Seizure prediction with bipolar spectral power features using Adaboost and SVM classifiers

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

Volumn , Issue , 2013, Pages 6305-6308

  Bandarabadi, Mojtaba ^a   Dourado, Antonio ^a   Teixeira, Cesar A ^a   Netoff, Theoden I ^b   Parhi, Keshab K ^b  

^a UNIVERSITY OF COIMBRA   (Portugal)

^b UNIVERSITY OF MINNESOTA   (United States)

Author keywords

Adaboost; Classification; Epilepsy; Power Spectral Density; Seizure Prediction; Support Vector Machine

Indexed keywords

COMPLEX SUPPORT VECTOR MACHINES; DECISION STUMPS; EPILEPSY; FALSE ALARM RATE; LOWER COMPLEXITY; NONLINEAR GAUSSIAN; SEIZURE PREDICTION; SVM CLASSIFICATION;

CLASSIFICATION (OF INFORMATION); ELECTROENCEPHALOGRAPHY; FORECASTING; POWER SPECTRAL DENSITY; SUPPORT VECTOR MACHINES;

ADAPTIVE BOOSTING;

ADULT; ALGORITHMS; DATABASES, FACTUAL; ELECTROENCEPHALOGRAPHY; FEMALE; HUMANS; MALE; PREDICTIVE VALUE OF TESTS; REPRODUCIBILITY OF RESULTS; SEIZURES; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINES;

ADULT; ALGORITHMS; DATABASES, FACTUAL; ELECTROENCEPHALOGRAPHY; FEMALE; HUMANS; MALE; PREDICTIVE VALUE OF TESTS; REPRODUCIBILITY OF RESULTS; SEIZURES; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINES;

EID: 84886448572     PISSN: 1557170X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/EMBC.2013.6610995     Document Type: Conference Paper

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