Analysing constructional aspects of figure completion for the diagnosis of visuospatial neglect

Guest, Richard and Fairhurst, Michael and Potter, Jonathan and Donnelly, Nick (2000) Analysing constructional aspects of figure completion for the diagnosis of visuospatial neglect. International Conference on Pattern Recognition, 4 . pp. 316-319. ISSN 1051-4651. (The full text of this publication is not available from this repository)

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Abstract

Visuospatial neglect (VSN) is a condition following a stroke or head injury whereby a patient fails to respond to stimuli on one side of the visual field. A standard clinical assessment technique for analysis of VSN is a pencil-and-paper based figure drawing task. Traditional static analysis of this task involves assessing the presence of the major components of the drawing. Marking of drawings is subjective, relying on assessors' own judgement and experience, and therefore no standardisation exists between assessors. Using a computer-based test capture system, this paper establishes a standardised performance assessment for a drawing task including a series of novel dynamic performance features pertaining to the timing and constructional aspects of test performance. A case study of two patients demonstrates the ability to detect VSN from a response which would have traditionally been assessed as normal and hence improve the sensitivity of the task.

Item Type: Article
Additional information: Conference Information: 15th International Conference on Pattern Recognition (ICPR-2000) BARCELONA, SPAIN, SEP 03-07, 2000 Int Assoc Pattern Recognit; Assoc Pattern Recognit & Image Anal; Ctr Visio Comp; Univ Autonoma Barcelona; Univ Politecn Catalunya; Comissionat Universitats Recerca, Generalitat Catalunya Dept Presidencia; Minist Ciencia Tecnol; Fdn Catalana Recerca; HP Invent
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Q Science > Q Science (General) > Q335 Artificial intelligence
Divisions: Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts
Depositing User: O.O. Odanye
Date Deposited: 21 May 2009 07:41
Last Modified: 19 May 2014 10:57
Resource URI: http://kar.kent.ac.uk/id/eprint/16173 (The current URI for this page, for reference purposes)
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