Title :
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
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;
Conference_Titel :
Frontiers in Handwriting Recognition, 2004. IWFHR-9 2004. Ninth International Workshop on
Print_ISBN :
0-7695-2187-8
DOI :
10.1109/IWFHR.2004.69
