Detecting epileptic seizures in long-term human EEG: A new approach to automatic online and real-time detection and classification of polymorphic seizure patterns

Journal of Clinical Neurophysiology

Volumn 25, Issue 3, 2008, Pages 119-131

  Meier, Ralph ^a,b   Dittrich, Heike ^b   Schulze Bonhage, Andreas ^a,b   Aertsen, Ad ^a  

^a UNIVERSITY OF FREIBURG   (Germany)

^b UNIVERSITY OF FREIBURG   (Germany)

Author keywords

Ictal morphology categorization; Long term human EEG; Polymorphic seizure patterns; Seizure detection; Support Vector Machines

Indexed keywords

ALPHA RHYTHM; ARTICLE; BETA RHYTHM; CONTROLLED STUDY; DELTA RHYTHM; DIAGNOSTIC ACCURACY; DIAGNOSTIC PROCEDURE; DIFFERENTIAL DIAGNOSIS; DISEASE CLASSIFICATION; ELECTROENCEPHALOGRAPHY; HUMAN; MAJOR CLINICAL STUDY; PREVALENCE; SEIZURE; THETA RHYTHM; VALIDATION STUDY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SYSTEMS; DIAGNOSIS, COMPUTER-ASSISTED; ELECTROENCEPHALOGRAPHY; EPILEPSY; HUMANS; ONLINE SYSTEMS; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SEIZURES; SENSITIVITY AND SPECIFICITY;

EID: 44649182792     PISSN: 07360258     EISSN: None     Source Type: Journal    
DOI: 10.1097/WNP.0b013e3181775993     Document Type: Article

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