Low complexity algorithm for seizure prediction using Adaboost

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

Volumn , Issue , 2012, Pages 1061-1064

  Ayinala, Manohar ^a   Parhi, Keshab K ^a  

^a University of Minnesota   (United States)

Author keywords

adaboost; feature selection; power spectral density; prediction; seizure

Indexed keywords

ADABOOST ALGORITHM; BASE CLASSIFIERS; DECISION STUMPS; FALSE ALARM RATE; FALSE ALARMS; FEATURE RANKING; FEATURE SELECTION AND CLASSIFICATION; IMPLANTABLE DEVICES; LINEAR CLASSIFIERS; LOW COMPLEXITY ALGORITHM; LOW COMPUTATIONAL COMPLEXITY; LOW-COMPLEXITY; NONLINEAR CLASSIFIERS; SEIZURE; SEIZURE PREDICTION; SPECTRAL POWER; TIME SPENT;

ALGORITHMS; ELECTROENCEPHALOGRAPHY; ERRORS; FEATURE EXTRACTION; FORECASTING; IMPLANTS (SURGICAL); POWER SPECTRAL DENSITY;

ADAPTIVE BOOSTING;

ALGORITHM; ARTICLE; ELECTRODE IMPLANT; ELECTROENCEPHALOGRAPHY; EQUIPMENT; FEMALE; HUMAN; MALE; METHODOLOGY; PATHOPHYSIOLOGY; PREDICTIVE VALUE; SEIZURE; SIGNAL PROCESSING;

ALGORITHMS; ELECTRODES, IMPLANTED; ELECTROENCEPHALOGRAPHY; FEMALE; HUMANS; MALE; PREDICTIVE VALUE OF TESTS; SEIZURES; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 84870790574     PISSN: 1557170X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/EMBC.2012.6346117     Document Type: Conference Paper

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