Analysis of dysgraphic children based on letter position / Zarith Marissa Mustafa

Analysis of dysgraphic children based on letter position / Zarith Marissa Mustafa

This report will discuss about handwriting disability that is commonly known as dysgraphia. Currently, in Malaysia there are no system that can detect this disease automatically. This disease is detected when the teacher send the student to the occupational therapist when the student is having troub...

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Main Author: Mustafa, Zarith Marissa
Format: Thesis
Language:English
Published: 2015
Online Access:https://ir.uitm.edu.my/id/eprint/64006/1/64006.PDF
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spelling my-uitm-ir.640062023-08-28T07:43:25Z Analysis of dysgraphic children based on letter position / Zarith Marissa Mustafa 2015 Mustafa, Zarith Marissa This report will discuss about handwriting disability that is commonly known as dysgraphia. Currently, in Malaysia there are no system that can detect this disease automatically. This disease is detected when the teacher send the student to the occupational therapist when the student is having trouble in handwriting. This disease also cannot be cured or fixed. There are no medicine for dysgraphia and the children has to do therapy in order to get better. Dysgraphia cannot be detected easilyby just looking at children handwriting because each child has a unique way of writing. The problem of lack of expert in Malaysia has made this disease is harder to detect. The objective for this project are to identify letter positioning features that can classify children with dysgraphia potential symptom. Another objective is to construct a prototype based on Kohonen (SOM) method to classify children with potential dysgraphia symptom whether it is high, medium or low potential. This project consists of six phases which are information gathering, data collection, preliminary data analysis, system design and development, performance evaluation and documentation. The data are collected from Sekolah Kebangsaan Bota Kanan, Bota Perak and Tadika Junior Cergas, Tangkak Johor. Through preliminary data analysis there are six features that has been detected which are overshooting, undershooting, over spacing, under spacing, inconsistent spacing and overlappings pacing. This features had been used in Kohonen algorithm to classify the children whether it is high, medium or low potential of dysgraphia. Based on the result, the system can classified the children same as what the expert are expected. There are many experiments that has been done in order to get a good classifying result. The experiments such as changing the learning rate and different type of activation function had been done in order to obtain the best result. It can be concluded that this prototype system can be a great help especially for identifying child with dysgraphia. The accuracy of the prototype are 60%. The researcher hope in the future this system can automatically detect full dysgraphia symptom. 2015 Thesis https://ir.uitm.edu.my/id/eprint/64006/ https://ir.uitm.edu.my/id/eprint/64006/1/64006.PDF text en public degree Universiti Teknologi Mara (UiTM) Faculty of Computer and Mathematical Sciences Abd Khalid, Noor Elaiza (Dr.)
institution Universiti Teknologi MARA
collection UiTM Institutional Repository
language English
advisor Abd Khalid, Noor Elaiza (Dr.)
description This report will discuss about handwriting disability that is commonly known as dysgraphia. Currently, in Malaysia there are no system that can detect this disease automatically. This disease is detected when the teacher send the student to the occupational therapist when the student is having trouble in handwriting. This disease also cannot be cured or fixed. There are no medicine for dysgraphia and the children has to do therapy in order to get better. Dysgraphia cannot be detected easilyby just looking at children handwriting because each child has a unique way of writing. The problem of lack of expert in Malaysia has made this disease is harder to detect. The objective for this project are to identify letter positioning features that can classify children with dysgraphia potential symptom. Another objective is to construct a prototype based on Kohonen (SOM) method to classify children with potential dysgraphia symptom whether it is high, medium or low potential. This project consists of six phases which are information gathering, data collection, preliminary data analysis, system design and development, performance evaluation and documentation. The data are collected from Sekolah Kebangsaan Bota Kanan, Bota Perak and Tadika Junior Cergas, Tangkak Johor. Through preliminary data analysis there are six features that has been detected which are overshooting, undershooting, over spacing, under spacing, inconsistent spacing and overlappings pacing. This features had been used in Kohonen algorithm to classify the children whether it is high, medium or low potential of dysgraphia. Based on the result, the system can classified the children same as what the expert are expected. There are many experiments that has been done in order to get a good classifying result. The experiments such as changing the learning rate and different type of activation function had been done in order to obtain the best result. It can be concluded that this prototype system can be a great help especially for identifying child with dysgraphia. The accuracy of the prototype are 60%. The researcher hope in the future this system can automatically detect full dysgraphia symptom.
format Thesis
qualification_level Bachelor degree
author Mustafa, Zarith Marissa
spellingShingle Mustafa, Zarith Marissa
Analysis of dysgraphic children based on letter position / Zarith Marissa Mustafa
author_facet Mustafa, Zarith Marissa
author_sort Mustafa, Zarith Marissa
title Analysis of dysgraphic children based on letter position / Zarith Marissa Mustafa
title_short Analysis of dysgraphic children based on letter position / Zarith Marissa Mustafa
title_full Analysis of dysgraphic children based on letter position / Zarith Marissa Mustafa
title_fullStr Analysis of dysgraphic children based on letter position / Zarith Marissa Mustafa
title_full_unstemmed Analysis of dysgraphic children based on letter position / Zarith Marissa Mustafa
title_sort analysis of dysgraphic children based on letter position / zarith marissa mustafa
granting_institution Universiti Teknologi Mara (UiTM)
granting_department Faculty of Computer and Mathematical Sciences
publishDate 2015
url https://ir.uitm.edu.my/id/eprint/64006/1/64006.PDF
_version_ 1783735380792573952

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