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
fDate :
5/1/1989 12:00:00 AM
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;
Journal_Title :
Biomedical Engineering, IEEE Transactions on