Liang, Yiqing, Guest, Richard, Fairhurst, Michael, Potter, Jonathan (2007) Feature-based assessment of visuo-spatial neglect patients using hand-drawing tasks. Pattern Analysis & Applications, 10 (4). pp. 361-374. ISSN 1433-7541. (doi:10.1007/s10044-007-0074-x) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:2586)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
Official URL: http://dx.doi.org/10.1007/s10044-007-0074-x |
Abstract
Visuo-spatial neglect (VSN) is a post-stroke condition in which a patient fails to respond to stimuli on one side of the visual field. Using an established pencil-and-paper-based method for the assessment of VSN (the Rivermead Behavioural Inattention Test) as a reference, a battery of computer-based hand-drawing tests is developed and shown to be effective in distinguishing between stroke subjects with and without neglect. The novel approach adopts measurements both of the outcome and the process by which the drawing tasks are executed. This approach provides a novel diagnostic capability which results in increased test sensitivity, a more objective assessment and a reduction in overall evaluation time. The paper describes the development of a binary assessment system using the computer-based acquisition and analysis of task data alongside feature selection techniques to maximise performance.
Item Type: | Article |
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DOI/Identification number: | 10.1007/s10044-007-0074-x |
Uncontrolled keywords: | diagnostic feature analysis; computer-based drawing assessment |
Subjects: | T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image processing |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts |
Depositing User: | Suzanne Duffy |
Date Deposited: | 31 Mar 2008 17:53 UTC |
Last Modified: | 05 Nov 2024 09:33 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/2586 (The current URI for this page, for reference purposes) |
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