DocumentCode :
344154
Title :
Automated and enhanced assessment of unilateral visual neglect
Author :
Garbi ; Smith, S.L. ; Heseltine, D. ; Thomson, P.
Author_Institution :
York Univ., UK
Volume :
1
fYear :
1999
fDate :
36342
Firstpage :
382
Abstract :
This paper describes the application of image processing and data analysis techniques in the development of a new test for unilateral visual neglect. It combines the power of high speed automated processing with implementation in a conventional clinical testing environment. This achieves the ideal scenario of providing fast and enhanced assessment of the patient´s condition whilst maintaining confidence in the testing procedure adopted. The test procedure or task domain requires the patient to provide responses in the form of drawing motions commonly referred to as a paper and pencil activity. These responses are digitised in real-time by means of a conventional digitising tablet. This data is subsequently analysed through a number of static and dynamic measurements which provides those results normally expected from a clinical test of this type and, enhanced spatial profiles that enable the patient´s condition to be uniquely assessed in a more visual and comprehensive manner. Results are provided for a stroke patient previously diagnosed with unilateral visual neglect and a control without any known neurological dysfunction
Keywords :
medical image processing; automated assessment; clinical test; clinical testing environment; data analysis; digitising tablet; dynamic measurements; enhanced assessment; enhanced spatial profiles; high speed automated processing; image processing; patient condition; static measurements; stroke patient; test procedure; unilateral visual neglect;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Image Processing And Its Applications, 1999. Seventh International Conference on (Conf. Publ. No. 465)
Conference_Location :
Manchester
ISSN :
0537-9989
Print_ISBN :
0-85296-717-9
Type :
conf
DOI :
10.1049/cp:19990348
Filename :
791417
Link To Document :
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