Modulating population granularity for improved diagnosis of developmental dyspraxia from dynamic drawing analysis

Author

Hoque, S. ; Fairhurst, M.C. ; Razian, M.A.

Author_Institution

Dept. of Electron., Kent Univ., Canterbury, UK

fYear

2004

fDate

26-29 Oct. 2004

Firstpage

26

Lastpage

31

Abstract

In this paper, we describe a diagnostic tool for automated assessment of developmental dyspraxia among children using Beery´s VMI test drawings. Various attributes extracted from the dynamic pen movements are used for this assessment. The test environment is exactly the same as that used in conventional VMI tests, except that the test population is partitioned into several age-bands. The population granularity significantly improved the diagnostic accuracy and also revealed interesting results despite limited data availability.

Keywords

feature extraction; handwritten character recognition; medical diagnostic computing; paediatrics; patient diagnosis; developmental dyspraxia; diagnostic tool; dynamic drawing analysis; feature extraction; population granularity; visual motor integration; Automatic speech recognition; Automatic testing; Data mining; Delay effects; Demography; Emotion recognition; Parkinson´s disease; Pediatrics; Shape; Standards development;

fLanguage

English

Publisher

ieee

Conference_Titel

Frontiers in Handwriting Recognition, 2004. IWFHR-9 2004. Ninth International Workshop on

ISSN

1550-5235

Print_ISBN

0-7695-2187-8

Type

conf

DOI

10.1109/IWFHR.2004.69

Filename

1363882