. v Mariboru, Fak. za elektrotehniko, računalništvo in informatiko, Računalništvo in informacijske tehnologije
Pages:	VII, 36 str.
ID:	8728167