EEG monitoring based on fuzzy classification

EEG monitoring based on fuzzy classification

The problem of automatic monitoring of electroencephalogram (EEG) recordings is addressed. A new approach based on fuzzy classification of spike events in the EEG is used in a monitoring system to reduce the number of false positive classifications. The overall monitoring system is divided into thre...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Kittel, W.A., Epstein, C.M., Hayes, M.H.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Biomedical monitoring
Computerized monitoring
Electroencephalography
Epilepsy
Fuzzy systems
Medical diagnostic imaging
Patient monitoring
Pattern analysis
Shape
Signal analysis
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Beschreibung
Zusammenfassung:The problem of automatic monitoring of electroencephalogram (EEG) recordings is addressed. A new approach based on fuzzy classification of spike events in the EEG is used in a monitoring system to reduce the number of false positive classifications. The overall monitoring system is divided into three phases of analysis: the transformation of the monitored signals into a symbolic representation; the syntactic classification of potential spikes; and the semantic verification of these spike events for the 16-channel EEG. This system is described along with results from recognition experiments.< >
DOI:10.1109/MWSCAS.1992.271227