Dyslexia Detection from Eye Movements Using Artificial Neural Networks

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F05%3A03112660" target="_blank" >RIV/68407700:21230/05:03112660 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Dyslexia Detection from Eye Movements Using Artificial Neural Networks

Original language description

The main goal of the study was to propose and implement a neural network based classifier for dyslexia detection from eye movement signal. Eye movements of 76 school children were measured using videooculographic (VOG) technique during one reading and four non-reading tasks. Time and frequency domain features were extracted and various feature selection methods were performed to select subsets of significant features. Finally a feed-forward neural network using back-propagation algorithm was used for asupervised learning. A suitable topology was chose and learning parameters were set experimentally. The final classifier reached about 90% correct identification of the presence of dyslexia and about 90.5% correct identification of the absence of dyslexia.

Czech name

Není k dispozici

Czech description

Není k dispozici

Type

A - Audiovisual production

CEP classification

JC - Computer hardware and software

OECD FORD branch

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Project

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Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2005

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

ISBN

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Place of publication

Praha

Publisher/client name

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Version

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Carrier ID

neuvedeno