Linked Life Data

7515786

Source:http://linkedlifedata.com/resource/pubmed/id/7515786

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
1994-7-12
pubmed:abstractText
A new method of recognition of epileptic activity using adaptive segmentation in EEG during long-term intensive monitoring was developed in Tampere. The performance of the system was validated and compared to the commercially available discharge recognition system of Gotman. Twelve approximately 30 min EEG segments recorded during intensive monitoring from 6 patients were analysed. On these EEG segments two EEG specialists marked the occurrence of epileptic activity independently. Later they re-evaluated any differences in their scoring. This consensus file was used as a reference in validating the performance of the two computer programs. We found that the program developed in Tampere detected discharge activity more often than the Gotman system. Both systems performed poorly in spike recognition. In the specificity of the recognized segments, the Gotman system was better.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
0013-4694
pubmed:author
pubmed:issnType
Print
pubmed:volume
90
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
438-43
pubmed:dateRevised
2008-9-9
pubmed:meshHeading
pubmed:year
1994
pubmed:articleTitle
Evaluation of a computerized system for recognition of epileptic activity during long-term EEG recording.
pubmed:affiliation
University of Tampere, Department of Neurology, Finland.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't