DocumentCode :
968273
Title :
Context-based automated detection of epileptogenic sharp transients in the EEG: elimination of false positives
Author :
Glover, John R., Jr. ; Raghaven, N. ; Ktonas, Periklis Y. ; Frost, James D., Jr.
Author_Institution :
Dept. of Electr. Eng., Houston Univ., TX, USA
Volume :
36
Issue :
5
fYear :
1989
fDate :
5/1/1989 12:00:00 AM
Firstpage :
519
Lastpage :
527
Abstract :
A description is given of a knowledge-based system for the elimination of false positives in the automated detection of epileptogenic sharp transients in the EEG (electroencephalogram). The system makes comprehensive use of spatial and temporal context information available on 16 channels of EEG. EKG, (electrocardiogram) EMG (electromyogram), and EOG (electrooculogram). A knowledge-based implementation is used because of the ease with which it allows the contextual rules to be expressed and refined. The resulting system is shown to be capable of rejecting a wide variety of artifacts commonly found in EEG recordings that cause numerous false positive detections in systems making less comprehensive use of context.
Keywords :
electroencephalography; expert systems; medical diagnostic computing; EEG; artifacts rejection; contextual rules; epileptogenic sharp transients; false positives elimination; knowledge-based system; Blood; Electroencephalography; Electromyography; Electrooculography; Epilepsy; Heart; Helium; Knowledge based systems; Lungs; Nervous system; Artificial Intelligence; Electrocardiography; Electroencephalography; Electromyography; Electrooculography; Epilepsies, Partial; False Positive Reactions; Humans;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/10.24253
Filename :
24253
Link To Document :
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