Prepoznavanje disleksije pri otrocih s pomočjo analize očesnih gibov

diplomsko delo

Erika Stanković (Author), Jure Žabkar (Mentor)

Abstract

Odkrivanje disleksije pri otroku je dolgotrajen postopek, ki je v Sloveniji trenutno popolnoma odvisen od otrokovih učiteljev in pritiska staršev. Zaradi tega je potreba po računalniškem sistemu, s pomočjo katerega bi lahko na hiter in preprost način izvedli presejalni test, vse večja. V diplomskem delu smo analizirali podatke sledilca očem, pridobljene z aplikacijo za odkrivanje disleksije. Najprej smo v surovih podatkih določili fiksacije in sakade s pomočjo algoritma prepoznavanja s pragom hitrosti. Naslednji korak je bil pridobivanje več različnih skupin značilk, ki opisujejo lastnosti premikov oči. Na skupinah značilk smo izvedli hierarhično gručenje. Rezultati so pokazali, da je najboljše gručenje z značilkami, ki so definirane kot povprečja vseh nalog, a take gruče ne ločujejo med dislektiki in nedislektiki. Z gručenjem z značilkami, ki so v sorodni literaturi navedene kot dobro diskriminatorne za disleksijo, smo pokazali, da lahko v takem gručenju najdemo skupino otrok, ki imajo večje tveganje za disleksijo.

Keywords

disleksija;premiki oči;sledenje pogledu;hierarhično gručenje;računalništvo;računalništvo in informatika;računalništvo in matematika;interdisciplinarni študij;univerzitetni študij;diplomske naloge;

Data

Language:	Slovenian
Year of publishing:	2020
Typology:	2.11 - Undergraduate Thesis
Organization:	UL FRI - Faculty of Computer and Information Science
Publisher:	[E. Stanković]
UDC:	004.8:616.89-008.434.5(043.2)
COBISS:	28552451
Views:	1012
Downloads:	196
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	Screening for dyslexia in children using eye tracking
Secondary abstract:	Screening for dyslexia in children is a long procedure, which currently in Slovenia completely depends on the child's teachers and the pressure from parents. This is why the need for a computer system, which would be able to do a fast and easy screening, is increasing. In this thesis we analysed eye tracker data, which we acquired from an application for screening dyslexia. First, we identified fixations and saccades from raw data using the identification by velocity threshold (IVT) algorithm. The next step was to create multiple different groups of features, which describe the characteristics of eye movements. On these groups of features we used hierarchical clustering. Results showed that the best clustering was the one that used features, defined as averages over all tasks, but these clusters didn't differentiate well between dyslexics and non-dyslexics. By using clustering with features, which are defined as discriminatory for dyslexia in related works, we showed that in this clustering, we can find groups of children that are at higher risk of dyslexia.
Secondary keywords:	dyslexia;eye movements;eye tracking;hierarchical clustering;computer science;computer and information science;computer science and mathematics;interdisciplinary studies;diploma;
Type (COBISS):	Bachelor thesis/paper
Study programme:	1000407
Embargo end date (OpenAIRE):	1970-01-01
Thesis comment:	Univ. v Ljubljani, Fak. za računalništvo in informatiko
Pages:	59 str.
ID:	12027633